From 4cf3747a7eb8dd25d8182b4d0c3647b82a6d4ca6 Mon Sep 17 00:00:00 2001
From: Panos Mavrogiorgos <pmav99@gmail.com>
Date: Wed, 1 Mar 2023 01:13:17 +0200
Subject: [PATCH] Update pre-commit, linting and dev requirements

1. Disable autofix from pre-commit.ci

2. Add `nbstripout` in pre-commit which is a tool for stripping output from jupyter notebooks.
This is useful for keeping notebook size small and notebook diffs (semi-)sane.

3. Replace `prospector` with `ruff`. `ruff` is way faster and works great as a pre-commit
 hook. Furthermore is under very active development and it is quite easy to enable more
checks.

4. Remove deptry.

5. Require poetry 1.2+ for development since we make use of dependency groups.
For example in the sample notebooks we use use `matplotlib` for
visualization and `scipy` for filling missing IOC data. These are **not** `searvey`
dependencies. They are just something we chose to use in our examples. In this sense it
doesn't make sense to have them as "extras", because installing them will not add any
functionality to `searvey`.  Still we want them to be present in the dev environment in order
to be able to develop/use the notebooks. Dependency groups is an elegant way to
both allow installing them and to keep them separated from "core" and "dev" dependencies.

Note: I removed `black` and `ruff` from the dev-dependencies because we can run them
through pre-commit. The benefit of this approach is that these tools run into their own
dedicated environments and thus we have fewer dependencies in the searvey environment.
Running them should be done with `make style` and `make lint` respectively.
---
 .gitignore                        |    2 +
 .pre-commit-config.yaml           |   37 +-
 .prospector.yml                   |   96 -
 Makefile                          |   23 +-
 README.md                         |   61 +-
 docs/source/conf.py               |    8 +-
 examples/IOC_data.ipynb           | 3225 +----------------------------
 examples/USGS_data.ipynb          | 2381 +--------------------
 examples/coops_data.ipynb         | 1550 +-------------
 poetry.lock                       | 1393 +++++++++----
 pyproject.toml                    |  103 +-
 requirements/requirements-dev.txt |  218 +-
 requirements/requirements.txt     |   72 +-
 searvey/utils.py                  |    5 +-
 tests/ioc_test.py                 |    1 -
 tests/multi_test.py               |    2 +-
 tests/stations_test.py            |    1 -
 tests/usgs_test.py                |    1 -
 18 files changed, 1389 insertions(+), 7790 deletions(-)
 delete mode 100644 .prospector.yml

diff --git a/.gitignore b/.gitignore
index a77cb1e..d4a1c30 100644
--- a/.gitignore
+++ b/.gitignore
@@ -143,3 +143,5 @@ cython_debug/
 
 Notebooks/
 conda.recipe/
+
+ignored/
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 0249ac6..332fe83 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -1,9 +1,10 @@
 ---
+ci:
+  skip: ["mypy", "docs"]
+  autofix_prs: false
 default_language_version:
   python: "python3"
 fail_fast: false
-ci:
-  skip: ["poetry-lock", "lint", "mypy", "docs"]
 
 repos:
   - repo: "https://github.com/pre-commit/pre-commit-hooks"
@@ -41,35 +42,37 @@ repos:
           - "--py38-plus"
 
   - repo: "https://github.com/psf/black"
-    rev: "22.12.0"
+    rev: "23.1.0"
     hooks:
       - id: "black"
 
-  # - repo: "https://github.com/fpgmaas/deptry"
-  #   rev: "0.7.1"
-  #   hooks:
-  #     - id: "deptry"
-  #       args: ["--ignore-notebooks"]
+  - repo: "https://github.com/charliermarsh/ruff-pre-commit"
+    # Ruff version.
+    rev: 'v0.0.253'
+    hooks:
+      - id: "ruff"
+
+  - repo: "https://github.com/kynan/nbstripout"
+    rev: "0.6.1"
+    hooks:
+      - id: "nbstripout"
 
   - repo: "https://github.com/python-poetry/poetry"
-    rev: "1.3.0"
+    rev: "1.4.0"
     hooks:
       - id: "poetry-check"
       - id: "poetry-lock"
+        args: ["--check"]
       - id: "poetry-export"
-        args: ["--without-hashes", "-f", "requirements.txt", "-o", "requirements/requirements.txt"]
+        name: 'poetry export main'
+        args: ["--without-hashes", "--only", "main", "-f", "requirements.txt", "-o", "requirements/requirements.txt"]
       - id: "poetry-export"
-        args: ["--without-hashes", "-f", "requirements.txt", "--dev", "-o", "requirements/requirements-dev.txt"]
+        name: 'poetry export dev'
+        args: ["--without-hashes", "--with", "dev", "--with", "docs", "--with", "jupyter", "-f", "requirements.txt", "-o", "requirements/requirements-dev.txt"]
 
   - repo: "local"
     hooks:
 
-      - id: "lint"
-        name: "lint"
-        entry: "make lint"
-        language: "system"
-        types: ["python"]
-
       - id: "mypy"
         name: "mypy"
         entry: "make mypy"
diff --git a/.prospector.yml b/.prospector.yml
deleted file mode 100644
index eb4c57f..0000000
--- a/.prospector.yml
+++ /dev/null
@@ -1,96 +0,0 @@
----
-
-inherits:
-  - "strictness_veryhigh"
-
-strictness: "veryhigh"
-test-warnings: true
-doc-warnings: true
-member-warnings: true
-
-ignore-paths:
-  - "venv"
-  - "venv.bak"
-  - ".venv"
-  - ".venv.bak"
-  - "docs"
-  # - "test"
-
-pylint:
-  run: false
-  disable:
-    - "bad-continuation"  # there is a conflict with black in function arguments
-    - "empty-docstring"
-    - "fixme"
-    - "line-too-long"
-    - "missing-docstring"
-    - "missing-module-docstring"
-    - "no-else-raise"
-    - "no-else-return"
-    - "too-few-public-methods"
-    - "too-many-arguments"
-    - "wrong-import-order"
-  options:
-    max-line-length: 108
-    extension-pkg-whitelist:
-      - "pydantic"
-    max-args: 7
-    good-names:
-      # counters
-      - "i"
-      - "j"
-      - "k"
-      - "n"
-      # dimensions
-      - "h"
-      - "w"
-      - "l"
-      # vectors
-      - "x"
-      - "y"
-      - "z"
-      # files
-      - "fd"
-      # pandas
-      - "df"
-      - "sr"
-      - "ts"
-      # geopandas
-      - "gs"
-      - "gf"
-      # xarray
-      - "ds"
-      - "da"
-      # matplotlib
-      - "ax"
-      - "rc"
-      # various
-      - "app"
-      - "env"
-      - "id"
-      - "logger"
-      - "router"
-      # alembic
-      - "revision"
-      - "down_revision"
-      - "branch_labels"
-      - "depends_on"
-    contextmanager-decorators:
-      - "contextlib.contextmanager"
-      - "decorator.contextmanager"
-
-mccabe:
-  run: true
-
-pycodestyle:
-  options:
-    max-line-length: 108
-  disable:
-    - "E203"  # disable whitespace before colon - useful for numpy slicing
-    - "E501"  # disable line too length. No reason to check for line length in each and every tool
-
-pydocstyle:
-  run: false
-  disable:
-    - 'D400'
-    - 'D401'
diff --git a/Makefile b/Makefile
index 6481ba8..013712d 100644
--- a/Makefile
+++ b/Makefile
@@ -1,18 +1,31 @@
 .PHONY: list docs
 
 list:
-	@LC_ALL=C $(MAKE) -pRrq -f $(lastword $(MAKEFILE_LIST)) : 2>/dev/null | awk -v RS= -F: '/^# File/,/^# Finished Make data base/ {if ($$1 !~ "^[#.]") {print $$1}}' | sort | egrep -v -e '^[^[:alnum:]]' -e '^$@$$'
+	@LC_ALL=C $(MAKE) -pRrq -f $(lastword $(MAKEFILE_LIST)) : 2>/dev/null | awk -v RS= -F: '/^# File/,/^# Finished Make data base/ {if ($$1 !~ "^[#.]") {print $$1}}' | sort | grep -E -v -e '^[^[:alnum:]]' -e '^$@$$'
+
+init:
+	poetry install --with dev --with docs --with jupyter --sync
+	pre-commit install
+
+style:
+	pre-commit run black -a
 
 lint:
-	prospector --absolute-paths --no-external-config --profile-path .prospector.yaml -w profile-validator searvey
+	pre-commit run ruff -a
 
 mypy:
 	dmypy run searvey
 
+test:
+	python -m pytest -vlx
+
+cov:
+	coverage erase
+	python -m pytest --cov=searvey -n auto --durations=10
+
 docs:
 	make -C docs html
 
 deps:
-	deptry --ignore-notebooks ./
-	poetry export --without-hashes -f requirements.txt -o requirements/requirements.txt
-	poetry export --without-hashes -f requirements.txt --with dev -o requirements/requirements-dev.txt
+	pre-commit run poetry-lock -a
+	pre-commit run poetry-export -a
diff --git a/README.md b/README.md
index 0add3d1..14123a6 100644
--- a/README.md
+++ b/README.md
@@ -7,10 +7,9 @@
 
 Searvey aims to provide the following functionality:
 
-- Unified catalogue of observational data including near real time.
+- Unified catalogue of observational data including near real time (WIP).
 
-- Real time data analysis/clean up to facilitate comparison with numerical
-  models.
+- Real time data analysis/clean up to facilitate comparison with numerical models (WIP).
 
 - On demand data retrieval from multiple sources that currently include:
 
@@ -20,22 +19,66 @@ Searvey aims to provide the following functionality:
 
 ## Installation
 
-The package can be installed with `conda`:
+The package can be installed with `pip`:
+
+```
+pip install searvey
+```
+
+and conda`:
+
+```
+conda install -c conda-forge searvey
+```
 
-`conda install -c conda-forge searvey`
 
 ## Development
 
+In order to develop `searvey` you will need:
+
+- Python 3.8+
+- GNU Make
+- [poetry](https://python-poetry.org/) >= 1.2 (you can install it with [pipx](https://github.com/pypa/pipx): `pipx install poetry`).
+- [poetry-dynamic-versioning](https://github.com/mtkennerly/poetry-dynamic-versioning) which is a poetry plugin.
+  Take note that this needs to be installed in the same (virtual) environment as poetry, not in the `searvey` one!
+  If you used `pipx` for installing `poetry`, then you can inject it in the proper env with `pipx inject poetry poetry-dynamic-versioning`.
+- [pre-commit](https://pre-commit.com/). You can also install this one with `pipx`: `pipx install pre-commit`
+
+In order to setup the dev environment you can use:
+
 ```
 python3 -mvenv .venv
 source .venv/bin/activate
-poetry install
-pre-commit install
+make init
+```
+
+which will:
+
+1. create and activate a virtual environment,
+2. install the full set of dependencies
+3. Setup the pre-commit hooks
+
+After that you should run the tests with:
+
+```
+make test
 ```
 
+If you execute `make` without arguments, you should see more subcommands. E.g.
+
+```
+make mypy
+make lint
+make docs
+make deps
+```
+
+Check them out!
+
+### Jupyter
+
 If you wish to use jupyterlab to test searvey, then, assuming you have an
-existing jupyterlab
-installation, you should be able to add a kernel to it with:
+existing jupyterlab installation, you should be able to add a kernel to it with:
 
 ```bash
 python -m ipykernel install --user --name searvey
diff --git a/docs/source/conf.py b/docs/source/conf.py
index 97c87f9..0dbd5af 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -14,9 +14,7 @@
 from os import PathLike
 from pathlib import Path
 
-import toml
 from dunamai import Version
-from setuptools import config
 
 
 def repository_root(path: PathLike = None) -> Path:
@@ -42,14 +40,12 @@ def repository_root(path: PathLike = None) -> Path:
 )
 
 # -- Project information -----------------------------------------------------
-metadata = toml.load("../../pyproject.toml")["tool"]["poetry"]
-
-project = metadata["name"]
+project = "searvey"
 copyright = f"{datetime.date.today().year}, https://github.com/oceanmodeling"
 
 # The full version, including alpha/beta/rc tags
 try:
-    release = Version.from_any_vcs().serialize()
+    release = Version.from_any_vcs().serialize(dirty=True)
 except RuntimeError:
     release = os.environ.get("VERSION", "0.0.0")
 
diff --git a/examples/IOC_data.ipynb b/examples/IOC_data.ipynb
index 7d9df5e..1ee338b 100644
--- a/examples/IOC_data.ipynb
+++ b/examples/IOC_data.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "724e5b65",
    "metadata": {
     "tags": []
@@ -35,13 +35,6 @@
    "cell_type": "markdown",
    "id": "f3d14b77",
    "metadata": {
-    "execution": {
-     "iopub.execute_input": "2022-06-08T12:43:45.973799Z",
-     "iopub.status.busy": "2022-06-08T12:43:45.973432Z",
-     "iopub.status.idle": "2022-06-08T12:43:51.596147Z",
-     "shell.execute_reply": "2022-06-08T12:43:51.595523Z",
-     "shell.execute_reply.started": "2022-06-08T12:43:45.973779Z"
-    },
     "tags": []
    },
    "source": [
@@ -50,426 +43,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "a204aec2",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>ioc_code</th>\n",
-       "      <th>gloss_id</th>\n",
-       "      <th>lat</th>\n",
-       "      <th>lon</th>\n",
-       "      <th>country</th>\n",
-       "      <th>location</th>\n",
-       "      <th>connection</th>\n",
-       "      <th>contacts</th>\n",
-       "      <th>dcp_id</th>\n",
-       "      <th>last_observation_level</th>\n",
-       "      <th>...</th>\n",
-       "      <th>observations_expected_per_week</th>\n",
-       "      <th>observations_ratio_per_week</th>\n",
-       "      <th>observations_arrived_per_month</th>\n",
-       "      <th>observations_expected_per_month</th>\n",
-       "      <th>observations_ratio_per_month</th>\n",
-       "      <th>observations_ratio_per_day</th>\n",
-       "      <th>sample_interval</th>\n",
-       "      <th>average_delay_per_day</th>\n",
-       "      <th>transmit_interval</th>\n",
-       "      <th>geometry</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>abas</td>\n",
-       "      <td>327</td>\n",
-       "      <td>44.020</td>\n",
-       "      <td>144.290</td>\n",
-       "      <td>Japan</td>\n",
-       "      <td>Abashiri</td>\n",
-       "      <td>SWJP40</td>\n",
-       "      <td>Japan Meteorological Agency ( Japan )</td>\n",
-       "      <td>ABASHIRI</td>\n",
-       "      <td>2.29</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43150</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>10'</td>\n",
-       "      <td>POINT (144.29000 44.02000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>abed</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>57.140</td>\n",
-       "      <td>-2.080</td>\n",
-       "      <td>UK</td>\n",
-       "      <td>Aberdeen</td>\n",
-       "      <td>ftp</td>\n",
-       "      <td>National Oceanography Centre ( UK )</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.36</td>\n",
-       "      <td>...</td>\n",
-       "      <td>672</td>\n",
-       "      <td>100</td>\n",
-       "      <td>2877</td>\n",
-       "      <td>2880.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>15'</td>\n",
-       "      <td>22'</td>\n",
-       "      <td>15'</td>\n",
-       "      <td>POINT (-2.08000 57.14000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>abur</td>\n",
-       "      <td>82</td>\n",
-       "      <td>31.580</td>\n",
-       "      <td>131.410</td>\n",
-       "      <td>Japan</td>\n",
-       "      <td>Aburatsu</td>\n",
-       "      <td>SWJP40</td>\n",
-       "      <td>Japan Meteorological Agency ( Japan )</td>\n",
-       "      <td>ABURATSU</td>\n",
-       "      <td>2.62</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43150</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>10'</td>\n",
-       "      <td>POINT (131.41000 31.58000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>acaj</td>\n",
-       "      <td>182</td>\n",
-       "      <td>13.574</td>\n",
-       "      <td>-89.838</td>\n",
-       "      <td>El Salvador</td>\n",
-       "      <td>Acajutla</td>\n",
-       "      <td>SEMS40</td>\n",
-       "      <td>Ministerio de Medio Ambiente y Recursos Natura...</td>\n",
-       "      <td>50313520</td>\n",
-       "      <td>-1.94</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>89</td>\n",
-       "      <td>42330</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>98</td>\n",
-       "      <td>99</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>3'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-89.83800 13.57400)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>acap</td>\n",
-       "      <td>267</td>\n",
-       "      <td>16.833</td>\n",
-       "      <td>-99.917</td>\n",
-       "      <td>Mexico</td>\n",
-       "      <td>Acapulco</td>\n",
-       "      <td>SEPA40</td>\n",
-       "      <td>Centro de Investigación Científica y de Educac...</td>\n",
-       "      <td>3540E15A</td>\n",
-       "      <td>8.26</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>0</td>\n",
-       "      <td>-down-</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-99.91700 16.83300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1163</th>\n",
-       "      <td>zhap</td>\n",
-       "      <td>78</td>\n",
-       "      <td>21.580</td>\n",
-       "      <td>111.820</td>\n",
-       "      <td>China</td>\n",
-       "      <td>Zhapo</td>\n",
-       "      <td>SZCI01</td>\n",
-       "      <td>China Meteorological Administration ( China )</td>\n",
-       "      <td>09731</td>\n",
-       "      <td>1.90</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>73</td>\n",
-       "      <td>31565</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>73</td>\n",
-       "      <td>71</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>14'</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>POINT (111.82000 21.58000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1164</th>\n",
-       "      <td>zihu</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>17.637</td>\n",
-       "      <td>-101.558</td>\n",
-       "      <td>Mexico</td>\n",
-       "      <td>Zihuatanejo, Gro</td>\n",
-       "      <td>ftp</td>\n",
-       "      <td>Universidad Nacional Autónoma de México ( Mexi...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3.62</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43200</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>18'</td>\n",
-       "      <td>15'</td>\n",
-       "      <td>POINT (-101.55800 17.63700)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1165</th>\n",
-       "      <td>zihu2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>17.636</td>\n",
-       "      <td>-101.558</td>\n",
-       "      <td>Mexico</td>\n",
-       "      <td>Zihuatanejo2</td>\n",
-       "      <td>SOMX10</td>\n",
-       "      <td>Universidad Nacional Autónoma de México ( Mexi...</td>\n",
-       "      <td>0102D23E</td>\n",
-       "      <td>3.65</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>98</td>\n",
-       "      <td>42900</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>99</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>10'</td>\n",
-       "      <td>POINT (-101.55800 17.63600)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1166</th>\n",
-       "      <td>zygi</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>34.727</td>\n",
-       "      <td>33.338</td>\n",
-       "      <td>Cyprus</td>\n",
-       "      <td>Zygi</td>\n",
-       "      <td>ftp</td>\n",
-       "      <td>Cyprus Oceanography Center ( Cyprus )</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.91</td>\n",
-       "      <td>...</td>\n",
-       "      <td>20160</td>\n",
-       "      <td>0</td>\n",
-       "      <td>-down-</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.5'</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>POINT (33.33800 34.72700)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1167</th>\n",
-       "      <td>zygi1</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>34.726</td>\n",
-       "      <td>33.340</td>\n",
-       "      <td>Cyprus</td>\n",
-       "      <td>Zygi</td>\n",
-       "      <td>bgan</td>\n",
-       "      <td>Joint Research Centre ( Europe )</td>\n",
-       "      <td>ZYGI1</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>POINT (33.34000 34.72600)</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1168 rows × 25 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     ioc_code  gloss_id     lat      lon      country          location  \\\n",
-       "0        abas       327  44.020  144.290        Japan          Abashiri   \n",
-       "1        abed      <NA>  57.140   -2.080           UK          Aberdeen   \n",
-       "2        abur        82  31.580  131.410        Japan          Aburatsu   \n",
-       "3        acaj       182  13.574  -89.838  El Salvador          Acajutla   \n",
-       "4        acap       267  16.833  -99.917       Mexico          Acapulco   \n",
-       "...       ...       ...     ...      ...          ...               ...   \n",
-       "1163     zhap        78  21.580  111.820        China             Zhapo   \n",
-       "1164     zihu      <NA>  17.637 -101.558       Mexico  Zihuatanejo, Gro   \n",
-       "1165    zihu2      <NA>  17.636 -101.558       Mexico      Zihuatanejo2   \n",
-       "1166     zygi      <NA>  34.727   33.338       Cyprus              Zygi   \n",
-       "1167    zygi1      <NA>  34.726   33.340       Cyprus              Zygi   \n",
-       "\n",
-       "     connection                                           contacts    dcp_id  \\\n",
-       "0        SWJP40              Japan Meteorological Agency ( Japan )  ABASHIRI   \n",
-       "1           ftp                National Oceanography Centre ( UK )       NaN   \n",
-       "2        SWJP40              Japan Meteorological Agency ( Japan )  ABURATSU   \n",
-       "3        SEMS40  Ministerio de Medio Ambiente y Recursos Natura...  50313520   \n",
-       "4        SEPA40  Centro de Investigación Científica y de Educac...  3540E15A   \n",
-       "...         ...                                                ...       ...   \n",
-       "1163     SZCI01      China Meteorological Administration ( China )     09731   \n",
-       "1164        ftp  Universidad Nacional Autónoma de México ( Mexi...       NaN   \n",
-       "1165     SOMX10  Universidad Nacional Autónoma de México ( Mexi...  0102D23E   \n",
-       "1166        ftp              Cyprus Oceanography Center ( Cyprus )       NaN   \n",
-       "1167       bgan                   Joint Research Centre ( Europe )     ZYGI1   \n",
-       "\n",
-       "      last_observation_level  ... observations_expected_per_week  \\\n",
-       "0                       2.29  ...                          10080   \n",
-       "1                       1.36  ...                            672   \n",
-       "2                       2.62  ...                          10080   \n",
-       "3                      -1.94  ...                          10080   \n",
-       "4                       8.26  ...                          10080   \n",
-       "...                      ...  ...                            ...   \n",
-       "1163                    1.90  ...                          10080   \n",
-       "1164                    3.62  ...                          10080   \n",
-       "1165                    3.65  ...                          10080   \n",
-       "1166                    1.91  ...                          20160   \n",
-       "1167                     NaN  ...                          10080   \n",
-       "\n",
-       "     observations_ratio_per_week observations_arrived_per_month  \\\n",
-       "0                            100                          43150   \n",
-       "1                            100                           2877   \n",
-       "2                            100                          43150   \n",
-       "3                             89                          42330   \n",
-       "4                              0                         -down-   \n",
-       "...                          ...                            ...   \n",
-       "1163                          73                          31565   \n",
-       "1164                         100                          43200   \n",
-       "1165                          98                          42900   \n",
-       "1166                           0                         -down-   \n",
-       "1167                           0                            NaN   \n",
-       "\n",
-       "     observations_expected_per_month observations_ratio_per_month  \\\n",
-       "0                            43200.0                          100   \n",
-       "1                             2880.0                          100   \n",
-       "2                            43200.0                          100   \n",
-       "3                            43200.0                           98   \n",
-       "4                                NaN                            0   \n",
-       "...                              ...                          ...   \n",
-       "1163                         43200.0                           73   \n",
-       "1164                         43200.0                          100   \n",
-       "1165                         43200.0                           99   \n",
-       "1166                             NaN                            0   \n",
-       "1167                             NaN                            0   \n",
-       "\n",
-       "      observations_ratio_per_day  sample_interval average_delay_per_day  \\\n",
-       "0                            100               1'                    8'   \n",
-       "1                            100              15'                   22'   \n",
-       "2                            100               1'                    8'   \n",
-       "3                             99               1'                    3'   \n",
-       "4                              0               1'                   NaN   \n",
-       "...                          ...              ...                   ...   \n",
-       "1163                          71               1'                   14'   \n",
-       "1164                         100               1'                   18'   \n",
-       "1165                         100               1'                    8'   \n",
-       "1166                           0             0.5'                   NaN   \n",
-       "1167                           0               1'                   NaN   \n",
-       "\n",
-       "      transmit_interval                     geometry  \n",
-       "0                   10'   POINT (144.29000 44.02000)  \n",
-       "1                   15'    POINT (-2.08000 57.14000)  \n",
-       "2                   10'   POINT (131.41000 31.58000)  \n",
-       "3                    5'   POINT (-89.83800 13.57400)  \n",
-       "4                    5'   POINT (-99.91700 16.83300)  \n",
-       "...                 ...                          ...  \n",
-       "1163                 1'   POINT (111.82000 21.58000)  \n",
-       "1164                15'  POINT (-101.55800 17.63700)  \n",
-       "1165                10'  POINT (-101.55800 17.63600)  \n",
-       "1166                 1'    POINT (33.33800 34.72700)  \n",
-       "1167                 1'    POINT (33.34000 34.72600)  \n",
-       "\n",
-       "[1168 rows x 25 columns]"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "ioc_stations = ioc.get_ioc_stations()\n",
     "ioc_stations"
@@ -477,25 +56,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "4e59396b",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 864x533.981 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "figure, axis = plt.subplots(1, 1)\n",
     "figure.set_size_inches(12, 12 / 1.61803398875)\n",
@@ -508,31 +74,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "15f54339",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['ioc_code', 'gloss_id', 'lat', 'lon', 'country', 'location',\n",
-       "       'connection', 'contacts', 'dcp_id', 'last_observation_level',\n",
-       "       'last_observation_time', 'delay', 'interval', 'added_to_system',\n",
-       "       'observations_arrived_per_week', 'observations_expected_per_week',\n",
-       "       'observations_ratio_per_week', 'observations_arrived_per_month',\n",
-       "       'observations_expected_per_month', 'observations_ratio_per_month',\n",
-       "       'observations_ratio_per_day', 'sample_interval',\n",
-       "       'average_delay_per_day', 'transmit_interval', 'geometry'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "ioc_stations.columns"
    ]
@@ -541,13 +88,6 @@
    "cell_type": "markdown",
    "id": "8ba13aa2",
    "metadata": {
-    "execution": {
-     "iopub.execute_input": "2022-06-08T12:50:03.778509Z",
-     "iopub.status.busy": "2022-06-08T12:50:03.778244Z",
-     "iopub.status.idle": "2022-06-08T12:50:03.811163Z",
-     "shell.execute_reply": "2022-06-08T12:50:03.810727Z",
-     "shell.execute_reply.started": "2022-06-08T12:50:03.778483Z"
-    },
     "tags": []
    },
    "source": [
@@ -556,1294 +96,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "54da6995",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>ioc_code</th>\n",
-       "      <th>gloss_id</th>\n",
-       "      <th>lat</th>\n",
-       "      <th>lon</th>\n",
-       "      <th>country</th>\n",
-       "      <th>location</th>\n",
-       "      <th>connection</th>\n",
-       "      <th>contacts</th>\n",
-       "      <th>dcp_id</th>\n",
-       "      <th>last_observation_level</th>\n",
-       "      <th>...</th>\n",
-       "      <th>observations_expected_per_week</th>\n",
-       "      <th>observations_ratio_per_week</th>\n",
-       "      <th>observations_arrived_per_month</th>\n",
-       "      <th>observations_expected_per_month</th>\n",
-       "      <th>observations_ratio_per_month</th>\n",
-       "      <th>observations_ratio_per_day</th>\n",
-       "      <th>sample_interval</th>\n",
-       "      <th>average_delay_per_day</th>\n",
-       "      <th>transmit_interval</th>\n",
-       "      <th>geometry</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>acnj</td>\n",
-       "      <td>220</td>\n",
-       "      <td>39.355</td>\n",
-       "      <td>-74.418</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Atlantic City</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3367B730</td>\n",
-       "      <td>0.21</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>99</td>\n",
-       "      <td>43009</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>7'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-74.41800 39.35500)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>acnj2</td>\n",
-       "      <td>220</td>\n",
-       "      <td>39.355</td>\n",
-       "      <td>-74.418</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Atlantic City</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3367B730</td>\n",
-       "      <td>-8.61</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>79</td>\n",
-       "      <td>34630</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>80</td>\n",
-       "      <td>81</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-74.41800 39.35500)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>49</th>\n",
-       "      <td>apfl</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>29.727</td>\n",
-       "      <td>-84.982</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Apalachicola</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3346C2B4</td>\n",
-       "      <td>1.87</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>0</td>\n",
-       "      <td>34211</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>79</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-84.98200 29.72700)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50</th>\n",
-       "      <td>apfl2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>29.727</td>\n",
-       "      <td>-84.982</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Apalachicola</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3346C2B4</td>\n",
-       "      <td>-6.07</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>79</td>\n",
-       "      <td>33925</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>79</td>\n",
-       "      <td>81</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-84.98200 29.72700)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>83</th>\n",
-       "      <td>bamd</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>39.267</td>\n",
-       "      <td>-76.578</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Baltimore</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336577DA</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>17</td>\n",
-       "      <td>7186</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-76.57800 39.26700)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>84</th>\n",
-       "      <td>bamd2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>39.267</td>\n",
-       "      <td>-76.578</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Baltimore</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336577DA</td>\n",
-       "      <td>-4.13</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>77</td>\n",
-       "      <td>33960</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>79</td>\n",
-       "      <td>79</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>9'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-76.57800 39.26700)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>85</th>\n",
-       "      <td>bame</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>44.392</td>\n",
-       "      <td>-68.205</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Bar Harbor</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336747B4</td>\n",
-       "      <td>1.55</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>17</td>\n",
-       "      <td>7198</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>9'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-68.20500 44.39200)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>86</th>\n",
-       "      <td>bame2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>44.392</td>\n",
-       "      <td>-68.205</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Bar Harbor</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336747B4</td>\n",
-       "      <td>-4.67</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>78</td>\n",
-       "      <td>34335</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>79</td>\n",
-       "      <td>81</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-68.20500 44.39200)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>105</th>\n",
-       "      <td>benc</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>34.720</td>\n",
-       "      <td>-76.670</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Beaufort</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3364C6AE</td>\n",
-       "      <td>0.02</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43060</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>7'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-76.67000 34.72000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>106</th>\n",
-       "      <td>benc2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>34.720</td>\n",
-       "      <td>-76.670</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Beaufort</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3364C6AE</td>\n",
-       "      <td>-4.09</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>77</td>\n",
-       "      <td>34065</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>79</td>\n",
-       "      <td>78</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-76.67000 34.72000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>108</th>\n",
-       "      <td>bgct</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>41.173</td>\n",
-       "      <td>-73.182</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Bridgeport</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.40</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>17</td>\n",
-       "      <td>7176</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>6'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-73.18200 41.17300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>109</th>\n",
-       "      <td>bgct2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>41.173</td>\n",
-       "      <td>-73.182</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Bridgeport</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3372E712</td>\n",
-       "      <td>-5.17</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>77</td>\n",
-       "      <td>33455</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>77</td>\n",
-       "      <td>81</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>7'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-73.18200 41.17300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>122</th>\n",
-       "      <td>boma</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>42.355</td>\n",
-       "      <td>-71.052</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Boston</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>335E54EE</td>\n",
-       "      <td>1.87</td>\n",
-       "      <td>...</td>\n",
-       "      <td>1680</td>\n",
-       "      <td>100</td>\n",
-       "      <td>7200</td>\n",
-       "      <td>7200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>6'</td>\n",
-       "      <td>6'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-71.05200 42.35500)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>142</th>\n",
-       "      <td>btny</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>40.700</td>\n",
-       "      <td>-74.020</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Battery The</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336670D4</td>\n",
-       "      <td>0.24</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43047</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>7'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-74.02000 40.70000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>143</th>\n",
-       "      <td>btny2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>40.700</td>\n",
-       "      <td>-74.020</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Battery The</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336670D4</td>\n",
-       "      <td>-4.06</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>78</td>\n",
-       "      <td>33820</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>78</td>\n",
-       "      <td>78</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-74.02000 40.70000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>174</th>\n",
-       "      <td>cbmd</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>38.573</td>\n",
-       "      <td>-76.068</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Cambridge</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3366E5B6</td>\n",
-       "      <td>0.63</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>17</td>\n",
-       "      <td>7199</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>12'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-76.06800 38.57300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>175</th>\n",
-       "      <td>cbmd2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>38.573</td>\n",
-       "      <td>-76.068</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Cambridge</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3366E5B6</td>\n",
-       "      <td>-2.21</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>0</td>\n",
-       "      <td>18827</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>44</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-76.06800 38.57300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>211</th>\n",
-       "      <td>cmnj</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>38.968</td>\n",
-       "      <td>-74.960</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Cape May</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>335D53E0</td>\n",
-       "      <td>0.17</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43030</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>7'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-74.96000 38.96800)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>212</th>\n",
-       "      <td>cmnj2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>38.968</td>\n",
-       "      <td>-74.960</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Cape May</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>335D53E0</td>\n",
-       "      <td>-5.10</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>78</td>\n",
-       "      <td>33915</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>79</td>\n",
-       "      <td>81</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-74.96000 38.96800)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>213</th>\n",
-       "      <td>cnme</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>44.640</td>\n",
-       "      <td>-67.300</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>CutlerNavalBase</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3354305A</td>\n",
-       "      <td>0.77</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>0</td>\n",
-       "      <td>-down-</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-67.30000 44.64000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>258</th>\n",
-       "      <td>cwfl</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>27.978</td>\n",
-       "      <td>-82.832</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Clearwater Beach</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3358C142</td>\n",
-       "      <td>0.80</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>42906</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>99</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>10'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-82.83200 27.97800)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>259</th>\n",
-       "      <td>cwfl2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>27.978</td>\n",
-       "      <td>-82.832</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Clearwater Beach</td>\n",
-       "      <td>SXXX50</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3358C142</td>\n",
-       "      <td>-5.22</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>77</td>\n",
-       "      <td>33865</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>78</td>\n",
-       "      <td>79</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>11'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-82.83200 27.97800)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>260</th>\n",
-       "      <td>cwme</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>44.657</td>\n",
-       "      <td>-67.210</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Cutler Farris Wharf, ME</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>33672252</td>\n",
-       "      <td>2.01</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>17</td>\n",
-       "      <td>7199</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>17</td>\n",
-       "      <td>17</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>6'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-67.21000 44.65700)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>261</th>\n",
-       "      <td>cwme2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>44.657</td>\n",
-       "      <td>-67.210</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Cutler Farris Wharf, ME</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>33672252</td>\n",
-       "      <td>-5.86</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>79</td>\n",
-       "      <td>34090</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>79</td>\n",
-       "      <td>81</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>7'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-67.21000 44.65700)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>281</th>\n",
-       "      <td>dpnc</td>\n",
-       "      <td>219</td>\n",
-       "      <td>36.183</td>\n",
-       "      <td>-75.747</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Duck Pier</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>335DD5F4</td>\n",
-       "      <td>0.18</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>42895</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>99</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-75.74700 36.18300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>301</th>\n",
-       "      <td>epme</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>44.903</td>\n",
-       "      <td>-66.985</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>East Port</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3365875E</td>\n",
-       "      <td>2.93</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43194</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>3'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-66.98500 44.90300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>302</th>\n",
-       "      <td>epme2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>44.903</td>\n",
-       "      <td>-66.985</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>East Port</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3365875E</td>\n",
-       "      <td>-6.80</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>77</td>\n",
-       "      <td>33640</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>78</td>\n",
-       "      <td>79</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>11'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-66.98500 44.90300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>311</th>\n",
-       "      <td>fbfl</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>30.672</td>\n",
-       "      <td>-81.465</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Fernadina Beach</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336782AA</td>\n",
-       "      <td>-0.13</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>42994</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-81.46500 30.67200)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>312</th>\n",
-       "      <td>fbfl2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>30.672</td>\n",
-       "      <td>-81.465</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Fernadina Beach</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336782AA</td>\n",
-       "      <td>-4.85</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>79</td>\n",
-       "      <td>34605</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>80</td>\n",
-       "      <td>79</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>7'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-81.46500 30.67200)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>321</th>\n",
-       "      <td>fmfl</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>26.650</td>\n",
-       "      <td>-81.870</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Fort Myers</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336754C2</td>\n",
-       "      <td>0.46</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43043</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-81.87000 26.65000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>322</th>\n",
-       "      <td>fmfl2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>26.650</td>\n",
-       "      <td>-81.870</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Fort Myers</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>336754C2</td>\n",
-       "      <td>-2.72</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>79</td>\n",
-       "      <td>34370</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>80</td>\n",
-       "      <td>80</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>7'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-81.87000 26.65000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>329</th>\n",
-       "      <td>fpga</td>\n",
-       "      <td>289</td>\n",
-       "      <td>32.033</td>\n",
-       "      <td>-80.902</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Fort Pulaski</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>335F151E</td>\n",
-       "      <td>-0.01</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>42851</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>99</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-80.90200 32.03300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>330</th>\n",
-       "      <td>fpga2</td>\n",
-       "      <td>289</td>\n",
-       "      <td>32.033</td>\n",
-       "      <td>-80.902</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Fort Pulaski</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>335F151E</td>\n",
-       "      <td>-5.83</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>77</td>\n",
-       "      <td>33840</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>78</td>\n",
-       "      <td>78</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>8'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-80.90200 32.03300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>644</th>\n",
-       "      <td>mony</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>41.048</td>\n",
-       "      <td>-71.960</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Montauk, NY</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>33401412</td>\n",
-       "      <td>0.32</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>99</td>\n",
-       "      <td>42966</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>99</td>\n",
-       "      <td>99</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>6'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-71.96000 41.04800)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>645</th>\n",
-       "      <td>mony2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>41.048</td>\n",
-       "      <td>-71.960</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Montauk, NY</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>33401412</td>\n",
-       "      <td>-3.86</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>77</td>\n",
-       "      <td>34200</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>79</td>\n",
-       "      <td>80</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>7'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-71.96000 41.04800)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>842</th>\n",
-       "      <td>ptme</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>43.657</td>\n",
-       "      <td>-70.247</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Portland</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>335F0668</td>\n",
-       "      <td>-3.96</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>93</td>\n",
-       "      <td>40980</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>95</td>\n",
-       "      <td>96</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>9'</td>\n",
-       "      <td>6'</td>\n",
-       "      <td>POINT (-70.24700 43.65700)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>954</th>\n",
-       "      <td>setp1</td>\n",
-       "      <td>211</td>\n",
-       "      <td>26.683</td>\n",
-       "      <td>-78.983</td>\n",
-       "      <td>Bahamas</td>\n",
-       "      <td>Settlement pt</td>\n",
-       "      <td>SEPO40</td>\n",
-       "      <td>Bahamas Department of Meteorology ( Bahamas )+...</td>\n",
-       "      <td>3543234A</td>\n",
-       "      <td>2.87</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>89</td>\n",
-       "      <td>42201</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>98</td>\n",
-       "      <td>99</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>4'</td>\n",
-       "      <td>10'</td>\n",
-       "      <td>POINT (-78.98300 26.68300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1148</th>\n",
-       "      <td>wood</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>41.523</td>\n",
-       "      <td>-70.672</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Woods Hole, MA</td>\n",
-       "      <td>web</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3340A79C</td>\n",
-       "      <td>0.25</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43193</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>100</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>4'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-70.67200 41.52300)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1149</th>\n",
-       "      <td>wood2</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>41.523</td>\n",
-       "      <td>-70.672</td>\n",
-       "      <td>USA</td>\n",
-       "      <td>Woods Hole, MA</td>\n",
-       "      <td>SXXX03</td>\n",
-       "      <td>National Ocean Service-NOAA ( USA )</td>\n",
-       "      <td>3340A79C</td>\n",
-       "      <td>-3.96</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>77</td>\n",
-       "      <td>34165</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>79</td>\n",
-       "      <td>79</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>10'</td>\n",
-       "      <td>5'</td>\n",
-       "      <td>POINT (-70.67200 41.52300)</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>39 rows × 25 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     ioc_code  gloss_id     lat     lon  country                 location  \\\n",
-       "6        acnj       220  39.355 -74.418      USA            Atlantic City   \n",
-       "7       acnj2       220  39.355 -74.418      USA            Atlantic City   \n",
-       "49       apfl      <NA>  29.727 -84.982      USA             Apalachicola   \n",
-       "50      apfl2      <NA>  29.727 -84.982      USA             Apalachicola   \n",
-       "83       bamd      <NA>  39.267 -76.578      USA                Baltimore   \n",
-       "84      bamd2      <NA>  39.267 -76.578      USA                Baltimore   \n",
-       "85       bame      <NA>  44.392 -68.205      USA               Bar Harbor   \n",
-       "86      bame2      <NA>  44.392 -68.205      USA               Bar Harbor   \n",
-       "105      benc      <NA>  34.720 -76.670      USA                 Beaufort   \n",
-       "106     benc2      <NA>  34.720 -76.670      USA                 Beaufort   \n",
-       "108      bgct      <NA>  41.173 -73.182      USA               Bridgeport   \n",
-       "109     bgct2      <NA>  41.173 -73.182      USA               Bridgeport   \n",
-       "122      boma      <NA>  42.355 -71.052      USA                   Boston   \n",
-       "142      btny      <NA>  40.700 -74.020      USA              Battery The   \n",
-       "143     btny2      <NA>  40.700 -74.020      USA              Battery The   \n",
-       "174      cbmd      <NA>  38.573 -76.068      USA                Cambridge   \n",
-       "175     cbmd2      <NA>  38.573 -76.068      USA                Cambridge   \n",
-       "211      cmnj      <NA>  38.968 -74.960      USA                 Cape May   \n",
-       "212     cmnj2      <NA>  38.968 -74.960      USA                 Cape May   \n",
-       "213      cnme      <NA>  44.640 -67.300      USA          CutlerNavalBase   \n",
-       "258      cwfl      <NA>  27.978 -82.832      USA         Clearwater Beach   \n",
-       "259     cwfl2      <NA>  27.978 -82.832      USA         Clearwater Beach   \n",
-       "260      cwme      <NA>  44.657 -67.210      USA  Cutler Farris Wharf, ME   \n",
-       "261     cwme2      <NA>  44.657 -67.210      USA  Cutler Farris Wharf, ME   \n",
-       "281      dpnc       219  36.183 -75.747      USA                Duck Pier   \n",
-       "301      epme      <NA>  44.903 -66.985      USA                East Port   \n",
-       "302     epme2      <NA>  44.903 -66.985      USA                East Port   \n",
-       "311      fbfl      <NA>  30.672 -81.465      USA          Fernadina Beach   \n",
-       "312     fbfl2      <NA>  30.672 -81.465      USA          Fernadina Beach   \n",
-       "321      fmfl      <NA>  26.650 -81.870      USA               Fort Myers   \n",
-       "322     fmfl2      <NA>  26.650 -81.870      USA               Fort Myers   \n",
-       "329      fpga       289  32.033 -80.902      USA             Fort Pulaski   \n",
-       "330     fpga2       289  32.033 -80.902      USA             Fort Pulaski   \n",
-       "644      mony      <NA>  41.048 -71.960      USA              Montauk, NY   \n",
-       "645     mony2      <NA>  41.048 -71.960      USA              Montauk, NY   \n",
-       "842      ptme      <NA>  43.657 -70.247      USA                 Portland   \n",
-       "954     setp1       211  26.683 -78.983  Bahamas            Settlement pt   \n",
-       "1148     wood      <NA>  41.523 -70.672      USA           Woods Hole, MA   \n",
-       "1149    wood2      <NA>  41.523 -70.672      USA           Woods Hole, MA   \n",
-       "\n",
-       "     connection                                           contacts    dcp_id  \\\n",
-       "6           web                National Ocean Service-NOAA ( USA )  3367B730   \n",
-       "7        SXXX03                National Ocean Service-NOAA ( USA )  3367B730   \n",
-       "49          web                National Ocean Service-NOAA ( USA )  3346C2B4   \n",
-       "50       SXXX03                National Ocean Service-NOAA ( USA )  3346C2B4   \n",
-       "83          web                National Ocean Service-NOAA ( USA )  336577DA   \n",
-       "84       SXXX03                National Ocean Service-NOAA ( USA )  336577DA   \n",
-       "85          web                National Ocean Service-NOAA ( USA )  336747B4   \n",
-       "86       SXXX03                National Ocean Service-NOAA ( USA )  336747B4   \n",
-       "105         web                National Ocean Service-NOAA ( USA )  3364C6AE   \n",
-       "106      SXXX03                National Ocean Service-NOAA ( USA )  3364C6AE   \n",
-       "108         web                National Ocean Service-NOAA ( USA )       NaN   \n",
-       "109      SXXX03                National Ocean Service-NOAA ( USA )  3372E712   \n",
-       "122         web                National Ocean Service-NOAA ( USA )  335E54EE   \n",
-       "142         web                National Ocean Service-NOAA ( USA )  336670D4   \n",
-       "143      SXXX03                National Ocean Service-NOAA ( USA )  336670D4   \n",
-       "174         web                National Ocean Service-NOAA ( USA )  3366E5B6   \n",
-       "175      SXXX03                National Ocean Service-NOAA ( USA )  3366E5B6   \n",
-       "211         web                National Ocean Service-NOAA ( USA )  335D53E0   \n",
-       "212      SXXX03                National Ocean Service-NOAA ( USA )  335D53E0   \n",
-       "213         web                National Ocean Service-NOAA ( USA )  3354305A   \n",
-       "258         web                National Ocean Service-NOAA ( USA )  3358C142   \n",
-       "259      SXXX50                National Ocean Service-NOAA ( USA )  3358C142   \n",
-       "260         web                National Ocean Service-NOAA ( USA )  33672252   \n",
-       "261      SXXX03                National Ocean Service-NOAA ( USA )  33672252   \n",
-       "281         web                National Ocean Service-NOAA ( USA )  335DD5F4   \n",
-       "301         web                National Ocean Service-NOAA ( USA )  3365875E   \n",
-       "302      SXXX03                National Ocean Service-NOAA ( USA )  3365875E   \n",
-       "311         web                National Ocean Service-NOAA ( USA )  336782AA   \n",
-       "312      SXXX03                National Ocean Service-NOAA ( USA )  336782AA   \n",
-       "321         web                National Ocean Service-NOAA ( USA )  336754C2   \n",
-       "322      SXXX03                National Ocean Service-NOAA ( USA )  336754C2   \n",
-       "329         web                National Ocean Service-NOAA ( USA )  335F151E   \n",
-       "330      SXXX03                National Ocean Service-NOAA ( USA )  335F151E   \n",
-       "644         web                National Ocean Service-NOAA ( USA )  33401412   \n",
-       "645      SXXX03                National Ocean Service-NOAA ( USA )  33401412   \n",
-       "842      SXXX03                National Ocean Service-NOAA ( USA )  335F0668   \n",
-       "954      SEPO40  Bahamas Department of Meteorology ( Bahamas )+...  3543234A   \n",
-       "1148        web                National Ocean Service-NOAA ( USA )  3340A79C   \n",
-       "1149     SXXX03                National Ocean Service-NOAA ( USA )  3340A79C   \n",
-       "\n",
-       "      last_observation_level  ... observations_expected_per_week  \\\n",
-       "6                       0.21  ...                          10080   \n",
-       "7                      -8.61  ...                          10080   \n",
-       "49                      1.87  ...                          10080   \n",
-       "50                     -6.07  ...                          10080   \n",
-       "83                      0.37  ...                          10080   \n",
-       "84                     -4.13  ...                          10080   \n",
-       "85                      1.55  ...                          10080   \n",
-       "86                     -4.67  ...                          10080   \n",
-       "105                     0.02  ...                          10080   \n",
-       "106                    -4.09  ...                          10080   \n",
-       "108                     1.40  ...                          10080   \n",
-       "109                    -5.17  ...                          10080   \n",
-       "122                     1.87  ...                           1680   \n",
-       "142                     0.24  ...                          10080   \n",
-       "143                    -4.06  ...                          10080   \n",
-       "174                     0.63  ...                          10080   \n",
-       "175                    -2.21  ...                          10080   \n",
-       "211                     0.17  ...                          10080   \n",
-       "212                    -5.10  ...                          10080   \n",
-       "213                     0.77  ...                          10080   \n",
-       "258                     0.80  ...                          10080   \n",
-       "259                    -5.22  ...                          10080   \n",
-       "260                     2.01  ...                          10080   \n",
-       "261                    -5.86  ...                          10080   \n",
-       "281                     0.18  ...                          10080   \n",
-       "301                     2.93  ...                          10080   \n",
-       "302                    -6.80  ...                          10080   \n",
-       "311                    -0.13  ...                          10080   \n",
-       "312                    -4.85  ...                          10080   \n",
-       "321                     0.46  ...                          10080   \n",
-       "322                    -2.72  ...                          10080   \n",
-       "329                    -0.01  ...                          10080   \n",
-       "330                    -5.83  ...                          10080   \n",
-       "644                     0.32  ...                          10080   \n",
-       "645                    -3.86  ...                          10080   \n",
-       "842                    -3.96  ...                          10080   \n",
-       "954                     2.87  ...                          10080   \n",
-       "1148                    0.25  ...                          10080   \n",
-       "1149                   -3.96  ...                          10080   \n",
-       "\n",
-       "     observations_ratio_per_week observations_arrived_per_month  \\\n",
-       "6                             99                          43009   \n",
-       "7                             79                          34630   \n",
-       "49                             0                          34211   \n",
-       "50                            79                          33925   \n",
-       "83                            17                           7186   \n",
-       "84                            77                          33960   \n",
-       "85                            17                           7198   \n",
-       "86                            78                          34335   \n",
-       "105                          100                          43060   \n",
-       "106                           77                          34065   \n",
-       "108                           17                           7176   \n",
-       "109                           77                          33455   \n",
-       "122                          100                           7200   \n",
-       "142                          100                          43047   \n",
-       "143                           78                          33820   \n",
-       "174                           17                           7199   \n",
-       "175                            0                          18827   \n",
-       "211                          100                          43030   \n",
-       "212                           78                          33915   \n",
-       "213                            0                         -down-   \n",
-       "258                          100                          42906   \n",
-       "259                           77                          33865   \n",
-       "260                           17                           7199   \n",
-       "261                           79                          34090   \n",
-       "281                          100                          42895   \n",
-       "301                          100                          43194   \n",
-       "302                           77                          33640   \n",
-       "311                          100                          42994   \n",
-       "312                           79                          34605   \n",
-       "321                          100                          43043   \n",
-       "322                           79                          34370   \n",
-       "329                          100                          42851   \n",
-       "330                           77                          33840   \n",
-       "644                           99                          42966   \n",
-       "645                           77                          34200   \n",
-       "842                           93                          40980   \n",
-       "954                           89                          42201   \n",
-       "1148                         100                          43193   \n",
-       "1149                          77                          34165   \n",
-       "\n",
-       "     observations_expected_per_month observations_ratio_per_month  \\\n",
-       "6                            43200.0                          100   \n",
-       "7                            43200.0                           80   \n",
-       "49                           43200.0                           79   \n",
-       "50                           43200.0                           79   \n",
-       "83                           43200.0                           17   \n",
-       "84                           43200.0                           79   \n",
-       "85                           43200.0                           17   \n",
-       "86                           43200.0                           79   \n",
-       "105                          43200.0                          100   \n",
-       "106                          43200.0                           79   \n",
-       "108                          43200.0                           17   \n",
-       "109                          43200.0                           77   \n",
-       "122                           7200.0                          100   \n",
-       "142                          43200.0                          100   \n",
-       "143                          43200.0                           78   \n",
-       "174                          43200.0                           17   \n",
-       "175                          43200.0                           44   \n",
-       "211                          43200.0                          100   \n",
-       "212                          43200.0                           79   \n",
-       "213                              NaN                            0   \n",
-       "258                          43200.0                           99   \n",
-       "259                          43200.0                           78   \n",
-       "260                          43200.0                           17   \n",
-       "261                          43200.0                           79   \n",
-       "281                          43200.0                           99   \n",
-       "301                          43200.0                          100   \n",
-       "302                          43200.0                           78   \n",
-       "311                          43200.0                          100   \n",
-       "312                          43200.0                           80   \n",
-       "321                          43200.0                          100   \n",
-       "322                          43200.0                           80   \n",
-       "329                          43200.0                           99   \n",
-       "330                          43200.0                           78   \n",
-       "644                          43200.0                           99   \n",
-       "645                          43200.0                           79   \n",
-       "842                          43200.0                           95   \n",
-       "954                          43200.0                           98   \n",
-       "1148                         43200.0                          100   \n",
-       "1149                         43200.0                           79   \n",
-       "\n",
-       "      observations_ratio_per_day  sample_interval average_delay_per_day  \\\n",
-       "6                            100               1'                    7'   \n",
-       "7                             81               1'                    8'   \n",
-       "49                             0               1'                   NaN   \n",
-       "50                            81               1'                    8'   \n",
-       "83                            17               1'                    5'   \n",
-       "84                            79               1'                    9'   \n",
-       "85                            17               1'                    9'   \n",
-       "86                            81               1'                    8'   \n",
-       "105                          100               1'                    7'   \n",
-       "106                           78               1'                    8'   \n",
-       "108                           17               1'                    6'   \n",
-       "109                           81               1'                    7'   \n",
-       "122                          100               6'                    6'   \n",
-       "142                          100               1'                    7'   \n",
-       "143                           78               1'                    8'   \n",
-       "174                           17               1'                   12'   \n",
-       "175                            0               1'                   NaN   \n",
-       "211                          100               1'                    7'   \n",
-       "212                           81               1'                    8'   \n",
-       "213                            0               1'                   NaN   \n",
-       "258                          100               1'                   10'   \n",
-       "259                           79               1'                   11'   \n",
-       "260                           17               1'                    6'   \n",
-       "261                           81               1'                    7'   \n",
-       "281                          100               1'                    5'   \n",
-       "301                          100               1'                    3'   \n",
-       "302                           79               1'                   11'   \n",
-       "311                          100               1'                    5'   \n",
-       "312                           79               1'                    7'   \n",
-       "321                          100               1'                    5'   \n",
-       "322                           80               1'                    7'   \n",
-       "329                          100               1'                    8'   \n",
-       "330                           78               1'                    8'   \n",
-       "644                           99               1'                    6'   \n",
-       "645                           80               1'                    7'   \n",
-       "842                           96               1'                    9'   \n",
-       "954                           99               1'                    4'   \n",
-       "1148                         100               1'                    4'   \n",
-       "1149                          79               1'                   10'   \n",
-       "\n",
-       "      transmit_interval                    geometry  \n",
-       "6                    5'  POINT (-74.41800 39.35500)  \n",
-       "7                    5'  POINT (-74.41800 39.35500)  \n",
-       "49                   5'  POINT (-84.98200 29.72700)  \n",
-       "50                   5'  POINT (-84.98200 29.72700)  \n",
-       "83                   5'  POINT (-76.57800 39.26700)  \n",
-       "84                   5'  POINT (-76.57800 39.26700)  \n",
-       "85                   5'  POINT (-68.20500 44.39200)  \n",
-       "86                   5'  POINT (-68.20500 44.39200)  \n",
-       "105                  5'  POINT (-76.67000 34.72000)  \n",
-       "106                  5'  POINT (-76.67000 34.72000)  \n",
-       "108                  5'  POINT (-73.18200 41.17300)  \n",
-       "109                  5'  POINT (-73.18200 41.17300)  \n",
-       "122                  5'  POINT (-71.05200 42.35500)  \n",
-       "142                  5'  POINT (-74.02000 40.70000)  \n",
-       "143                  5'  POINT (-74.02000 40.70000)  \n",
-       "174                  5'  POINT (-76.06800 38.57300)  \n",
-       "175                  5'  POINT (-76.06800 38.57300)  \n",
-       "211                  5'  POINT (-74.96000 38.96800)  \n",
-       "212                  5'  POINT (-74.96000 38.96800)  \n",
-       "213                  5'  POINT (-67.30000 44.64000)  \n",
-       "258                  5'  POINT (-82.83200 27.97800)  \n",
-       "259                  5'  POINT (-82.83200 27.97800)  \n",
-       "260                  5'  POINT (-67.21000 44.65700)  \n",
-       "261                  5'  POINT (-67.21000 44.65700)  \n",
-       "281                  5'  POINT (-75.74700 36.18300)  \n",
-       "301                  5'  POINT (-66.98500 44.90300)  \n",
-       "302                  5'  POINT (-66.98500 44.90300)  \n",
-       "311                  5'  POINT (-81.46500 30.67200)  \n",
-       "312                  5'  POINT (-81.46500 30.67200)  \n",
-       "321                  5'  POINT (-81.87000 26.65000)  \n",
-       "322                  5'  POINT (-81.87000 26.65000)  \n",
-       "329                  5'  POINT (-80.90200 32.03300)  \n",
-       "330                  5'  POINT (-80.90200 32.03300)  \n",
-       "644                  5'  POINT (-71.96000 41.04800)  \n",
-       "645                  5'  POINT (-71.96000 41.04800)  \n",
-       "842                  6'  POINT (-70.24700 43.65700)  \n",
-       "954                 10'  POINT (-78.98300 26.68300)  \n",
-       "1148                 5'  POINT (-70.67200 41.52300)  \n",
-       "1149                 5'  POINT (-70.67200 41.52300)  \n",
-       "\n",
-       "[39 rows x 25 columns]"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "east_coast = shapely.geometry.box(-85, 25, -65, 45)\n",
     "east_coast\n",
@@ -1854,116 +112,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "9b465177",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>ioc_code</th>\n",
-       "      <th>gloss_id</th>\n",
-       "      <th>lat</th>\n",
-       "      <th>lon</th>\n",
-       "      <th>country</th>\n",
-       "      <th>location</th>\n",
-       "      <th>connection</th>\n",
-       "      <th>contacts</th>\n",
-       "      <th>dcp_id</th>\n",
-       "      <th>last_observation_level</th>\n",
-       "      <th>...</th>\n",
-       "      <th>observations_expected_per_week</th>\n",
-       "      <th>observations_ratio_per_week</th>\n",
-       "      <th>observations_arrived_per_month</th>\n",
-       "      <th>observations_expected_per_month</th>\n",
-       "      <th>observations_ratio_per_month</th>\n",
-       "      <th>observations_ratio_per_day</th>\n",
-       "      <th>sample_interval</th>\n",
-       "      <th>average_delay_per_day</th>\n",
-       "      <th>transmit_interval</th>\n",
-       "      <th>geometry</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>954</th>\n",
-       "      <td>setp1</td>\n",
-       "      <td>211</td>\n",
-       "      <td>26.683</td>\n",
-       "      <td>-78.983</td>\n",
-       "      <td>Bahamas</td>\n",
-       "      <td>Settlement pt</td>\n",
-       "      <td>SEPO40</td>\n",
-       "      <td>Bahamas Department of Meteorology ( Bahamas )+...</td>\n",
-       "      <td>3543234A</td>\n",
-       "      <td>2.87</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10080</td>\n",
-       "      <td>89</td>\n",
-       "      <td>42201</td>\n",
-       "      <td>43200.0</td>\n",
-       "      <td>98</td>\n",
-       "      <td>99</td>\n",
-       "      <td>1'</td>\n",
-       "      <td>4'</td>\n",
-       "      <td>10'</td>\n",
-       "      <td>POINT (-78.98300 26.68300)</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1 rows × 25 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "    ioc_code  gloss_id     lat     lon  country       location connection  \\\n",
-       "954    setp1       211  26.683 -78.983  Bahamas  Settlement pt     SEPO40   \n",
-       "\n",
-       "                                              contacts    dcp_id  \\\n",
-       "954  Bahamas Department of Meteorology ( Bahamas )+...  3543234A   \n",
-       "\n",
-       "     last_observation_level  ... observations_expected_per_week  \\\n",
-       "954                    2.87  ...                          10080   \n",
-       "\n",
-       "    observations_ratio_per_week observations_arrived_per_month  \\\n",
-       "954                          89                          42201   \n",
-       "\n",
-       "    observations_expected_per_month observations_ratio_per_month  \\\n",
-       "954                         43200.0                           98   \n",
-       "\n",
-       "     observations_ratio_per_day  sample_interval average_delay_per_day  \\\n",
-       "954                          99               1'                    4'   \n",
-       "\n",
-       "     transmit_interval                    geometry  \n",
-       "954                10'  POINT (-78.98300 26.68300)  \n",
-       "\n",
-       "[1 rows x 25 columns]"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "east_stations[~east_stations.contacts.str.contains(\"NOAA\")]"
    ]
@@ -1978,472 +132,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "0e14b584",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      " 41%|████████████████████████████████████████████████████▌                                                                           | 16/39 [00:04<00:05,  4.58it/s]2022-07-09 16:31:40,437; INFO    ; ThreadPoolExecutor-0_4 ; searvey.ioc                 264; No data for cnme\n",
-      " 51%|█████████████████████████████████████████████████████████████████▋                                                              | 20/39 [00:05<00:04,  4.12it/s]2022-07-09 16:31:41,377; INFO    ; ThreadPoolExecutor-0_1 ; searvey.ioc                 264; No data for cwme2\n",
-      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 39/39 [00:11<00:00,  3.53it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
-       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "</symbol>\n",
-       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
-       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-array-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: '►';\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: '(';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: ')';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:   (ioc_code: 37, time: 4321)\n",
-       "Coordinates:\n",
-       "  * ioc_code  (ioc_code) object &#x27;acnj&#x27; &#x27;acnj2&#x27; &#x27;apfl&#x27; ... &#x27;setp1&#x27; &#x27;wood&#x27; &#x27;wood2&#x27;\n",
-       "  * time      (time) datetime64[ns] 2020-05-27 ... 2020-05-30\n",
-       "Data variables:\n",
-       "    pwl       (ioc_code, time) float64 nan nan nan nan ... nan -3.898 -3.899\n",
-       "    lon       (ioc_code) float64 -74.42 -74.42 -84.98 ... -78.98 -70.67 -70.67\n",
-       "    lat       (ioc_code) float64 39.35 39.35 29.73 29.73 ... 26.68 41.52 41.52\n",
-       "    country   (ioc_code) object &#x27;USA&#x27; &#x27;USA&#x27; &#x27;USA&#x27; ... &#x27;Bahamas&#x27; &#x27;USA&#x27; &#x27;USA&#x27;\n",
-       "    location  (ioc_code) object &#x27;Atlantic City&#x27; ... &#x27;Woods Hole, MA&#x27;\n",
-       "    wls       (ioc_code, time) float64 1.035 1.035 1.036 1.033 ... nan nan nan\n",
-       "    prs       (ioc_code, time) float64 nan nan nan nan nan ... nan nan nan nan\n",
-       "    ra2       (ioc_code, time) float64 nan nan nan nan nan ... nan nan nan nan\n",
-       "    rad       (ioc_code, time) float64 nan nan nan nan nan ... nan nan nan nan</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-23e285d5-6865-4ac4-be10-a0a3f34b069a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-23e285d5-6865-4ac4-be10-a0a3f34b069a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>ioc_code</span>: 37</li><li><span class='xr-has-index'>time</span>: 4321</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c5b023eb-3627-4ad4-88e3-c6b2e9818ade' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c5b023eb-3627-4ad4-88e3-c6b2e9818ade' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ioc_code</span></div><div class='xr-var-dims'>(ioc_code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;acnj&#x27; &#x27;acnj2&#x27; ... &#x27;wood&#x27; &#x27;wood2&#x27;</div><input id='attrs-6dd4d52f-06de-4b43-9bca-11d1553491f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6dd4d52f-06de-4b43-9bca-11d1553491f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7708d079-f756-44ff-93db-f9bf1407afc1' class='xr-var-data-in' type='checkbox'><label for='data-7708d079-f756-44ff-93db-f9bf1407afc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;acnj&#x27;, &#x27;acnj2&#x27;, &#x27;apfl&#x27;, &#x27;apfl2&#x27;, &#x27;bamd&#x27;, &#x27;bamd2&#x27;, &#x27;bame&#x27;, &#x27;bame2&#x27;,\n",
-       "       &#x27;benc&#x27;, &#x27;benc2&#x27;, &#x27;bgct&#x27;, &#x27;bgct2&#x27;, &#x27;boma&#x27;, &#x27;btny&#x27;, &#x27;btny2&#x27;, &#x27;cbmd&#x27;,\n",
-       "       &#x27;cbmd2&#x27;, &#x27;cmnj&#x27;, &#x27;cmnj2&#x27;, &#x27;cwfl&#x27;, &#x27;cwfl2&#x27;, &#x27;cwme&#x27;, &#x27;dpnc&#x27;, &#x27;epme&#x27;,\n",
-       "       &#x27;epme2&#x27;, &#x27;fbfl&#x27;, &#x27;fbfl2&#x27;, &#x27;fmfl&#x27;, &#x27;fmfl2&#x27;, &#x27;fpga&#x27;, &#x27;fpga2&#x27;, &#x27;mony&#x27;,\n",
-       "       &#x27;mony2&#x27;, &#x27;ptme&#x27;, &#x27;setp1&#x27;, &#x27;wood&#x27;, &#x27;wood2&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-05-27 ... 2020-05-30</div><input id='attrs-29032364-8619-498e-8b4c-97b82eb73a1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-29032364-8619-498e-8b4c-97b82eb73a1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8008a46e-4d1c-4e17-8d58-8c0c56271a4e' class='xr-var-data-in' type='checkbox'><label for='data-8008a46e-4d1c-4e17-8d58-8c0c56271a4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-05-27T00:00:00.000000000&#x27;, &#x27;2020-05-27T00:01:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-27T00:02:00.000000000&#x27;, ..., &#x27;2020-05-29T23:58:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-29T23:59:00.000000000&#x27;, &#x27;2020-05-30T00:00:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a68b0840-d5df-4cc0-8680-7511d110489b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a68b0840-d5df-4cc0-8680-7511d110489b' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>pwl</span></div><div class='xr-var-dims'>(ioc_code, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... nan -3.898 -3.899</div><input id='attrs-1b1e337f-31b0-4377-a9f6-9dedb12dea60' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b1e337f-31b0-4377-a9f6-9dedb12dea60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-472200b4-ca09-4ab2-ae7c-13704737eb0b' class='xr-var-data-in' type='checkbox'><label for='data-472200b4-ca09-4ab2-ae7c-13704737eb0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "       [-7.788, -7.787,    nan, ..., -8.595, -8.597, -8.599],\n",
-       "       [ 0.695,  0.692,  0.689, ...,  0.56 ,  0.559,  0.559],\n",
-       "       ...,\n",
-       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "       [-3.87 , -3.867, -3.867, ...,    nan, -3.898, -3.899]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(ioc_code)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-74.42 -74.42 ... -70.67 -70.67</div><input id='attrs-89864d83-23d6-419b-91bc-0863243bb15d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-89864d83-23d6-419b-91bc-0863243bb15d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-275852f6-9554-492b-897d-05a604782fb9' class='xr-var-data-in' type='checkbox'><label for='data-275852f6-9554-492b-897d-05a604782fb9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-74.418, -74.418, -84.982, -84.982, -76.578, -76.578, -68.205,\n",
-       "       -68.205, -76.67 , -76.67 , -73.182, -73.182, -71.052, -74.02 ,\n",
-       "       -74.02 , -76.068, -76.068, -74.96 , -74.96 , -82.832, -82.832,\n",
-       "       -67.21 , -75.747, -66.985, -66.985, -81.465, -81.465, -81.87 ,\n",
-       "       -81.87 , -80.902, -80.902, -71.96 , -71.96 , -70.247, -78.983,\n",
-       "       -70.672, -70.672])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(ioc_code)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>39.35 39.35 29.73 ... 41.52 41.52</div><input id='attrs-2b48839e-d627-4e11-9f94-c15b58167410' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b48839e-d627-4e11-9f94-c15b58167410' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-865259dd-5c84-4085-8aa0-31d610855a94' class='xr-var-data-in' type='checkbox'><label for='data-865259dd-5c84-4085-8aa0-31d610855a94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([39.355, 39.355, 29.727, 29.727, 39.267, 39.267, 44.392, 44.392,\n",
-       "       34.72 , 34.72 , 41.173, 41.173, 42.355, 40.7  , 40.7  , 38.573,\n",
-       "       38.573, 38.968, 38.968, 27.978, 27.978, 44.657, 36.183, 44.903,\n",
-       "       44.903, 30.672, 30.672, 26.65 , 26.65 , 32.033, 32.033, 41.048,\n",
-       "       41.048, 43.657, 26.683, 41.523, 41.523])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>country</span></div><div class='xr-var-dims'>(ioc_code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;USA&#x27; &#x27;USA&#x27; &#x27;USA&#x27; ... &#x27;USA&#x27; &#x27;USA&#x27;</div><input id='attrs-f9982ed5-5d3e-4c1b-8548-c23217ad8278' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f9982ed5-5d3e-4c1b-8548-c23217ad8278' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adecaf3d-3e49-48a9-8587-64dc00c8b7aa' class='xr-var-data-in' type='checkbox'><label for='data-adecaf3d-3e49-48a9-8587-64dc00c8b7aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;,\n",
-       "       &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;,\n",
-       "       &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;,\n",
-       "       &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;USA&#x27;, &#x27;Bahamas&#x27;, &#x27;USA&#x27;,\n",
-       "       &#x27;USA&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>location</span></div><div class='xr-var-dims'>(ioc_code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Atlantic City&#x27; ... &#x27;Woods Hole,...</div><input id='attrs-65ff5889-9b4c-4d3a-b75e-eff7367bf242' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-65ff5889-9b4c-4d3a-b75e-eff7367bf242' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd25c3b2-1415-4c60-95ba-d8f1a66461f1' class='xr-var-data-in' type='checkbox'><label for='data-fd25c3b2-1415-4c60-95ba-d8f1a66461f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Atlantic City&#x27;, &#x27;Atlantic City&#x27;, &#x27;Apalachicola&#x27;, &#x27;Apalachicola&#x27;,\n",
-       "       &#x27;Baltimore&#x27;, &#x27;Baltimore&#x27;, &#x27;Bar Harbor&#x27;, &#x27;Bar Harbor&#x27;, &#x27;Beaufort&#x27;,\n",
-       "       &#x27;Beaufort&#x27;, &#x27;Bridgeport&#x27;, &#x27;Bridgeport&#x27;, &#x27;Boston&#x27;, &#x27;Battery The&#x27;,\n",
-       "       &#x27;Battery The&#x27;, &#x27;Cambridge&#x27;, &#x27;Cambridge&#x27;, &#x27;Cape May&#x27;, &#x27;Cape May&#x27;,\n",
-       "       &#x27;Clearwater Beach&#x27;, &#x27;Clearwater Beach&#x27;, &#x27;Cutler Farris Wharf, ME&#x27;,\n",
-       "       &#x27;Duck Pier&#x27;, &#x27;East Port&#x27;, &#x27;East Port&#x27;, &#x27;Fernadina Beach&#x27;,\n",
-       "       &#x27;Fernadina Beach&#x27;, &#x27;Fort Myers&#x27;, &#x27;Fort Myers&#x27;, &#x27;Fort Pulaski&#x27;,\n",
-       "       &#x27;Fort Pulaski&#x27;, &#x27;Montauk, NY&#x27;, &#x27;Montauk, NY&#x27;, &#x27;Portland&#x27;,\n",
-       "       &#x27;Settlement pt&#x27;, &#x27;Woods Hole, MA&#x27;, &#x27;Woods Hole, MA&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wls</span></div><div class='xr-var-dims'>(ioc_code, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.035 1.035 1.036 ... nan nan nan</div><input id='attrs-97e8f9aa-f6cf-498a-acb6-6133fc18c5a9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-97e8f9aa-f6cf-498a-acb6-6133fc18c5a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de5be48d-ad72-4592-904a-25f84010e9a9' class='xr-var-data-in' type='checkbox'><label for='data-de5be48d-ad72-4592-904a-25f84010e9a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.035, 1.035, 1.036, ..., 0.235, 0.228, 0.226],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       ...,\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [0.338, 0.339, 0.342, ..., 0.308, 0.308, 0.311],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prs</span></div><div class='xr-var-dims'>(ioc_code, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-61c1b645-b397-4cd2-a528-7a6f5a805508' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-61c1b645-b397-4cd2-a528-7a6f5a805508' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3f41e32-7489-4993-b1c2-b3d2a8f00517' class='xr-var-data-in' type='checkbox'><label for='data-f3f41e32-7489-4993-b1c2-b3d2a8f00517' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       ...,\n",
-       "       [3.189, 3.189, 3.19 , ..., 3.206, 3.204, 3.201],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ra2</span></div><div class='xr-var-dims'>(ioc_code, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f332a754-7078-43c1-b1fb-0cdd24882b75' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f332a754-7078-43c1-b1fb-0cdd24882b75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ebb85f3-bbff-4149-a8b7-ada1e2a2a1c9' class='xr-var-data-in' type='checkbox'><label for='data-8ebb85f3-bbff-4149-a8b7-ada1e2a2a1c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       ...,\n",
-       "       [2.911, 2.915, 2.915, ..., 2.918, 2.914, 2.911],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rad</span></div><div class='xr-var-dims'>(ioc_code, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a208ce0b-02a3-4afc-a3c8-a5423f2a408f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a208ce0b-02a3-4afc-a3c8-a5423f2a408f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48a25735-8bdb-45cf-a757-2677537cf600' class='xr-var-data-in' type='checkbox'><label for='data-48a25735-8bdb-45cf-a757-2677537cf600' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       ...,\n",
-       "       [6.264, 6.263, 6.264, ..., 2.932, 2.935, 2.92 ],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4f0e6d04-6c3c-4d72-a205-b0740fa2bf00' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4f0e6d04-6c3c-4d72-a205-b0740fa2bf00' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:   (ioc_code: 37, time: 4321)\n",
-       "Coordinates:\n",
-       "  * ioc_code  (ioc_code) object 'acnj' 'acnj2' 'apfl' ... 'setp1' 'wood' 'wood2'\n",
-       "  * time      (time) datetime64[ns] 2020-05-27 ... 2020-05-30\n",
-       "Data variables:\n",
-       "    pwl       (ioc_code, time) float64 nan nan nan nan ... nan -3.898 -3.899\n",
-       "    lon       (ioc_code) float64 -74.42 -74.42 -84.98 ... -78.98 -70.67 -70.67\n",
-       "    lat       (ioc_code) float64 39.35 39.35 29.73 29.73 ... 26.68 41.52 41.52\n",
-       "    country   (ioc_code) object 'USA' 'USA' 'USA' ... 'Bahamas' 'USA' 'USA'\n",
-       "    location  (ioc_code) object 'Atlantic City' ... 'Woods Hole, MA'\n",
-       "    wls       (ioc_code, time) float64 1.035 1.035 1.036 1.033 ... nan nan nan\n",
-       "    prs       (ioc_code, time) float64 nan nan nan nan nan ... nan nan nan nan\n",
-       "    ra2       (ioc_code, time) float64 nan nan nan nan nan ... nan nan nan nan\n",
-       "    rad       (ioc_code, time) float64 nan nan nan nan nan ... nan nan nan nan"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "east_data = ioc.get_ioc_data(\n",
     "    ioc_metadata=east_stations,\n",
@@ -2455,404 +149,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "9fe12042",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
-       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "</symbol>\n",
-       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
-       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-array-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: '►';\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: '(';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: ')';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:   (time: 4321)\n",
-       "Coordinates:\n",
-       "    ioc_code  &lt;U5 &#x27;setp1&#x27;\n",
-       "  * time      (time) datetime64[ns] 2020-05-27 ... 2020-05-30\n",
-       "Data variables:\n",
-       "    lon       float64 -78.98\n",
-       "    lat       float64 26.68\n",
-       "    country   object &#x27;Bahamas&#x27;\n",
-       "    location  object &#x27;Settlement pt&#x27;\n",
-       "    prs       (time) float64 3.189 3.189 3.19 3.192 ... 3.2 3.206 3.204 3.201\n",
-       "    ra2       (time) float64 2.911 2.915 2.915 2.917 ... 2.921 2.918 2.914 2.911\n",
-       "    rad       (time) float64 6.264 6.263 6.264 6.264 ... 2.932 2.932 2.935 2.92</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4d541d08-478d-41de-99b4-0d1f6fc5ea17' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4d541d08-478d-41de-99b4-0d1f6fc5ea17' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 4321</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-47cdbef5-e54d-4a65-a28b-faede730415e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-47cdbef5-e54d-4a65-a28b-faede730415e' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ioc_code</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U5</div><div class='xr-var-preview xr-preview'>&#x27;setp1&#x27;</div><input id='attrs-37bc9f30-0363-4cc1-9406-c8a6d5b9063d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-37bc9f30-0363-4cc1-9406-c8a6d5b9063d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f594eab4-5908-4dd0-a4ea-2e5ebd63e9a4' class='xr-var-data-in' type='checkbox'><label for='data-f594eab4-5908-4dd0-a4ea-2e5ebd63e9a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;setp1&#x27;, dtype=&#x27;&lt;U5&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-05-27 ... 2020-05-30</div><input id='attrs-91187e9f-0309-4e26-818a-179f108c6958' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-91187e9f-0309-4e26-818a-179f108c6958' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3759a90-6478-4c81-9f39-968b001aa39d' class='xr-var-data-in' type='checkbox'><label for='data-e3759a90-6478-4c81-9f39-968b001aa39d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-05-27T00:00:00.000000000&#x27;, &#x27;2020-05-27T00:01:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-27T00:02:00.000000000&#x27;, ..., &#x27;2020-05-29T23:58:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-29T23:59:00.000000000&#x27;, &#x27;2020-05-30T00:00:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-510da009-c4b0-418e-a1fe-5a7a000b9abf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-510da009-c4b0-418e-a1fe-5a7a000b9abf' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.98</div><input id='attrs-2841d23a-9aff-4591-8a33-259c23b039cf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2841d23a-9aff-4591-8a33-259c23b039cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2952df5-dd36-423b-a266-a49de8dada6b' class='xr-var-data-in' type='checkbox'><label for='data-c2952df5-dd36-423b-a266-a49de8dada6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(-78.983)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>26.68</div><input id='attrs-0c4c93a4-9181-4a23-b60e-962ba11068d1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c4c93a4-9181-4a23-b60e-962ba11068d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8988b42-0e82-4e33-9b49-3ce13abbfd36' class='xr-var-data-in' type='checkbox'><label for='data-d8988b42-0e82-4e33-9b49-3ce13abbfd36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(26.683)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>country</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Bahamas&#x27;</div><input id='attrs-888f9643-f22e-4ae6-9845-9f64d0abab67' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-888f9643-f22e-4ae6-9845-9f64d0abab67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e845ec69-a878-4147-b096-08ed6b507a75' class='xr-var-data-in' type='checkbox'><label for='data-e845ec69-a878-4147-b096-08ed6b507a75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;Bahamas&#x27;, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>location</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Settlement pt&#x27;</div><input id='attrs-e0cdaa47-4441-4983-b4e1-34112ee03feb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e0cdaa47-4441-4983-b4e1-34112ee03feb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1d55309-0301-460d-b3be-09a530a45f6e' class='xr-var-data-in' type='checkbox'><label for='data-c1d55309-0301-460d-b3be-09a530a45f6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;Settlement pt&#x27;, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prs</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.189 3.189 3.19 ... 3.204 3.201</div><input id='attrs-f04dc416-d6d0-4004-9ea2-c1df858974b2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f04dc416-d6d0-4004-9ea2-c1df858974b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a6e65a0-0e79-4654-9ca9-d5c93e10f3f5' class='xr-var-data-in' type='checkbox'><label for='data-3a6e65a0-0e79-4654-9ca9-d5c93e10f3f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3.189, 3.189, 3.19 , ..., 3.206, 3.204, 3.201])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ra2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.911 2.915 2.915 ... 2.914 2.911</div><input id='attrs-db9ac368-268f-42e5-adf1-6dd720a7f6b2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db9ac368-268f-42e5-adf1-6dd720a7f6b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f280f5d-6578-453c-9180-a726f54e9de9' class='xr-var-data-in' type='checkbox'><label for='data-8f280f5d-6578-453c-9180-a726f54e9de9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2.911, 2.915, 2.915, ..., 2.918, 2.914, 2.911])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rad</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.264 6.263 6.264 ... 2.935 2.92</div><input id='attrs-40a9ce6a-0cac-4bd7-b8a0-faae71418451' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-40a9ce6a-0cac-4bd7-b8a0-faae71418451' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2a63500-4865-4550-806e-2928721601ab' class='xr-var-data-in' type='checkbox'><label for='data-e2a63500-4865-4550-806e-2928721601ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.264, 6.263, 6.264, ..., 2.932, 2.935, 2.92 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a72deb73-7e81-433e-a2c2-8995f7e8942f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a72deb73-7e81-433e-a2c2-8995f7e8942f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:   (time: 4321)\n",
-       "Coordinates:\n",
-       "    ioc_code  <U5 'setp1'\n",
-       "  * time      (time) datetime64[ns] 2020-05-27 ... 2020-05-30\n",
-       "Data variables:\n",
-       "    lon       float64 -78.98\n",
-       "    lat       float64 26.68\n",
-       "    country   object 'Bahamas'\n",
-       "    location  object 'Settlement pt'\n",
-       "    prs       (time) float64 3.189 3.189 3.19 3.192 ... 3.2 3.206 3.204 3.201\n",
-       "    ra2       (time) float64 2.911 2.915 2.915 2.917 ... 2.921 2.918 2.914 2.911\n",
-       "    rad       (time) float64 6.264 6.263 6.264 6.264 ... 2.932 2.932 2.935 2.92"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "def drop_all_nan_vars(ds: xr.Dataset) -> xr.Dataset:\n",
     "    for var in ds.data_vars:\n",
@@ -2864,435 +166,53 @@
     "ds"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d64a8f98-e4cf-43c6-961e-ef9c268b1212",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "As you can see not all the data are suitable for use...\n",
+    "\n",
+    "More specifically, the `rad` seems to have been re-calibrated in the afternoon of 2020-05-28:"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "id": "0a6b56d0",
+   "execution_count": null,
+   "id": "561cb02d-8542-41e1-917b-6307ef6163f0",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fix, axes = plt.subplots(1, 1)\n",
     "\n",
-    "_ = ds.prs.plot(ax=axes)\n",
-    "_ = ds.rad.plot(ax=axes)\n",
-    "_ = ds.ra2.plot(ax=axes)"
+    "_ = ds.prs.plot(ax=axes, label=\"prs\")\n",
+    "_ = ds.rad.plot(ax=axes, label=\"rad\")\n",
+    "_ = ds.ra2.plot(ax=axes, label=\"ra2\")\n",
+    "axes.legend()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "72fc8a45-0dd6-46a9-a55b-52f1054c7919",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Similarly some stations might have missing data"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "id": "9b40f51e",
+   "execution_count": null,
+   "id": "7d9301bd-456a-4844-9103-137c94e2708c",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
-       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "</symbol>\n",
-       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
-       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-array-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: '►';\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: '(';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: ')';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:   (time: 4321)\n",
-       "Coordinates:\n",
-       "    ioc_code  &lt;U5 &#x27;setp1&#x27;\n",
-       "  * time      (time) datetime64[ns] 2020-05-27 ... 2020-05-30\n",
-       "Data variables:\n",
-       "    lon       float64 -78.98\n",
-       "    lat       float64 26.68\n",
-       "    country   object &#x27;Bahamas&#x27;\n",
-       "    location  object &#x27;Settlement pt&#x27;\n",
-       "    prs       (time) float64 3.189 3.189 3.19 3.192 ... 3.2 3.206 3.204 3.201\n",
-       "    ra2       (time) float64 2.911 2.915 2.915 2.917 ... 2.921 2.918 2.914 2.911\n",
-       "    rad       (time) float64 6.264 6.263 6.264 6.264 ... 2.932 2.932 2.935 2.92</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8029af28-2850-4c27-b452-4a2974c3f752' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8029af28-2850-4c27-b452-4a2974c3f752' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 4321</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-51603ee7-ea73-4896-ada9-18b5906b1fef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-51603ee7-ea73-4896-ada9-18b5906b1fef' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ioc_code</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U5</div><div class='xr-var-preview xr-preview'>&#x27;setp1&#x27;</div><input id='attrs-12eb51ec-4140-498f-96ca-8b409a2bb911' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-12eb51ec-4140-498f-96ca-8b409a2bb911' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecf8e228-511a-4dc5-88e3-36dc3ea85d0c' class='xr-var-data-in' type='checkbox'><label for='data-ecf8e228-511a-4dc5-88e3-36dc3ea85d0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;setp1&#x27;, dtype=&#x27;&lt;U5&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-05-27 ... 2020-05-30</div><input id='attrs-f5ea3010-8289-4360-a804-649ed63659d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f5ea3010-8289-4360-a804-649ed63659d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3efd231-1c6c-4a7d-8913-fc031816452e' class='xr-var-data-in' type='checkbox'><label for='data-d3efd231-1c6c-4a7d-8913-fc031816452e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-05-27T00:00:00.000000000&#x27;, &#x27;2020-05-27T00:01:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-27T00:02:00.000000000&#x27;, ..., &#x27;2020-05-29T23:58:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-29T23:59:00.000000000&#x27;, &#x27;2020-05-30T00:00:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-401b3250-7121-4fe3-ab41-eac3f5766e1a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-401b3250-7121-4fe3-ab41-eac3f5766e1a' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.98</div><input id='attrs-5b98719e-09ed-4e29-81a5-510e42a7df49' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b98719e-09ed-4e29-81a5-510e42a7df49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae4fe585-4ec2-4bbb-a902-7ebfab9ec29f' class='xr-var-data-in' type='checkbox'><label for='data-ae4fe585-4ec2-4bbb-a902-7ebfab9ec29f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(-78.983)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>26.68</div><input id='attrs-3a6bb925-e9c5-4449-ac8b-64d4fab39f09' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3a6bb925-e9c5-4449-ac8b-64d4fab39f09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f546803b-a74c-4453-9002-1a3bc700a56c' class='xr-var-data-in' type='checkbox'><label for='data-f546803b-a74c-4453-9002-1a3bc700a56c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(26.683)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>country</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Bahamas&#x27;</div><input id='attrs-66f8a771-66a6-4863-a853-8936e52f4319' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-66f8a771-66a6-4863-a853-8936e52f4319' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b126f2d9-c177-46a3-a31a-150777039d52' class='xr-var-data-in' type='checkbox'><label for='data-b126f2d9-c177-46a3-a31a-150777039d52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;Bahamas&#x27;, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>location</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Settlement pt&#x27;</div><input id='attrs-a55a265d-ce2c-4ea6-92df-34f77f29bb27' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a55a265d-ce2c-4ea6-92df-34f77f29bb27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cd686fe-9c4d-4692-97e0-fa6bef544657' class='xr-var-data-in' type='checkbox'><label for='data-3cd686fe-9c4d-4692-97e0-fa6bef544657' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;Settlement pt&#x27;, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prs</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.189 3.189 3.19 ... 3.204 3.201</div><input id='attrs-1dc54630-43a1-41cc-8e8b-4c36f11d9d1e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1dc54630-43a1-41cc-8e8b-4c36f11d9d1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc48f761-898b-4f3f-b1b0-393f7ec7c741' class='xr-var-data-in' type='checkbox'><label for='data-cc48f761-898b-4f3f-b1b0-393f7ec7c741' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3.189, 3.189, 3.19 , ..., 3.206, 3.204, 3.201])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ra2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.911 2.915 2.915 ... 2.914 2.911</div><input id='attrs-6e099b12-79e0-473e-bbbd-398c136b3046' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e099b12-79e0-473e-bbbd-398c136b3046' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e9966dd-984e-492b-b960-4bd4fd276ae6' class='xr-var-data-in' type='checkbox'><label for='data-8e9966dd-984e-492b-b960-4bd4fd276ae6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2.911, 2.915, 2.915, ..., 2.918, 2.914, 2.911])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rad</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.264 6.263 6.264 ... 2.935 2.92</div><input id='attrs-ea044fa9-f6e8-4700-a2c2-bf8f175098fe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea044fa9-f6e8-4700-a2c2-bf8f175098fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09fcd9d8-0cfc-4c42-8620-51d110ec6017' class='xr-var-data-in' type='checkbox'><label for='data-09fcd9d8-0cfc-4c42-8620-51d110ec6017' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.264, 6.263, 6.264, ..., 2.932, 2.935, 2.92 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7aa3b383-a17b-467b-8c4d-2bc3fcf10aca' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7aa3b383-a17b-467b-8c4d-2bc3fcf10aca' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:   (time: 4321)\n",
-       "Coordinates:\n",
-       "    ioc_code  <U5 'setp1'\n",
-       "  * time      (time) datetime64[ns] 2020-05-27 ... 2020-05-30\n",
-       "Data variables:\n",
-       "    lon       float64 -78.98\n",
-       "    lat       float64 26.68\n",
-       "    country   object 'Bahamas'\n",
-       "    location  object 'Settlement pt'\n",
-       "    prs       (time) float64 3.189 3.189 3.19 3.192 ... 3.2 3.206 3.204 3.201\n",
-       "    ra2       (time) float64 2.911 2.915 2.915 2.917 ... 2.921 2.918 2.914 2.911\n",
-       "    rad       (time) float64 6.264 6.263 6.264 6.264 ... 2.932 2.932 2.935 2.92"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "bahamas = ds.where(ds.country == \"Bahamas\")\n",
     "bahamas"
@@ -3300,36 +220,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "id": "d094168d",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x165327d60>]"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "bahamas.ra2.plot()"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "44256c2b-c47c-4e76-9224-f062e8d9b40b",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Trying to fill the missing values is not that difficult, but you probably need to review the results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "90ed21e7-7dc5-4ebb-8291-ada8ceff70b9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "bahamas.ra2.interpolate_na(dim=\"time\", method=\"linear\").plot()"
+   ]
   }
  ],
  "metadata": {
@@ -3348,7 +267,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.9.16"
   }
  },
  "nbformat": 4,
diff --git a/examples/USGS_data.ipynb b/examples/USGS_data.ipynb
index 54efb17..bfea7bd 100644
--- a/examples/USGS_data.ipynb
+++ b/examples/USGS_data.ipynb
@@ -37,13 +37,6 @@
    "cell_type": "markdown",
    "id": "f3d14b77",
    "metadata": {
-    "execution": {
-     "iopub.execute_input": "2022-06-08T12:43:45.973799Z",
-     "iopub.status.busy": "2022-06-08T12:43:45.973432Z",
-     "iopub.status.idle": "2022-06-08T12:43:51.596147Z",
-     "shell.execute_reply": "2022-06-08T12:43:51.595523Z",
-     "shell.execute_reply.started": "2022-06-08T12:43:45.973779Z"
-    },
     "tags": []
    },
    "source": [
@@ -52,413 +45,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "a204aec2",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>agency_cd</th>\n",
-       "      <th>site_no</th>\n",
-       "      <th>station_nm</th>\n",
-       "      <th>site_tp_cd</th>\n",
-       "      <th>dec_lat_va</th>\n",
-       "      <th>dec_long_va</th>\n",
-       "      <th>coord_acy_cd</th>\n",
-       "      <th>dec_coord_datum_cd</th>\n",
-       "      <th>alt_va</th>\n",
-       "      <th>alt_acy_va</th>\n",
-       "      <th>...</th>\n",
-       "      <th>ts_id</th>\n",
-       "      <th>loc_web_ds</th>\n",
-       "      <th>medium_grp_cd</th>\n",
-       "      <th>parm_grp_cd</th>\n",
-       "      <th>srs_id</th>\n",
-       "      <th>access_cd</th>\n",
-       "      <th>begin_date</th>\n",
-       "      <th>end_date</th>\n",
-       "      <th>count_nu</th>\n",
-       "      <th>geometry</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>0234296910</td>\n",
-       "      <td>CHATTAHOOCHEE RIVER AT COAST GUARD DOCK AT EUF...</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>31.908216</td>\n",
-       "      <td>-85.144932</td>\n",
-       "      <td>U</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.01</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2006-01-01</td>\n",
-       "      <td>2022-01-01</td>\n",
-       "      <td>14</td>\n",
-       "      <td>POINT (-85.14493 31.90822)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>0234296910</td>\n",
-       "      <td>CHATTAHOOCHEE RIVER AT COAST GUARD DOCK AT EUF...</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>31.908216</td>\n",
-       "      <td>-85.144932</td>\n",
-       "      <td>U</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.01</td>\n",
-       "      <td>...</td>\n",
-       "      <td>298232</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642503</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2017-09-30</td>\n",
-       "      <td>2023-02-02</td>\n",
-       "      <td>1931</td>\n",
-       "      <td>POINT (-85.14493 31.90822)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>0234296910</td>\n",
-       "      <td>CHATTAHOOCHEE RIVER AT COAST GUARD DOCK AT EUF...</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>31.908216</td>\n",
-       "      <td>-85.144932</td>\n",
-       "      <td>U</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.01</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1990-03-18</td>\n",
-       "      <td>2017-02-22</td>\n",
-       "      <td>28</td>\n",
-       "      <td>POINT (-85.14493 31.90822)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>0234296910</td>\n",
-       "      <td>CHATTAHOOCHEE RIVER AT COAST GUARD DOCK AT EUF...</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>31.908216</td>\n",
-       "      <td>-85.144932</td>\n",
-       "      <td>U</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.01</td>\n",
-       "      <td>...</td>\n",
-       "      <td>234483</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642503</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2010-10-01</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>4508</td>\n",
-       "      <td>POINT (-85.14493 31.90822)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>02464800</td>\n",
-       "      <td>LAKE TUSCALOOSA NEAR TUSCALOOSA, ALABAMA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>33.267339</td>\n",
-       "      <td>-87.506116</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.10</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2006-01-01</td>\n",
-       "      <td>2022-01-01</td>\n",
-       "      <td>17</td>\n",
-       "      <td>POINT (-87.50612 33.26734)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>244062</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>14240304</td>\n",
-       "      <td>SPIRIT LAKE AT TUNNEL AT SPIRIT LAKE, WA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>46.276221</td>\n",
-       "      <td>-122.162597</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>3470.0</td>\n",
-       "      <td>10.00</td>\n",
-       "      <td>...</td>\n",
-       "      <td>152146</td>\n",
-       "      <td>[LAKE LEVEL]</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642503</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2007-10-01</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>5604</td>\n",
-       "      <td>POINT (-122.16260 46.27622)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>244063</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>14240304</td>\n",
-       "      <td>SPIRIT LAKE AT TUNNEL AT SPIRIT LAKE, WA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>46.276221</td>\n",
-       "      <td>-122.162597</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>3470.0</td>\n",
-       "      <td>10.00</td>\n",
-       "      <td>...</td>\n",
-       "      <td>152147</td>\n",
-       "      <td>LEVEL AT INTAKE GATE</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642503</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-10-06</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>120</td>\n",
-       "      <td>POINT (-122.16260 46.27622)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>244064</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>14240446</td>\n",
-       "      <td>CASTLE LAKE NEAR MOUNT ST. HELENS, WA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>46.256389</td>\n",
-       "      <td>-122.274444</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2006-01-01</td>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>15</td>\n",
-       "      <td>POINT (-122.27444 46.25639)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>244065</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>14240446</td>\n",
-       "      <td>CASTLE LAKE NEAR MOUNT ST. HELENS, WA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>46.256389</td>\n",
-       "      <td>-122.274444</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>150471</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642503</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1993-10-01</td>\n",
-       "      <td>2023-01-30</td>\n",
-       "      <td>9729</td>\n",
-       "      <td>POINT (-122.27444 46.25639)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>244066</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>14240446</td>\n",
-       "      <td>CASTLE LAKE NEAR MOUNT ST. HELENS, WA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>46.256389</td>\n",
-       "      <td>-122.274444</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>152151</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642503</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2008-01-16</td>\n",
-       "      <td>2023-01-31</td>\n",
-       "      <td>5494</td>\n",
-       "      <td>POINT (-122.27444 46.25639)</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>244067 rows × 25 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       agency_cd     site_no  \\\n",
-       "0           USGS  0234296910   \n",
-       "1           USGS  0234296910   \n",
-       "2           USGS  0234296910   \n",
-       "3           USGS  0234296910   \n",
-       "4           USGS    02464800   \n",
-       "...          ...         ...   \n",
-       "244062      USGS    14240304   \n",
-       "244063      USGS    14240304   \n",
-       "244064      USGS    14240446   \n",
-       "244065      USGS    14240446   \n",
-       "244066      USGS    14240446   \n",
-       "\n",
-       "                                               station_nm site_tp_cd  \\\n",
-       "0       CHATTAHOOCHEE RIVER AT COAST GUARD DOCK AT EUF...         LK   \n",
-       "1       CHATTAHOOCHEE RIVER AT COAST GUARD DOCK AT EUF...         LK   \n",
-       "2       CHATTAHOOCHEE RIVER AT COAST GUARD DOCK AT EUF...         LK   \n",
-       "3       CHATTAHOOCHEE RIVER AT COAST GUARD DOCK AT EUF...         LK   \n",
-       "4                LAKE TUSCALOOSA NEAR TUSCALOOSA, ALABAMA         LK   \n",
-       "...                                                   ...        ...   \n",
-       "244062           SPIRIT LAKE AT TUNNEL AT SPIRIT LAKE, WA         LK   \n",
-       "244063           SPIRIT LAKE AT TUNNEL AT SPIRIT LAKE, WA         LK   \n",
-       "244064              CASTLE LAKE NEAR MOUNT ST. HELENS, WA         LK   \n",
-       "244065              CASTLE LAKE NEAR MOUNT ST. HELENS, WA         LK   \n",
-       "244066              CASTLE LAKE NEAR MOUNT ST. HELENS, WA         LK   \n",
-       "\n",
-       "        dec_lat_va  dec_long_va coord_acy_cd dec_coord_datum_cd  alt_va  \\\n",
-       "0        31.908216   -85.144932            U              NAD83     0.0   \n",
-       "1        31.908216   -85.144932            U              NAD83     0.0   \n",
-       "2        31.908216   -85.144932            U              NAD83     0.0   \n",
-       "3        31.908216   -85.144932            U              NAD83     0.0   \n",
-       "4        33.267339   -87.506116            S              NAD83     0.0   \n",
-       "...            ...          ...          ...                ...     ...   \n",
-       "244062   46.276221  -122.162597            S              NAD83  3470.0   \n",
-       "244063   46.276221  -122.162597            S              NAD83  3470.0   \n",
-       "244064   46.256389  -122.274444            S              NAD83     NaN   \n",
-       "244065   46.256389  -122.274444            S              NAD83     NaN   \n",
-       "244066   46.256389  -122.274444            S              NAD83     NaN   \n",
-       "\n",
-       "        alt_acy_va  ...   ts_id            loc_web_ds medium_grp_cd  \\\n",
-       "0             0.01  ...       0                   NaN           wat   \n",
-       "1             0.01  ...  298232                   NaN           wat   \n",
-       "2             0.01  ...       0                   NaN           wat   \n",
-       "3             0.01  ...  234483                   NaN           wat   \n",
-       "4             0.10  ...       0                   NaN           wat   \n",
-       "...            ...  ...     ...                   ...           ...   \n",
-       "244062       10.00  ...  152146          [LAKE LEVEL]           wat   \n",
-       "244063       10.00  ...  152147  LEVEL AT INTAKE GATE           wat   \n",
-       "244064         NaN  ...       0                   NaN           wat   \n",
-       "244065         NaN  ...  150471                   NaN           wat   \n",
-       "244066         NaN  ...  152151                   NaN           wat   \n",
-       "\n",
-       "       parm_grp_cd   srs_id  access_cd begin_date   end_date count_nu  \\\n",
-       "0              NaN        0          0 2006-01-01 2022-01-01       14   \n",
-       "1              NaN  1642503          0 2017-09-30 2023-02-02     1931   \n",
-       "2              NaN        0          0 1990-03-18 2017-02-22       28   \n",
-       "3              NaN  1642503          0 2010-10-01 2023-02-03     4508   \n",
-       "4              NaN        0          0 2006-01-01 2022-01-01       17   \n",
-       "...            ...      ...        ...        ...        ...      ...   \n",
-       "244062         NaN  1642503          0 2007-10-01 2023-02-03     5604   \n",
-       "244063         NaN  1642503          0 2022-10-06 2023-02-03      120   \n",
-       "244064         NaN        0          0 2006-01-01 2020-01-01       15   \n",
-       "244065         NaN  1642503          0 1993-10-01 2023-01-30     9729   \n",
-       "244066         NaN  1642503          0 2008-01-16 2023-01-31     5494   \n",
-       "\n",
-       "                           geometry  \n",
-       "0        POINT (-85.14493 31.90822)  \n",
-       "1        POINT (-85.14493 31.90822)  \n",
-       "2        POINT (-85.14493 31.90822)  \n",
-       "3        POINT (-85.14493 31.90822)  \n",
-       "4        POINT (-87.50612 33.26734)  \n",
-       "...                             ...  \n",
-       "244062  POINT (-122.16260 46.27622)  \n",
-       "244063  POINT (-122.16260 46.27622)  \n",
-       "244064  POINT (-122.27444 46.25639)  \n",
-       "244065  POINT (-122.27444 46.25639)  \n",
-       "244066  POINT (-122.27444 46.25639)  \n",
-       "\n",
-       "[244067 rows x 25 columns]"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "usgs_stations = usgs.get_usgs_stations()\n",
     "usgs_stations"
@@ -466,23 +58,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "4e59396b",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 1200x741.641 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "figure, axis = plt.subplots(1, 1)\n",
     "figure.set_size_inches(12, 12 / 1.61803398875)\n",
@@ -497,29 +78,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "15f54339",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['agency_cd', 'site_no', 'station_nm', 'site_tp_cd', 'dec_lat_va',\n",
-       "       'dec_long_va', 'coord_acy_cd', 'dec_coord_datum_cd', 'alt_va',\n",
-       "       'alt_acy_va', 'alt_datum_cd', 'huc_cd', 'data_type_cd', 'parm_cd',\n",
-       "       'stat_cd', 'ts_id', 'loc_web_ds', 'medium_grp_cd', 'parm_grp_cd',\n",
-       "       'srs_id', 'access_cd', 'begin_date', 'end_date', 'count_nu',\n",
-       "       'geometry'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "usgs_stations.columns"
    ]
@@ -528,13 +92,6 @@
    "cell_type": "markdown",
    "id": "8ba13aa2",
    "metadata": {
-    "execution": {
-     "iopub.execute_input": "2022-06-08T12:50:03.778509Z",
-     "iopub.status.busy": "2022-06-08T12:50:03.778244Z",
-     "iopub.status.idle": "2022-06-08T12:50:03.811163Z",
-     "shell.execute_reply": "2022-06-08T12:50:03.810727Z",
-     "shell.execute_reply.started": "2022-06-08T12:50:03.778483Z"
-    },
     "tags": []
    },
    "source": [
@@ -543,413 +100,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "54da6995",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>agency_cd</th>\n",
-       "      <th>site_no</th>\n",
-       "      <th>station_nm</th>\n",
-       "      <th>site_tp_cd</th>\n",
-       "      <th>dec_lat_va</th>\n",
-       "      <th>dec_long_va</th>\n",
-       "      <th>coord_acy_cd</th>\n",
-       "      <th>dec_coord_datum_cd</th>\n",
-       "      <th>alt_va</th>\n",
-       "      <th>alt_acy_va</th>\n",
-       "      <th>...</th>\n",
-       "      <th>ts_id</th>\n",
-       "      <th>loc_web_ds</th>\n",
-       "      <th>medium_grp_cd</th>\n",
-       "      <th>parm_grp_cd</th>\n",
-       "      <th>srs_id</th>\n",
-       "      <th>access_cd</th>\n",
-       "      <th>begin_date</th>\n",
-       "      <th>end_date</th>\n",
-       "      <th>count_nu</th>\n",
-       "      <th>geometry</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>425227073212401</td>\n",
-       "      <td>RE 108</td>\n",
-       "      <td>GW</td>\n",
-       "      <td>42.874375</td>\n",
-       "      <td>-73.356731</td>\n",
-       "      <td>H</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>451.0</td>\n",
-       "      <td>4.3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642461</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2017-03-09</td>\n",
-       "      <td>2017-03-09</td>\n",
-       "      <td>1</td>\n",
-       "      <td>POINT (-73.35673 42.87438)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>425227073212401</td>\n",
-       "      <td>RE 108</td>\n",
-       "      <td>GW</td>\n",
-       "      <td>42.874375</td>\n",
-       "      <td>-73.356731</td>\n",
-       "      <td>H</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>451.0</td>\n",
-       "      <td>4.3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642461</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2017-03-09</td>\n",
-       "      <td>2017-03-09</td>\n",
-       "      <td>1</td>\n",
-       "      <td>POINT (-73.35673 42.87438)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>425227073212401</td>\n",
-       "      <td>RE 108</td>\n",
-       "      <td>GW</td>\n",
-       "      <td>42.874375</td>\n",
-       "      <td>-73.356731</td>\n",
-       "      <td>H</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>451.0</td>\n",
-       "      <td>4.3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642008</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2017-03-09</td>\n",
-       "      <td>2017-03-09</td>\n",
-       "      <td>1</td>\n",
-       "      <td>POINT (-73.35673 42.87438)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>425227073212401</td>\n",
-       "      <td>RE 108</td>\n",
-       "      <td>GW</td>\n",
-       "      <td>42.874375</td>\n",
-       "      <td>-73.356731</td>\n",
-       "      <td>H</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>451.0</td>\n",
-       "      <td>4.3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>233087</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2017-03-06</td>\n",
-       "      <td>2017-03-08</td>\n",
-       "      <td>2</td>\n",
-       "      <td>POINT (-73.35673 42.87438)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>425227073212401</td>\n",
-       "      <td>RE 108</td>\n",
-       "      <td>GW</td>\n",
-       "      <td>42.874375</td>\n",
-       "      <td>-73.356731</td>\n",
-       "      <td>H</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>451.0</td>\n",
-       "      <td>4.3</td>\n",
-       "      <td>...</td>\n",
-       "      <td>217132</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642461</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2017-02-22</td>\n",
-       "      <td>2017-03-09</td>\n",
-       "      <td>15</td>\n",
-       "      <td>POINT (-73.35673 42.87438)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6668</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>422302071083801</td>\n",
-       "      <td>FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>42.383889</td>\n",
-       "      <td>-71.143889</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>27.6</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>67561</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1644459</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2009-10-01</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>4873</td>\n",
-       "      <td>POINT (-71.14389 42.38389)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6669</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>422302071083801</td>\n",
-       "      <td>FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>42.383889</td>\n",
-       "      <td>-71.143889</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>27.6</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>67557</td>\n",
-       "      <td>[(2)]</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2007-10-01</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>5604</td>\n",
-       "      <td>POINT (-71.14389 42.38389)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6670</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>422302071083801</td>\n",
-       "      <td>FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>42.383889</td>\n",
-       "      <td>-71.143889</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>27.6</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>67560</td>\n",
-       "      <td>Fresh Pond Sonde</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1646694</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2007-10-01</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>5604</td>\n",
-       "      <td>POINT (-71.14389 42.38389)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6671</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>422302071083801</td>\n",
-       "      <td>FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>42.383889</td>\n",
-       "      <td>-71.143889</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>27.6</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>225988</td>\n",
-       "      <td>Huron Ave Gatehouse, [Data provided by CWD]</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1643311</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-10-06</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>120</td>\n",
-       "      <td>POINT (-71.14389 42.38389)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6672</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>422302071083801</td>\n",
-       "      <td>FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>42.383889</td>\n",
-       "      <td>-71.143889</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>27.6</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>225987</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1648328</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2007-10-01</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>5604</td>\n",
-       "      <td>POINT (-71.14389 42.38389)</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>6673 rows × 25 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     agency_cd          site_no                                 station_nm  \\\n",
-       "0         USGS  425227073212401                                     RE 108   \n",
-       "1         USGS  425227073212401                                     RE 108   \n",
-       "2         USGS  425227073212401                                     RE 108   \n",
-       "3         USGS  425227073212401                                     RE 108   \n",
-       "4         USGS  425227073212401                                     RE 108   \n",
-       "...        ...              ...                                        ...   \n",
-       "6668      USGS  422302071083801  FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA   \n",
-       "6669      USGS  422302071083801  FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA   \n",
-       "6670      USGS  422302071083801  FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA   \n",
-       "6671      USGS  422302071083801  FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA   \n",
-       "6672      USGS  422302071083801  FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA   \n",
-       "\n",
-       "     site_tp_cd  dec_lat_va  dec_long_va coord_acy_cd dec_coord_datum_cd  \\\n",
-       "0            GW   42.874375   -73.356731            H              NAD83   \n",
-       "1            GW   42.874375   -73.356731            H              NAD83   \n",
-       "2            GW   42.874375   -73.356731            H              NAD83   \n",
-       "3            GW   42.874375   -73.356731            H              NAD83   \n",
-       "4            GW   42.874375   -73.356731            H              NAD83   \n",
-       "...         ...         ...          ...          ...                ...   \n",
-       "6668         LK   42.383889   -71.143889            S              NAD83   \n",
-       "6669         LK   42.383889   -71.143889            S              NAD83   \n",
-       "6670         LK   42.383889   -71.143889            S              NAD83   \n",
-       "6671         LK   42.383889   -71.143889            S              NAD83   \n",
-       "6672         LK   42.383889   -71.143889            S              NAD83   \n",
-       "\n",
-       "      alt_va  alt_acy_va  ...   ts_id  \\\n",
-       "0      451.0         4.3  ...       0   \n",
-       "1      451.0         4.3  ...       0   \n",
-       "2      451.0         4.3  ...       0   \n",
-       "3      451.0         4.3  ...  233087   \n",
-       "4      451.0         4.3  ...  217132   \n",
-       "...      ...         ...  ...     ...   \n",
-       "6668    27.6         5.0  ...   67561   \n",
-       "6669    27.6         5.0  ...   67557   \n",
-       "6670    27.6         5.0  ...   67560   \n",
-       "6671    27.6         5.0  ...  225988   \n",
-       "6672    27.6         5.0  ...  225987   \n",
-       "\n",
-       "                                       loc_web_ds medium_grp_cd parm_grp_cd  \\\n",
-       "0                                             NaN           wat         NaN   \n",
-       "1                                             NaN           wat         NaN   \n",
-       "2                                             NaN           wat         NaN   \n",
-       "3                                             NaN           wat         NaN   \n",
-       "4                                             NaN           wat         NaN   \n",
-       "...                                           ...           ...         ...   \n",
-       "6668                                          NaN           wat         NaN   \n",
-       "6669                                        [(2)]           wat         NaN   \n",
-       "6670                             Fresh Pond Sonde           wat         NaN   \n",
-       "6671  Huron Ave Gatehouse, [Data provided by CWD]           wat         NaN   \n",
-       "6672                                          NaN           wat         NaN   \n",
-       "\n",
-       "       srs_id  access_cd begin_date   end_date count_nu  \\\n",
-       "0     1642461          0 2017-03-09 2017-03-09        1   \n",
-       "1     1642461          0 2017-03-09 2017-03-09        1   \n",
-       "2     1642008          0 2017-03-09 2017-03-09        1   \n",
-       "3           0          0 2017-03-06 2017-03-08        2   \n",
-       "4     1642461          0 2017-02-22 2017-03-09       15   \n",
-       "...       ...        ...        ...        ...      ...   \n",
-       "6668  1644459          0 2009-10-01 2023-02-03     4873   \n",
-       "6669        0          0 2007-10-01 2023-02-03     5604   \n",
-       "6670  1646694          0 2007-10-01 2023-02-03     5604   \n",
-       "6671  1643311          0 2022-10-06 2023-02-03      120   \n",
-       "6672  1648328          0 2007-10-01 2023-02-03     5604   \n",
-       "\n",
-       "                        geometry  \n",
-       "0     POINT (-73.35673 42.87438)  \n",
-       "1     POINT (-73.35673 42.87438)  \n",
-       "2     POINT (-73.35673 42.87438)  \n",
-       "3     POINT (-73.35673 42.87438)  \n",
-       "4     POINT (-73.35673 42.87438)  \n",
-       "...                          ...  \n",
-       "6668  POINT (-71.14389 42.38389)  \n",
-       "6669  POINT (-71.14389 42.38389)  \n",
-       "6670  POINT (-71.14389 42.38389)  \n",
-       "6671  POINT (-71.14389 42.38389)  \n",
-       "6672  POINT (-71.14389 42.38389)  \n",
-       "\n",
-       "[6673 rows x 25 columns]"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "us_northeast = shapely.geometry.box(-75, 40, -70, 45)\n",
     "us_northeast\n",
@@ -960,413 +116,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "9b465177",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>agency_cd</th>\n",
-       "      <th>site_no</th>\n",
-       "      <th>station_nm</th>\n",
-       "      <th>site_tp_cd</th>\n",
-       "      <th>dec_lat_va</th>\n",
-       "      <th>dec_long_va</th>\n",
-       "      <th>coord_acy_cd</th>\n",
-       "      <th>dec_coord_datum_cd</th>\n",
-       "      <th>alt_va</th>\n",
-       "      <th>alt_acy_va</th>\n",
-       "      <th>...</th>\n",
-       "      <th>ts_id</th>\n",
-       "      <th>loc_web_ds</th>\n",
-       "      <th>medium_grp_cd</th>\n",
-       "      <th>parm_grp_cd</th>\n",
-       "      <th>srs_id</th>\n",
-       "      <th>access_cd</th>\n",
-       "      <th>begin_date</th>\n",
-       "      <th>end_date</th>\n",
-       "      <th>count_nu</th>\n",
-       "      <th>geometry</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>141</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>01096508</td>\n",
-       "      <td>MERRIMACK RIVER AT NASHUA, NH</td>\n",
-       "      <td>ST</td>\n",
-       "      <td>42.763422</td>\n",
-       "      <td>-71.442843</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.01</td>\n",
-       "      <td>...</td>\n",
-       "      <td>309650</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>17164583</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-10-06</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>120</td>\n",
-       "      <td>POINT (-71.44284 42.76342)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>539</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>01209510</td>\n",
-       "      <td>SAUGATUCK RIVER AT ROUTE 1 AT WESTPORT, CT</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>41.140894</td>\n",
-       "      <td>-73.363033</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.10</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>ALL</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-04-05</td>\n",
-       "      <td>2023-01-17</td>\n",
-       "      <td>22</td>\n",
-       "      <td>POINT (-73.36303 41.14089)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>540</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>01209510</td>\n",
-       "      <td>SAUGATUCK RIVER AT ROUTE 1 AT WESTPORT, CT</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>41.140894</td>\n",
-       "      <td>-73.363033</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.10</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>INF</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-04-05</td>\n",
-       "      <td>2023-01-17</td>\n",
-       "      <td>22</td>\n",
-       "      <td>POINT (-73.36303 41.14089)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>541</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>01209510</td>\n",
-       "      <td>SAUGATUCK RIVER AT ROUTE 1 AT WESTPORT, CT</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>41.140894</td>\n",
-       "      <td>-73.363033</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.10</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>PHY</td>\n",
-       "      <td>1645597</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-04-05</td>\n",
-       "      <td>2023-01-17</td>\n",
-       "      <td>22</td>\n",
-       "      <td>POINT (-73.36303 41.14089)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>542</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>01209510</td>\n",
-       "      <td>SAUGATUCK RIVER AT ROUTE 1 AT WESTPORT, CT</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>41.140894</td>\n",
-       "      <td>-73.363033</td>\n",
-       "      <td>5</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.10</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>PHY</td>\n",
-       "      <td>1645720</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-04-05</td>\n",
-       "      <td>2023-01-17</td>\n",
-       "      <td>22</td>\n",
-       "      <td>POINT (-73.36303 41.14089)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6151</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>04294500</td>\n",
-       "      <td>LAKE CHAMPLAIN AT BURLINGTON, VT</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>44.476160</td>\n",
-       "      <td>-73.221517</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.05</td>\n",
-       "      <td>...</td>\n",
-       "      <td>253418</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642503</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-06-01</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>247</td>\n",
-       "      <td>POINT (-73.22152 44.47616)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6553</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>04295000</td>\n",
-       "      <td>RICHELIEU R (LAKE CHAMPLAIN) AT ROUSES POINT NY</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>44.996278</td>\n",
-       "      <td>-73.359806</td>\n",
-       "      <td>1</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>245276</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642503</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-10-06</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>120</td>\n",
-       "      <td>POINT (-73.35981 44.99628)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6594</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>410606073245700</td>\n",
-       "      <td>NORWALK RIVER AT NORWALK AQUARIUM NR S NORWALK...</td>\n",
-       "      <td>ES</td>\n",
-       "      <td>41.101619</td>\n",
-       "      <td>-73.415947</td>\n",
-       "      <td>H</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.60</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>BIO</td>\n",
-       "      <td>86546</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-03-15</td>\n",
-       "      <td>2023-01-03</td>\n",
-       "      <td>20</td>\n",
-       "      <td>POINT (-73.41595 41.10162)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6656</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>420717071221301</td>\n",
-       "      <td>KINGSBURY POND NEAR NORFOLK, MA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>42.121389</td>\n",
-       "      <td>-71.370278</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>...</td>\n",
-       "      <td>320743</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1642503</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2023-01-09</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>25</td>\n",
-       "      <td>POINT (-71.37028 42.12139)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6671</th>\n",
-       "      <td>USGS</td>\n",
-       "      <td>422302071083801</td>\n",
-       "      <td>FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA</td>\n",
-       "      <td>LK</td>\n",
-       "      <td>42.383889</td>\n",
-       "      <td>-71.143889</td>\n",
-       "      <td>S</td>\n",
-       "      <td>NAD83</td>\n",
-       "      <td>27.6</td>\n",
-       "      <td>5.00</td>\n",
-       "      <td>...</td>\n",
-       "      <td>225988</td>\n",
-       "      <td>Huron Ave Gatehouse, [Data provided by CWD]</td>\n",
-       "      <td>wat</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1643311</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2022-10-06</td>\n",
-       "      <td>2023-02-03</td>\n",
-       "      <td>120</td>\n",
-       "      <td>POINT (-71.14389 42.38389)</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>181 rows × 25 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     agency_cd          site_no  \\\n",
-       "141       USGS         01096508   \n",
-       "539       USGS         01209510   \n",
-       "540       USGS         01209510   \n",
-       "541       USGS         01209510   \n",
-       "542       USGS         01209510   \n",
-       "...        ...              ...   \n",
-       "6151      USGS         04294500   \n",
-       "6553      USGS         04295000   \n",
-       "6594      USGS  410606073245700   \n",
-       "6656      USGS  420717071221301   \n",
-       "6671      USGS  422302071083801   \n",
-       "\n",
-       "                                             station_nm site_tp_cd  \\\n",
-       "141                       MERRIMACK RIVER AT NASHUA, NH         ST   \n",
-       "539          SAUGATUCK RIVER AT ROUTE 1 AT WESTPORT, CT         ES   \n",
-       "540          SAUGATUCK RIVER AT ROUTE 1 AT WESTPORT, CT         ES   \n",
-       "541          SAUGATUCK RIVER AT ROUTE 1 AT WESTPORT, CT         ES   \n",
-       "542          SAUGATUCK RIVER AT ROUTE 1 AT WESTPORT, CT         ES   \n",
-       "...                                                 ...        ...   \n",
-       "6151                   LAKE CHAMPLAIN AT BURLINGTON, VT         LK   \n",
-       "6553    RICHELIEU R (LAKE CHAMPLAIN) AT ROUSES POINT NY         LK   \n",
-       "6594  NORWALK RIVER AT NORWALK AQUARIUM NR S NORWALK...         ES   \n",
-       "6656                    KINGSBURY POND NEAR NORFOLK, MA         LK   \n",
-       "6671          FRESH POND IN GATE HOUSE AT CAMBRIDGE, MA         LK   \n",
-       "\n",
-       "      dec_lat_va  dec_long_va coord_acy_cd dec_coord_datum_cd  alt_va  \\\n",
-       "141    42.763422   -71.442843            S              NAD83     0.0   \n",
-       "539    41.140894   -73.363033            5              NAD83     0.0   \n",
-       "540    41.140894   -73.363033            5              NAD83     0.0   \n",
-       "541    41.140894   -73.363033            5              NAD83     0.0   \n",
-       "542    41.140894   -73.363033            5              NAD83     0.0   \n",
-       "...          ...          ...          ...                ...     ...   \n",
-       "6151   44.476160   -73.221517            S              NAD83     0.0   \n",
-       "6553   44.996278   -73.359806            1              NAD83     NaN   \n",
-       "6594   41.101619   -73.415947            H              NAD83     4.0   \n",
-       "6656   42.121389   -71.370278            S              NAD83     NaN   \n",
-       "6671   42.383889   -71.143889            S              NAD83    27.6   \n",
-       "\n",
-       "      alt_acy_va  ...   ts_id                                   loc_web_ds  \\\n",
-       "141         0.01  ...  309650                                          NaN   \n",
-       "539         0.10  ...       0                                          NaN   \n",
-       "540         0.10  ...       0                                          NaN   \n",
-       "541         0.10  ...       0                                          NaN   \n",
-       "542         0.10  ...       0                                          NaN   \n",
-       "...          ...  ...     ...                                          ...   \n",
-       "6151        0.05  ...  253418                                          NaN   \n",
-       "6553         NaN  ...  245276                                          NaN   \n",
-       "6594        1.60  ...       0                                          NaN   \n",
-       "6656         NaN  ...  320743                                          NaN   \n",
-       "6671        5.00  ...  225988  Huron Ave Gatehouse, [Data provided by CWD]   \n",
-       "\n",
-       "     medium_grp_cd parm_grp_cd    srs_id  access_cd begin_date   end_date  \\\n",
-       "141            wat         NaN  17164583          0 2022-10-06 2023-02-03   \n",
-       "539            wat         ALL         0          0 2022-04-05 2023-01-17   \n",
-       "540            wat         INF         0          0 2022-04-05 2023-01-17   \n",
-       "541            wat         PHY   1645597          0 2022-04-05 2023-01-17   \n",
-       "542            wat         PHY   1645720          0 2022-04-05 2023-01-17   \n",
-       "...            ...         ...       ...        ...        ...        ...   \n",
-       "6151           wat         NaN   1642503          0 2022-06-01 2023-02-03   \n",
-       "6553           wat         NaN   1642503          0 2022-10-06 2023-02-03   \n",
-       "6594           wat         BIO     86546          0 2022-03-15 2023-01-03   \n",
-       "6656           wat         NaN   1642503          0 2023-01-09 2023-02-03   \n",
-       "6671           wat         NaN   1643311          0 2022-10-06 2023-02-03   \n",
-       "\n",
-       "     count_nu                    geometry  \n",
-       "141       120  POINT (-71.44284 42.76342)  \n",
-       "539        22  POINT (-73.36303 41.14089)  \n",
-       "540        22  POINT (-73.36303 41.14089)  \n",
-       "541        22  POINT (-73.36303 41.14089)  \n",
-       "542        22  POINT (-73.36303 41.14089)  \n",
-       "...       ...                         ...  \n",
-       "6151      247  POINT (-73.22152 44.47616)  \n",
-       "6553      120  POINT (-73.35981 44.99628)  \n",
-       "6594       20  POINT (-73.41595 41.10162)  \n",
-       "6656       25  POINT (-71.37028 42.12139)  \n",
-       "6671      120  POINT (-71.14389 42.38389)  \n",
-       "\n",
-       "[181 rows x 25 columns]"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "ne_stations[ne_stations.begin_date > \"2022\"]"
    ]
@@ -1381,587 +136,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "0e14b584",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|███████████████████████████████████████████████████████████████████████████████| 4/4 [00:22<00:00,  5.73s/it]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
-       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "</symbol>\n",
-       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
-       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "body[data-theme=dark],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-array-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: '►';\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: '(';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: ')';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-index-preview {\n",
-       "  grid-column: 2 / 5;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data,\n",
-       ".xr-index-data-in:checked ~ .xr-index-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-index-name div,\n",
-       ".xr-index-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:    (site_no: 78, datetime: 1133, code: 7, option: 8)\n",
-       "Coordinates:\n",
-       "  * site_no    (site_no) object &#x27;01063995&#x27; &#x27;01098499&#x27; ... &#x27;422302071083801&#x27;\n",
-       "  * datetime   (datetime) datetime64[ns] 2020-05-27T04:00:00 ... 2020-05-31T0...\n",
-       "  * code       (code) object &#x27;00062&#x27; &#x27;62614&#x27; &#x27;62615&#x27; ... &#x27;62620&#x27; &#x27;63160&#x27; &#x27;72279&#x27;\n",
-       "  * option     (option) object &#x27;&#x27; &#x27;2&#x27; ... &#x27;test&#x27; &#x27;upstream of weir&#x27;\n",
-       "Data variables:\n",
-       "    value      (site_no, datetime, code, option) object nan nan nan ... nan nan\n",
-       "    qualifier  (site_no, datetime, code, option) object nan nan nan ... nan nan\n",
-       "    lon        (site_no) float64 -70.51 -71.38 -71.27 ... -70.06 -70.05 -71.14\n",
-       "    lat        (site_no) float64 43.78 42.32 42.42 42.4 ... 41.93 41.93 42.38\n",
-       "    unit       (code) object &#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27;\n",
-       "    name       (code) object &#x27;Elevation of reservoir water surface above datu...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f0bebe1f-46a6-4d71-916f-c73d857f35ed' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f0bebe1f-46a6-4d71-916f-c73d857f35ed' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>site_no</span>: 78</li><li><span class='xr-has-index'>datetime</span>: 1133</li><li><span class='xr-has-index'>code</span>: 7</li><li><span class='xr-has-index'>option</span>: 8</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8b4f4186-16b5-4d3d-96a5-210383eb71ea' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8b4f4186-16b5-4d3d-96a5-210383eb71ea' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>site_no</span></div><div class='xr-var-dims'>(site_no)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;01063995&#x27; ... &#x27;422302071083801&#x27;</div><input id='attrs-8ed7172c-e93c-4439-b85d-7d569350cc1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ed7172c-e93c-4439-b85d-7d569350cc1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-895ae78f-e6b0-40cc-9581-578e9c661e7e' class='xr-var-data-in' type='checkbox'><label for='data-895ae78f-e6b0-40cc-9581-578e9c661e7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;01063995&#x27;, &#x27;01098499&#x27;, &#x27;01104425&#x27;, &#x27;01104430&#x27;, &#x27;01104480&#x27;, &#x27;01179500&#x27;,\n",
-       "       &#x27;01194815&#x27;, &#x27;01209510&#x27;, &#x27;012112296&#x27;, &#x27;01302250&#x27;, &#x27;01302600&#x27;, &#x27;01302845&#x27;,\n",
-       "       &#x27;01304057&#x27;, &#x27;01304200&#x27;, &#x27;01304250&#x27;, &#x27;01304562&#x27;, &#x27;01304705&#x27;, &#x27;01304746&#x27;,\n",
-       "       &#x27;01304920&#x27;, &#x27;01305575&#x27;, &#x27;01306402&#x27;, &#x27;01309225&#x27;, &#x27;01310521&#x27;, &#x27;01310740&#x27;,\n",
-       "       &#x27;01311143&#x27;, &#x27;01311145&#x27;, &#x27;01311850&#x27;, &#x27;01311875&#x27;, &#x27;01314500&#x27;, &#x27;01323500&#x27;,\n",
-       "       &#x27;01330884&#x27;, &#x27;01350100&#x27;, &#x27;01359139&#x27;, &#x27;01359165&#x27;, &#x27;01372043&#x27;, &#x27;01376562&#x27;,\n",
-       "       &#x27;01376950&#x27;, &#x27;01377450&#x27;, &#x27;01378480&#x27;, &#x27;01378570&#x27;, &#x27;01380900&#x27;, &#x27;01383000&#x27;,\n",
-       "       &#x27;01386990&#x27;, &#x27;01392650&#x27;, &#x27;01396060&#x27;, &#x27;01396790&#x27;, &#x27;01407081&#x27;, &#x27;01407498&#x27;,\n",
-       "       &#x27;01407600&#x27;, &#x27;01407770&#x27;, &#x27;01408048&#x27;, &#x27;01408168&#x27;, &#x27;01414750&#x27;, &#x27;01435900&#x27;,\n",
-       "       &#x27;01460378&#x27;, &#x27;01460380&#x27;, &#x27;01460415&#x27;, &#x27;01460440&#x27;, &#x27;01460500&#x27;, &#x27;01460595&#x27;,\n",
-       "       &#x27;01464040&#x27;, &#x27;01467024&#x27;, &#x27;04253300&#x27;, &#x27;04253400&#x27;, &#x27;04278000&#x27;, &#x27;04279085&#x27;,\n",
-       "       &#x27;04283500&#x27;, &#x27;04285000&#x27;, &#x27;04285800&#x27;, &#x27;04288040&#x27;, &#x27;04288500&#x27;, &#x27;04294413&#x27;,\n",
-       "       &#x27;04295500&#x27;, &#x27;413758070320501&#x27;, &#x27;415556070031901&#x27;, &#x27;415560070032501&#x27;,\n",
-       "       &#x27;415601070030701&#x27;, &#x27;422302071083801&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>datetime</span></div><div class='xr-var-dims'>(datetime)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-05-27T04:00:00 ... 2020-05-...</div><input id='attrs-19eb8398-df54-4025-91a2-4d21b9f2f167' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-19eb8398-df54-4025-91a2-4d21b9f2f167' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8dbed358-c576-4a58-a274-0a2488695d7b' class='xr-var-data-in' type='checkbox'><label for='data-8dbed358-c576-4a58-a274-0a2488695d7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-05-27T04:00:00.000000000&#x27;, &#x27;2020-05-27T04:06:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-27T04:12:00.000000000&#x27;, ..., &#x27;2020-05-31T04:06:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-31T04:15:00.000000000&#x27;, &#x27;2020-05-31T04:30:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>code</span></div><div class='xr-var-dims'>(code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;00062&#x27; &#x27;62614&#x27; ... &#x27;63160&#x27; &#x27;72279&#x27;</div><input id='attrs-9d5e0e96-afa1-4cf5-b750-13ecc90b0795' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9d5e0e96-afa1-4cf5-b750-13ecc90b0795' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f74536ba-0427-4b30-8e1c-b07a4ec09a37' class='xr-var-data-in' type='checkbox'><label for='data-f74536ba-0427-4b30-8e1c-b07a4ec09a37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;00062&#x27;, &#x27;62614&#x27;, &#x27;62615&#x27;, &#x27;62619&#x27;, &#x27;62620&#x27;, &#x27;63160&#x27;, &#x27;72279&#x27;],\n",
-       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>option</span></div><div class='xr-var-dims'>(option)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;&#x27; &#x27;2&#x27; ... &#x27;upstream of weir&#x27;</div><input id='attrs-f0b74b66-692f-461d-bcf2-2dd716f7f6c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f0b74b66-692f-461d-bcf2-2dd716f7f6c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd851a11-cfae-48ed-ae94-43fcb2e37316' class='xr-var-data-in' type='checkbox'><label for='data-bd851a11-cfae-48ed-ae94-43fcb2e37316' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;&#x27;, &#x27;2&#x27;, &#x27;downstream of weir&#x27;, &#x27;gate house&#x27;, &#x27;navd88&#x27;, &#x27;ngvd29&#x27;, &#x27;test&#x27;,\n",
-       "       &#x27;upstream of weir&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-03ce1312-10b7-4cb5-a7f9-90084e78af72' class='xr-section-summary-in' type='checkbox'  checked><label for='section-03ce1312-10b7-4cb5-a7f9-90084e78af72' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>value</span></div><div class='xr-var-dims'>(site_no, datetime, code, option)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-605cc933-0498-4d19-a93c-79541c475abf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-605cc933-0498-4d19-a93c-79541c475abf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37e349c9-5a0c-458c-a8a8-d0b193165fc4' class='xr-var-data-in' type='checkbox'><label for='data-37e349c9-5a0c-458c-a8a8-d0b193165fc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [265.9, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
-       "\n",
-       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
-       "\n",
-       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "...\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
-       "\n",
-       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
-       "\n",
-       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]]]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qualifier</span></div><div class='xr-var-dims'>(site_no, datetime, code, option)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-112d27d7-ad8a-4e84-88de-df0ca7911b60' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-112d27d7-ad8a-4e84-88de-df0ca7911b60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1cdd549-3d08-4ad2-8013-f1dad5eac533' class='xr-var-data-in' type='checkbox'><label for='data-f1cdd549-3d08-4ad2-8013-f1dad5eac533' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [&#x27;A&#x27;, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
-       "\n",
-       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
-       "\n",
-       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "...\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
-       "\n",
-       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]],\n",
-       "\n",
-       "        [[nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         ...,\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan],\n",
-       "         [nan, nan, nan, ..., nan, nan, nan]]]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(site_no)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-70.51 -71.38 ... -70.05 -71.14</div><input id='attrs-2f3a2415-696a-4aea-9c01-f2bf7211e6f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2f3a2415-696a-4aea-9c01-f2bf7211e6f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3aa07c5a-2d97-4e3c-9fe9-1fe13c8a3ee3' class='xr-var-data-in' type='checkbox'><label for='data-3aa07c5a-2d97-4e3c-9fe9-1fe13c8a3ee3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-70.5061111 , -71.3838083 , -71.2711111 , -71.2733903 ,\n",
-       "       -71.2650565 , -72.8642636 , -72.34927778, -73.3630333 ,\n",
-       "       -73.6250806 , -73.7101944 , -73.638     , -73.5931944 ,\n",
-       "       -73.1431667 , -72.30675   , -72.55477778, -72.6386667 ,\n",
-       "       -72.2244444 , -72.50327778, -72.75086389, -72.9896944 ,\n",
-       "       -73.09125   , -73.3556765 , -73.5754058 , -73.5837396 ,\n",
-       "       -73.6561111 , -73.7373543 , -73.7579103 , -73.885136  ,\n",
-       "       -74.2759825 , -73.92706958, -73.72113889, -74.4445923 ,\n",
-       "       -73.7475    , -73.7589167 , -73.94069299, -74.12988889,\n",
-       "       -74.0011111 , -74.0491667 , -74.0294444 , -74.04      ,\n",
-       "       -74.39777778, -74.3333333 , -74.29527778, -74.1228611 ,\n",
-       "       -74.2622222 , -74.9236111 , -74.1475    , -74.115     ,\n",
-       "       -73.9747222 , -74.0261111 , -74.0447222 , -74.0544444 ,\n",
-       "       -74.8196667 , -74.6389167 , -74.8666667 , -74.8669444 ,\n",
-       "       -74.7775    , -74.685     , -74.6183333 , -74.4641667 ,\n",
-       "       -74.7558333 , -74.9316667 , -74.78263889, -74.9693611 ,\n",
-       "       -73.45788889, -73.41838889, -72.4445467 , -72.5748324 ,\n",
-       "       -72.5759425 , -72.7461806 , -72.76984118, -73.4535    ,\n",
-       "       -72.2062133 , -70.53475079, -70.0553056 , -70.05688889,\n",
-       "       -70.051975  , -71.14388889])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(site_no)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>43.78 42.32 42.42 ... 41.93 42.38</div><input id='attrs-25b0c17a-67b2-4f81-bfc4-bdf822200091' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-25b0c17a-67b2-4f81-bfc4-bdf822200091' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f0ad481-f35f-4a56-a84c-6d2a0c55ebc8' class='xr-var-data-in' type='checkbox'><label for='data-6f0ad481-f35f-4a56-a84c-6d2a0c55ebc8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([43.77777778, 42.31514167, 42.42166667, 42.3981512 , 42.3556519 ,\n",
-       "       42.28786655, 41.2813333 , 41.14089444, 41.0141222 , 40.8662222 ,\n",
-       "       40.88855556, 40.9051111 , 40.9628611 , 41.13663889, 40.97969444,\n",
-       "       40.91777778, 40.93319444, 40.85055556, 40.7881111 , 40.69138889,\n",
-       "       40.72105556, 40.66926687, 40.6276026 , 40.5934366 , 40.6088333 ,\n",
-       "       40.59316026, 40.6173266 , 40.57371636, 43.75562018, 43.3159042 ,\n",
-       "       43.0539722 , 42.3559156 , 42.64788889, 42.61952778, 41.72176015,\n",
-       "       40.53888889, 41.0183333 , 41.01277778, 40.95638889, 40.87916667,\n",
-       "       40.89527778, 41.16166667, 41.045     , 40.71127778, 40.50388889,\n",
-       "       40.6436111 , 40.44916667, 40.31916667, 40.36555556, 40.18555556,\n",
-       "       40.11166667, 40.04055556, 42.08752778, 41.82788889, 40.29638889,\n",
-       "       40.29666667, 40.225     , 40.30444444, 40.3736111 , 40.50777778,\n",
-       "       40.18916667, 40.02916667, 43.74519444, 43.71266667, 43.80813889,\n",
-       "       43.62188889, 44.15506226, 44.3106136 , 44.2608926 , 44.3284361 ,\n",
-       "       44.381722  , 44.05275   , 44.93782448, 41.63427505, 41.9323583 ,\n",
-       "       41.93323889, 41.93365278, 42.38388889])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>unit</span></div><div class='xr-var-dims'>(code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27; &#x27;ft&#x27;</div><input id='attrs-4adcc963-a978-468b-88c4-e547d54cba4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4adcc963-a978-468b-88c4-e547d54cba4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da459139-d6d1-4726-8f2a-3319544285b7' class='xr-var-data-in' type='checkbox'><label for='data-da459139-d6d1-4726-8f2a-3319544285b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;ft&#x27;, &#x27;ft&#x27;, &#x27;ft&#x27;, &#x27;ft&#x27;, &#x27;ft&#x27;, &#x27;ft&#x27;, &#x27;ft&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>name</span></div><div class='xr-var-dims'>(code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Elevation of reservoir water su...</div><input id='attrs-b9a5f494-b6b9-4fd2-a975-dde38b83f79e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b9a5f494-b6b9-4fd2-a975-dde38b83f79e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76187df2-54e9-46a4-88f3-859660c50034' class='xr-var-data-in' type='checkbox'><label for='data-76187df2-54e9-46a4-88f3-859660c50034' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Elevation of reservoir water surface above datum, feet&#x27;,\n",
-       "       &#x27;Lake or reservoir water surface elevation above NGVD 1929, feet&#x27;,\n",
-       "       &#x27;Lake or reservoir water surface elevation above NAVD 1988, feet&#x27;,\n",
-       "       &#x27;Estuary or ocean water surface elevation above NGVD 1929, feet&#x27;,\n",
-       "       &#x27;Estuary or ocean water surface elevation above NAVD 1988, feet&#x27;,\n",
-       "       &#x27;Stream water level elevation above NAVD 1988, in feet&#x27;,\n",
-       "       &#x27;Tidal elevation, NOS-averaged, NAVD88, feet&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b8aa1e10-2759-4894-aa96-cb768af8ff75' class='xr-section-summary-in' type='checkbox'  ><label for='section-b8aa1e10-2759-4894-aa96-cb768af8ff75' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>site_no</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4db58db1-5577-4887-a57e-fec7284c3731' class='xr-index-data-in' type='checkbox'/><label for='index-4db58db1-5577-4887-a57e-fec7284c3731' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;01063995&#x27;, &#x27;01098499&#x27;, &#x27;01104425&#x27;, &#x27;01104430&#x27;, &#x27;01104480&#x27;, &#x27;01179500&#x27;,\n",
-       "       &#x27;01194815&#x27;, &#x27;01209510&#x27;, &#x27;012112296&#x27;, &#x27;01302250&#x27;, &#x27;01302600&#x27;, &#x27;01302845&#x27;,\n",
-       "       &#x27;01304057&#x27;, &#x27;01304200&#x27;, &#x27;01304250&#x27;, &#x27;01304562&#x27;, &#x27;01304705&#x27;, &#x27;01304746&#x27;,\n",
-       "       &#x27;01304920&#x27;, &#x27;01305575&#x27;, &#x27;01306402&#x27;, &#x27;01309225&#x27;, &#x27;01310521&#x27;, &#x27;01310740&#x27;,\n",
-       "       &#x27;01311143&#x27;, &#x27;01311145&#x27;, &#x27;01311850&#x27;, &#x27;01311875&#x27;, &#x27;01314500&#x27;, &#x27;01323500&#x27;,\n",
-       "       &#x27;01330884&#x27;, &#x27;01350100&#x27;, &#x27;01359139&#x27;, &#x27;01359165&#x27;, &#x27;01372043&#x27;, &#x27;01376562&#x27;,\n",
-       "       &#x27;01376950&#x27;, &#x27;01377450&#x27;, &#x27;01378480&#x27;, &#x27;01378570&#x27;, &#x27;01380900&#x27;, &#x27;01383000&#x27;,\n",
-       "       &#x27;01386990&#x27;, &#x27;01392650&#x27;, &#x27;01396060&#x27;, &#x27;01396790&#x27;, &#x27;01407081&#x27;, &#x27;01407498&#x27;,\n",
-       "       &#x27;01407600&#x27;, &#x27;01407770&#x27;, &#x27;01408048&#x27;, &#x27;01408168&#x27;, &#x27;01414750&#x27;, &#x27;01435900&#x27;,\n",
-       "       &#x27;01460378&#x27;, &#x27;01460380&#x27;, &#x27;01460415&#x27;, &#x27;01460440&#x27;, &#x27;01460500&#x27;, &#x27;01460595&#x27;,\n",
-       "       &#x27;01464040&#x27;, &#x27;01467024&#x27;, &#x27;04253300&#x27;, &#x27;04253400&#x27;, &#x27;04278000&#x27;, &#x27;04279085&#x27;,\n",
-       "       &#x27;04283500&#x27;, &#x27;04285000&#x27;, &#x27;04285800&#x27;, &#x27;04288040&#x27;, &#x27;04288500&#x27;, &#x27;04294413&#x27;,\n",
-       "       &#x27;04295500&#x27;, &#x27;413758070320501&#x27;, &#x27;415556070031901&#x27;, &#x27;415560070032501&#x27;,\n",
-       "       &#x27;415601070030701&#x27;, &#x27;422302071083801&#x27;],\n",
-       "      dtype=&#x27;object&#x27;, name=&#x27;site_no&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>datetime</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-59ceb319-1772-4aa1-80a1-43c491a7c13f' class='xr-index-data-in' type='checkbox'/><label for='index-59ceb319-1772-4aa1-80a1-43c491a7c13f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-05-27 04:00:00&#x27;, &#x27;2020-05-27 04:06:00&#x27;,\n",
-       "               &#x27;2020-05-27 04:12:00&#x27;, &#x27;2020-05-27 04:15:00&#x27;,\n",
-       "               &#x27;2020-05-27 04:18:00&#x27;, &#x27;2020-05-27 04:24:00&#x27;,\n",
-       "               &#x27;2020-05-27 04:30:00&#x27;, &#x27;2020-05-27 04:36:00&#x27;,\n",
-       "               &#x27;2020-05-27 04:42:00&#x27;, &#x27;2020-05-27 04:45:00&#x27;,\n",
-       "               ...\n",
-       "               &#x27;2020-05-31 03:30:00&#x27;, &#x27;2020-05-31 03:36:00&#x27;,\n",
-       "               &#x27;2020-05-31 03:42:00&#x27;, &#x27;2020-05-31 03:45:00&#x27;,\n",
-       "               &#x27;2020-05-31 03:48:00&#x27;, &#x27;2020-05-31 03:54:00&#x27;,\n",
-       "               &#x27;2020-05-31 04:00:00&#x27;, &#x27;2020-05-31 04:06:00&#x27;,\n",
-       "               &#x27;2020-05-31 04:15:00&#x27;, &#x27;2020-05-31 04:30:00&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;datetime&#x27;, length=1133, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>code</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-20b50fcb-2e12-4153-95e7-f3a3d8a551d4' class='xr-index-data-in' type='checkbox'/><label for='index-20b50fcb-2e12-4153-95e7-f3a3d8a551d4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;00062&#x27;, &#x27;62614&#x27;, &#x27;62615&#x27;, &#x27;62619&#x27;, &#x27;62620&#x27;, &#x27;63160&#x27;, &#x27;72279&#x27;], dtype=&#x27;object&#x27;, name=&#x27;code&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>option</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5329a633-ec0b-4cf0-b900-27e2b5593619' class='xr-index-data-in' type='checkbox'/><label for='index-5329a633-ec0b-4cf0-b900-27e2b5593619' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;&#x27;, &#x27;2&#x27;, &#x27;downstream of weir&#x27;, &#x27;gate house&#x27;, &#x27;navd88&#x27;, &#x27;ngvd29&#x27;, &#x27;test&#x27;,\n",
-       "       &#x27;upstream of weir&#x27;],\n",
-       "      dtype=&#x27;object&#x27;, name=&#x27;option&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-89a6722e-ec57-4766-a0cd-13d430562a71' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-89a6722e-ec57-4766-a0cd-13d430562a71' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:    (site_no: 78, datetime: 1133, code: 7, option: 8)\n",
-       "Coordinates:\n",
-       "  * site_no    (site_no) object '01063995' '01098499' ... '422302071083801'\n",
-       "  * datetime   (datetime) datetime64[ns] 2020-05-27T04:00:00 ... 2020-05-31T0...\n",
-       "  * code       (code) object '00062' '62614' '62615' ... '62620' '63160' '72279'\n",
-       "  * option     (option) object '' '2' ... 'test' 'upstream of weir'\n",
-       "Data variables:\n",
-       "    value      (site_no, datetime, code, option) object nan nan nan ... nan nan\n",
-       "    qualifier  (site_no, datetime, code, option) object nan nan nan ... nan nan\n",
-       "    lon        (site_no) float64 -70.51 -71.38 -71.27 ... -70.06 -70.05 -71.14\n",
-       "    lat        (site_no) float64 43.78 42.32 42.42 42.4 ... 41.93 41.93 42.38\n",
-       "    unit       (code) object 'ft' 'ft' 'ft' 'ft' 'ft' 'ft' 'ft'\n",
-       "    name       (code) object 'Elevation of reservoir water surface above datu..."
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "ne_data = usgs.get_usgs_data(\n",
     "    usgs_metadata=ne_stations,\n",
@@ -1973,522 +153,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "10b199e4-1980-4319-8bda-b12f3124ab36",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
-       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "</symbol>\n",
-       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
-       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "body[data-theme=dark],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-array-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: '►';\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: '(';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: ')';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-index-preview {\n",
-       "  grid-column: 2 / 5;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data,\n",
-       ".xr-index-data-in:checked ~ .xr-index-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-index-name div,\n",
-       ".xr-index-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:    (site_no: 20, datetime: 806, code: 1)\n",
-       "Coordinates:\n",
-       "  * site_no    (site_no) object &#x27;01302250&#x27; &#x27;01302600&#x27; ... &#x27;01372043&#x27; &#x27;01376562&#x27;\n",
-       "  * datetime   (datetime) datetime64[ns] 2020-05-27T05:00:00 ... 2020-05-31T0...\n",
-       "  * code       (code) object &#x27;62620&#x27;\n",
-       "Data variables:\n",
-       "    option     &lt;U6 &#x27;navd88&#x27;\n",
-       "    value      (site_no, datetime, code) object 2.35 2.36 2.38 ... nan 0.66 nan\n",
-       "    qualifier  (site_no, datetime, code) object &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; ... nan &#x27;A&#x27; nan\n",
-       "    lon        (site_no) float64 -73.71 -73.64 -73.59 ... -73.76 -73.94 -74.13\n",
-       "    lat        (site_no) float64 40.87 40.89 40.91 40.96 ... 42.62 41.72 40.54\n",
-       "    unit       (code) object &#x27;ft&#x27;\n",
-       "    name       (code) object &#x27;Estuary or ocean water surface elevation above ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-866f3426-105f-40e1-9326-9440b34ce779' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-866f3426-105f-40e1-9326-9440b34ce779' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>site_no</span>: 20</li><li><span class='xr-has-index'>datetime</span>: 806</li><li><span class='xr-has-index'>code</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9e8f2396-1672-4377-a309-b6249a8916a6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9e8f2396-1672-4377-a309-b6249a8916a6' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>site_no</span></div><div class='xr-var-dims'>(site_no)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;01302250&#x27; ... &#x27;01376562&#x27;</div><input id='attrs-6b477903-8de8-451b-b5a6-2f6baa3a0bf4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b477903-8de8-451b-b5a6-2f6baa3a0bf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d327c3dd-5306-4ee9-bef7-fd393a3b97f7' class='xr-var-data-in' type='checkbox'><label for='data-d327c3dd-5306-4ee9-bef7-fd393a3b97f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;01302250&#x27;, &#x27;01302600&#x27;, &#x27;01302845&#x27;, &#x27;01304057&#x27;, &#x27;01304200&#x27;, &#x27;01304562&#x27;,\n",
-       "       &#x27;01304746&#x27;, &#x27;01304920&#x27;, &#x27;01305575&#x27;, &#x27;01306402&#x27;, &#x27;01309225&#x27;, &#x27;01310521&#x27;,\n",
-       "       &#x27;01310740&#x27;, &#x27;01311143&#x27;, &#x27;01311145&#x27;, &#x27;01311850&#x27;, &#x27;01311875&#x27;, &#x27;01359165&#x27;,\n",
-       "       &#x27;01372043&#x27;, &#x27;01376562&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>datetime</span></div><div class='xr-var-dims'>(datetime)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-05-27T05:00:00 ... 2020-05-...</div><input id='attrs-b0ed47b6-4ac7-4dae-ad4b-23c6b38d6030' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b0ed47b6-4ac7-4dae-ad4b-23c6b38d6030' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7132ebc7-30a8-4ed5-a487-becf16ec944e' class='xr-var-data-in' type='checkbox'><label for='data-7132ebc7-30a8-4ed5-a487-becf16ec944e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-05-27T05:00:00.000000000&#x27;, &#x27;2020-05-27T05:06:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-27T05:12:00.000000000&#x27;, ..., &#x27;2020-05-31T03:54:00.000000000&#x27;,\n",
-       "       &#x27;2020-05-31T04:00:00.000000000&#x27;, &#x27;2020-05-31T04:30:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>code</span></div><div class='xr-var-dims'>(code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;62620&#x27;</div><input id='attrs-ad5fc598-9154-4352-9e0e-e54b786fc9b1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ad5fc598-9154-4352-9e0e-e54b786fc9b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b188020-c9a5-45b5-b08a-09ff1e2665af' class='xr-var-data-in' type='checkbox'><label for='data-2b188020-c9a5-45b5-b08a-09ff1e2665af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;62620&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-90ddfb8a-ea01-4659-a3c4-81f39cf82ddc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-90ddfb8a-ea01-4659-a3c4-81f39cf82ddc' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>option</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;navd88&#x27;</div><input id='attrs-d171b7fc-22fb-4ed2-bc31-1897f0b1d7d4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d171b7fc-22fb-4ed2-bc31-1897f0b1d7d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e42bcd1-43ed-4b9d-b45b-35e7f5ced581' class='xr-var-data-in' type='checkbox'><label for='data-0e42bcd1-43ed-4b9d-b45b-35e7f5ced581' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;navd88&#x27;, dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>value</span></div><div class='xr-var-dims'>(site_no, datetime, code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2.35 2.36 2.38 ... nan 0.66 nan</div><input id='attrs-893f6618-89dc-4a00-8cf4-94750af9989c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-893f6618-89dc-4a00-8cf4-94750af9989c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4f10557-26b7-433e-a11a-9542b74d74c3' class='xr-var-data-in' type='checkbox'><label for='data-e4f10557-26b7-433e-a11a-9542b74d74c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[2.35],\n",
-       "        [2.36],\n",
-       "        [2.38],\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        [nan]],\n",
-       "\n",
-       "       [[1.94],\n",
-       "        [2.19],\n",
-       "        [nan],\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        [nan]],\n",
-       "\n",
-       "       [[1.0],\n",
-       "        [1.17],\n",
-       "        [nan],\n",
-       "        ...,\n",
-       "...\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        [3.1]],\n",
-       "\n",
-       "       [[nan],\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        [nan]],\n",
-       "\n",
-       "       [[2.25],\n",
-       "        [2.16],\n",
-       "        [2.04],\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [0.66],\n",
-       "        [nan]]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qualifier</span></div><div class='xr-var-dims'>(site_no, datetime, code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; ... nan nan &#x27;A&#x27; nan</div><input id='attrs-188c1804-32ff-4aca-adcf-3025e1eb95d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-188c1804-32ff-4aca-adcf-3025e1eb95d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-421e22ee-f9aa-4a58-b387-1a4e72d1ab06' class='xr-var-data-in' type='checkbox'><label for='data-421e22ee-f9aa-4a58-b387-1a4e72d1ab06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[&#x27;A&#x27;],\n",
-       "        [&#x27;A&#x27;],\n",
-       "        [&#x27;A&#x27;],\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        [nan]],\n",
-       "\n",
-       "       [[&#x27;A&#x27;],\n",
-       "        [&#x27;A&#x27;],\n",
-       "        [nan],\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        [nan]],\n",
-       "\n",
-       "       [[&#x27;A&#x27;],\n",
-       "        [&#x27;A&#x27;],\n",
-       "        [nan],\n",
-       "        ...,\n",
-       "...\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        [&#x27;A&#x27;]],\n",
-       "\n",
-       "       [[nan],\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [nan],\n",
-       "        [nan]],\n",
-       "\n",
-       "       [[&#x27;A&#x27;],\n",
-       "        [&#x27;A&#x27;],\n",
-       "        [&#x27;A&#x27;],\n",
-       "        ...,\n",
-       "        [nan],\n",
-       "        [&#x27;A&#x27;],\n",
-       "        [nan]]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(site_no)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-73.71 -73.64 ... -73.94 -74.13</div><input id='attrs-4ba86581-070a-49d8-b385-ca9d4d375cb3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ba86581-070a-49d8-b385-ca9d4d375cb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c363ba15-e186-4925-b216-8ca2a194dd34' class='xr-var-data-in' type='checkbox'><label for='data-c363ba15-e186-4925-b216-8ca2a194dd34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-73.7101944 , -73.638     , -73.5931944 , -73.1431667 ,\n",
-       "       -72.30675   , -72.6386667 , -72.50327778, -72.75086389,\n",
-       "       -72.9896944 , -73.09125   , -73.3556765 , -73.5754058 ,\n",
-       "       -73.5837396 , -73.6561111 , -73.7373543 , -73.7579103 ,\n",
-       "       -73.885136  , -73.7589167 , -73.94069299, -74.12988889])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(site_no)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.87 40.89 40.91 ... 41.72 40.54</div><input id='attrs-2271191e-9e16-4bc1-b5f9-2e6f2f187936' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2271191e-9e16-4bc1-b5f9-2e6f2f187936' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b67e62cf-8df3-4374-adf5-7a876d673da8' class='xr-var-data-in' type='checkbox'><label for='data-b67e62cf-8df3-4374-adf5-7a876d673da8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([40.8662222 , 40.88855556, 40.9051111 , 40.9628611 , 41.13663889,\n",
-       "       40.91777778, 40.85055556, 40.7881111 , 40.69138889, 40.72105556,\n",
-       "       40.66926687, 40.6276026 , 40.5934366 , 40.6088333 , 40.59316026,\n",
-       "       40.6173266 , 40.57371636, 42.61952778, 41.72176015, 40.53888889])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>unit</span></div><div class='xr-var-dims'>(code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;ft&#x27;</div><input id='attrs-86919491-ae0d-47b3-b768-90ec08011a40' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86919491-ae0d-47b3-b768-90ec08011a40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-148b1fd6-5108-4627-8d54-ed095dc487d1' class='xr-var-data-in' type='checkbox'><label for='data-148b1fd6-5108-4627-8d54-ed095dc487d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;ft&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>name</span></div><div class='xr-var-dims'>(code)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;Estuary or ocean water surface ...</div><input id='attrs-67c40f12-7eed-47f5-93c1-e4d3ad59cb20' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67c40f12-7eed-47f5-93c1-e4d3ad59cb20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8b812c3-e89d-4684-99f9-fffcdc00ce05' class='xr-var-data-in' type='checkbox'><label for='data-d8b812c3-e89d-4684-99f9-fffcdc00ce05' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Estuary or ocean water surface elevation above NAVD 1988, feet&#x27;],\n",
-       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-28212ef7-8bd0-435b-9153-4bdff24c9f9b' class='xr-section-summary-in' type='checkbox'  ><label for='section-28212ef7-8bd0-435b-9153-4bdff24c9f9b' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>site_no</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bdd18ffa-9543-42d2-b265-08784e05af87' class='xr-index-data-in' type='checkbox'/><label for='index-bdd18ffa-9543-42d2-b265-08784e05af87' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;01302250&#x27;, &#x27;01302600&#x27;, &#x27;01302845&#x27;, &#x27;01304057&#x27;, &#x27;01304200&#x27;, &#x27;01304562&#x27;,\n",
-       "       &#x27;01304746&#x27;, &#x27;01304920&#x27;, &#x27;01305575&#x27;, &#x27;01306402&#x27;, &#x27;01309225&#x27;, &#x27;01310521&#x27;,\n",
-       "       &#x27;01310740&#x27;, &#x27;01311143&#x27;, &#x27;01311145&#x27;, &#x27;01311850&#x27;, &#x27;01311875&#x27;, &#x27;01359165&#x27;,\n",
-       "       &#x27;01372043&#x27;, &#x27;01376562&#x27;],\n",
-       "      dtype=&#x27;object&#x27;, name=&#x27;site_no&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>datetime</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4a8c3953-ad59-456e-b081-c278d6258951' class='xr-index-data-in' type='checkbox'/><label for='index-4a8c3953-ad59-456e-b081-c278d6258951' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-05-27 05:00:00&#x27;, &#x27;2020-05-27 05:06:00&#x27;,\n",
-       "               &#x27;2020-05-27 05:12:00&#x27;, &#x27;2020-05-27 05:18:00&#x27;,\n",
-       "               &#x27;2020-05-27 05:24:00&#x27;, &#x27;2020-05-27 05:30:00&#x27;,\n",
-       "               &#x27;2020-05-27 05:36:00&#x27;, &#x27;2020-05-27 05:42:00&#x27;,\n",
-       "               &#x27;2020-05-27 05:48:00&#x27;, &#x27;2020-05-27 05:54:00&#x27;,\n",
-       "               ...\n",
-       "               &#x27;2020-05-31 03:15:00&#x27;, &#x27;2020-05-31 03:18:00&#x27;,\n",
-       "               &#x27;2020-05-31 03:30:00&#x27;, &#x27;2020-05-31 03:36:00&#x27;,\n",
-       "               &#x27;2020-05-31 03:42:00&#x27;, &#x27;2020-05-31 03:45:00&#x27;,\n",
-       "               &#x27;2020-05-31 03:48:00&#x27;, &#x27;2020-05-31 03:54:00&#x27;,\n",
-       "               &#x27;2020-05-31 04:00:00&#x27;, &#x27;2020-05-31 04:30:00&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;datetime&#x27;, length=806, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>code</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f5a2f0f3-ab5b-4b1e-8815-f31fbaa81112' class='xr-index-data-in' type='checkbox'/><label for='index-f5a2f0f3-ab5b-4b1e-8815-f31fbaa81112' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;62620&#x27;], dtype=&#x27;object&#x27;, name=&#x27;code&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2df353f4-f7ad-4fde-9715-361658ff1991' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2df353f4-f7ad-4fde-9715-361658ff1991' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:    (site_no: 20, datetime: 806, code: 1)\n",
-       "Coordinates:\n",
-       "  * site_no    (site_no) object '01302250' '01302600' ... '01372043' '01376562'\n",
-       "  * datetime   (datetime) datetime64[ns] 2020-05-27T05:00:00 ... 2020-05-31T0...\n",
-       "  * code       (code) object '62620'\n",
-       "Data variables:\n",
-       "    option     <U6 'navd88'\n",
-       "    value      (site_no, datetime, code) object 2.35 2.36 2.38 ... nan 0.66 nan\n",
-       "    qualifier  (site_no, datetime, code) object 'A' 'A' 'A' 'A' ... nan 'A' nan\n",
-       "    lon        (site_no) float64 -73.71 -73.64 -73.59 ... -73.76 -73.94 -74.13\n",
-       "    lat        (site_no) float64 40.87 40.89 40.91 40.96 ... 42.62 41.72 40.54\n",
-       "    unit       (code) object 'ft'\n",
-       "    name       (code) object 'Estuary or ocean water surface elevation above ..."
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "def drop_all_nan_coords(ds: xr.Dataset) -> xr.Dataset:\n",
     "    for coord in ds.coords:\n",
@@ -2507,23 +175,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "0a6b56d0",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, axes = plt.subplots(1, 1)\n",
     "\n",
@@ -2540,9 +197,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "searvey",
    "language": "python",
-   "name": "python3"
+   "name": "searvey"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2554,7 +211,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.15"
+   "version": "3.9.16"
   }
  },
  "nbformat": 4,
diff --git a/examples/coops_data.ipynb b/examples/coops_data.ipynb
index b7a3603..3c17978 100644
--- a/examples/coops_data.ipynb
+++ b/examples/coops_data.ipynb
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -49,207 +49,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>nws_id</th>\n",
-       "      <th>name</th>\n",
-       "      <th>state</th>\n",
-       "      <th>status</th>\n",
-       "      <th>removed</th>\n",
-       "      <th>geometry</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>nos_id</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1600012</th>\n",
-       "      <td>46125</td>\n",
-       "      <td>QREB buoy</td>\n",
-       "      <td></td>\n",
-       "      <td>active</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>POINT (122.60028 37.75008)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1619910</th>\n",
-       "      <td>SNDP5</td>\n",
-       "      <td>Sand Island, Midway Islands</td>\n",
-       "      <td></td>\n",
-       "      <td>active</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>POINT (-177.36003 28.21170)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1630000</th>\n",
-       "      <td>APRP7</td>\n",
-       "      <td>Apra Harbor, Guam</td>\n",
-       "      <td></td>\n",
-       "      <td>active</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>POINT (144.65636 13.44339)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1631428</th>\n",
-       "      <td>PGBP7</td>\n",
-       "      <td>Pago Bay, Guam</td>\n",
-       "      <td></td>\n",
-       "      <td>active</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>POINT (144.79700 13.42830)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1770000</th>\n",
-       "      <td>NSTP6</td>\n",
-       "      <td>Pago Pago, American Samoa</td>\n",
-       "      <td></td>\n",
-       "      <td>active</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>POINT (-170.68944 -14.27667)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9087079</th>\n",
-       "      <td>GBWW3</td>\n",
-       "      <td>Green Bay</td>\n",
-       "      <td>WI</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2020-10-28 13:00:00,2007-08-06 23:59:00,2007-0...</td>\n",
-       "      <td>POINT (-88.00722 44.54111)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8770570</th>\n",
-       "      <td>SBPT2</td>\n",
-       "      <td>Sabine Pass North</td>\n",
-       "      <td>TX</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2021-01-18 00:00:00,2020-09-30 15:45:00,2020-0...</td>\n",
-       "      <td>POINT (-93.87010 29.72840)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8775870</th>\n",
-       "      <td>MQTT2</td>\n",
-       "      <td>Bob Hall Pier, Corpus Christi</td>\n",
-       "      <td>TX</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2021-12-22 20:00:00,2020-05-18 13:10:00,2019-0...</td>\n",
-       "      <td>POINT (-97.21670 27.58000)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8740166</th>\n",
-       "      <td>GBRM6</td>\n",
-       "      <td>Grand Bay NERR, Mississippi Sound</td>\n",
-       "      <td>MS</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2022-04-07 00:00:00,2022-03-30 23:58:00,2015-1...</td>\n",
-       "      <td>POINT (-88.40289 30.41319)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8662245</th>\n",
-       "      <td>NITS1</td>\n",
-       "      <td>Oyster Landing (N Inlet Estuary)</td>\n",
-       "      <td>SC</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2022-06-07 23:59:00,2022-06-07 00:00:00,2022-0...</td>\n",
-       "      <td>POINT (-79.18670 33.35170)</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>438 rows × 6 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "        nws_id                               name state        status  \\\n",
-       "nos_id                                                                  \n",
-       "1600012  46125                          QREB buoy              active   \n",
-       "1619910  SNDP5        Sand Island, Midway Islands              active   \n",
-       "1630000  APRP7                  Apra Harbor, Guam              active   \n",
-       "1631428  PGBP7                     Pago Bay, Guam              active   \n",
-       "1770000  NSTP6          Pago Pago, American Samoa              active   \n",
-       "...        ...                                ...   ...           ...   \n",
-       "9087079  GBWW3                          Green Bay    WI  discontinued   \n",
-       "8770570  SBPT2                  Sabine Pass North    TX  discontinued   \n",
-       "8775870  MQTT2      Bob Hall Pier, Corpus Christi    TX  discontinued   \n",
-       "8740166  GBRM6  Grand Bay NERR, Mississippi Sound    MS  discontinued   \n",
-       "8662245  NITS1   Oyster Landing (N Inlet Estuary)    SC  discontinued   \n",
-       "\n",
-       "                                                   removed  \\\n",
-       "nos_id                                                       \n",
-       "1600012                                               <NA>   \n",
-       "1619910                                               <NA>   \n",
-       "1630000                                               <NA>   \n",
-       "1631428                                               <NA>   \n",
-       "1770000                                               <NA>   \n",
-       "...                                                    ...   \n",
-       "9087079  2020-10-28 13:00:00,2007-08-06 23:59:00,2007-0...   \n",
-       "8770570  2021-01-18 00:00:00,2020-09-30 15:45:00,2020-0...   \n",
-       "8775870  2021-12-22 20:00:00,2020-05-18 13:10:00,2019-0...   \n",
-       "8740166  2022-04-07 00:00:00,2022-03-30 23:58:00,2015-1...   \n",
-       "8662245  2022-06-07 23:59:00,2022-06-07 00:00:00,2022-0...   \n",
-       "\n",
-       "                             geometry  \n",
-       "nos_id                                 \n",
-       "1600012    POINT (122.60028 37.75008)  \n",
-       "1619910   POINT (-177.36003 28.21170)  \n",
-       "1630000    POINT (144.65636 13.44339)  \n",
-       "1631428    POINT (144.79700 13.42830)  \n",
-       "1770000  POINT (-170.68944 -14.27667)  \n",
-       "...                               ...  \n",
-       "9087079    POINT (-88.00722 44.54111)  \n",
-       "8770570    POINT (-93.87010 29.72840)  \n",
-       "8775870    POINT (-97.21670 27.58000)  \n",
-       "8740166    POINT (-88.40289 30.41319)  \n",
-       "8662245    POINT (-79.18670 33.35170)  \n",
-       "\n",
-       "[438 rows x 6 columns]"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from searvey.coops import coops_stations\n",
     "\n",
@@ -259,36 +65,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1.0, 'all CO-OPS stations')"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 864x533.981 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "figure, axis = pyplot.subplots(1, 1)\n",
     "figure.set_size_inches(12, 12 / 1.61803398875)\n",
@@ -312,207 +95,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>nws_id</th>\n",
-       "      <th>name</th>\n",
-       "      <th>state</th>\n",
-       "      <th>status</th>\n",
-       "      <th>removed</th>\n",
-       "      <th>geometry</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>nos_id</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>8726679</th>\n",
-       "      <td>TSHF1</td>\n",
-       "      <td>East Bay Causeway</td>\n",
-       "      <td>FL</td>\n",
-       "      <td>active</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>POINT (-82.42575 27.92889)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8726694</th>\n",
-       "      <td>TPAF1</td>\n",
-       "      <td>TPA Cruise Terminal 2</td>\n",
-       "      <td>FL</td>\n",
-       "      <td>active</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>POINT (-82.43330 27.93330)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9044036</th>\n",
-       "      <td>FWNM4</td>\n",
-       "      <td>Fort Wayne</td>\n",
-       "      <td>MI</td>\n",
-       "      <td>active</td>\n",
-       "      <td>2005-04-29 23:59:00,2005-04-29 00:00:00,2001-1...</td>\n",
-       "      <td>POINT (-83.09330 42.29830)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9075035</th>\n",
-       "      <td>ESVM4</td>\n",
-       "      <td>Essexville</td>\n",
-       "      <td>MI</td>\n",
-       "      <td>active</td>\n",
-       "      <td>2007-03-28 23:59:00,2007-03-28 00:00:00,2007-0...</td>\n",
-       "      <td>POINT (-83.84680 43.64040)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9052076</th>\n",
-       "      <td>OCTN6</td>\n",
-       "      <td>Olcott</td>\n",
-       "      <td>NY</td>\n",
-       "      <td>active</td>\n",
-       "      <td>2007-06-01 23:59:00,2007-06-01 00:00:00,2004-0...</td>\n",
-       "      <td>POINT (-78.72733 43.33839)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8654400</th>\n",
-       "      <td>CFPN7</td>\n",
-       "      <td>Cape Hatteras Fishing Pier</td>\n",
-       "      <td>NC</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2018-09-19 23:59:00,2003-09-18 23:59:00,2003-0...</td>\n",
-       "      <td>POINT (-75.63500 35.22330)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8720625</th>\n",
-       "      <td>RCYF1</td>\n",
-       "      <td>Racy Point, St Johns River</td>\n",
-       "      <td>FL</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2019-08-05 14:00:00,2017-06-14 15:36:00,2017-0...</td>\n",
-       "      <td>POINT (-81.54830 29.80170)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8423898</th>\n",
-       "      <td>FTPN3</td>\n",
-       "      <td>Fort Point</td>\n",
-       "      <td>NH</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2020-04-13 00:00:00,2014-08-05 00:00:00,2012-0...</td>\n",
-       "      <td>POINT (-70.71056 43.07139)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8726667</th>\n",
-       "      <td>MCYF1</td>\n",
-       "      <td>Mckay Bay Entrance</td>\n",
-       "      <td>FL</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2020-05-20 00:00:00,2019-03-08 00:00:00,2017-0...</td>\n",
-       "      <td>POINT (-82.42500 27.91333)</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8662245</th>\n",
-       "      <td>NITS1</td>\n",
-       "      <td>Oyster Landing (N Inlet Estuary)</td>\n",
-       "      <td>SC</td>\n",
-       "      <td>discontinued</td>\n",
-       "      <td>2022-06-07 23:59:00,2022-06-07 00:00:00,2022-0...</td>\n",
-       "      <td>POINT (-79.18670 33.35170)</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>169 rows × 6 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "        nws_id                              name state        status  \\\n",
-       "nos_id                                                                 \n",
-       "8726679  TSHF1                 East Bay Causeway    FL        active   \n",
-       "8726694  TPAF1             TPA Cruise Terminal 2    FL        active   \n",
-       "9044036  FWNM4                        Fort Wayne    MI        active   \n",
-       "9075035  ESVM4                        Essexville    MI        active   \n",
-       "9052076  OCTN6                            Olcott    NY        active   \n",
-       "...        ...                               ...   ...           ...   \n",
-       "8654400  CFPN7        Cape Hatteras Fishing Pier    NC  discontinued   \n",
-       "8720625  RCYF1        Racy Point, St Johns River    FL  discontinued   \n",
-       "8423898  FTPN3                        Fort Point    NH  discontinued   \n",
-       "8726667  MCYF1                Mckay Bay Entrance    FL  discontinued   \n",
-       "8662245  NITS1  Oyster Landing (N Inlet Estuary)    SC  discontinued   \n",
-       "\n",
-       "                                                   removed  \\\n",
-       "nos_id                                                       \n",
-       "8726679                                               <NA>   \n",
-       "8726694                                               <NA>   \n",
-       "9044036  2005-04-29 23:59:00,2005-04-29 00:00:00,2001-1...   \n",
-       "9075035  2007-03-28 23:59:00,2007-03-28 00:00:00,2007-0...   \n",
-       "9052076  2007-06-01 23:59:00,2007-06-01 00:00:00,2004-0...   \n",
-       "...                                                    ...   \n",
-       "8654400  2018-09-19 23:59:00,2003-09-18 23:59:00,2003-0...   \n",
-       "8720625  2019-08-05 14:00:00,2017-06-14 15:36:00,2017-0...   \n",
-       "8423898  2020-04-13 00:00:00,2014-08-05 00:00:00,2012-0...   \n",
-       "8726667  2020-05-20 00:00:00,2019-03-08 00:00:00,2017-0...   \n",
-       "8662245  2022-06-07 23:59:00,2022-06-07 00:00:00,2022-0...   \n",
-       "\n",
-       "                           geometry  \n",
-       "nos_id                               \n",
-       "8726679  POINT (-82.42575 27.92889)  \n",
-       "8726694  POINT (-82.43330 27.93330)  \n",
-       "9044036  POINT (-83.09330 42.29830)  \n",
-       "9075035  POINT (-83.84680 43.64040)  \n",
-       "9052076  POINT (-78.72733 43.33839)  \n",
-       "...                             ...  \n",
-       "8654400  POINT (-75.63500 35.22330)  \n",
-       "8720625  POINT (-81.54830 29.80170)  \n",
-       "8423898  POINT (-70.71056 43.07139)  \n",
-       "8726667  POINT (-82.42500 27.91333)  \n",
-       "8662245  POINT (-79.18670 33.35170)  \n",
-       "\n",
-       "[169 rows x 6 columns]"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import shapely\n",
     "from searvey.coops import coops_stations_within_region\n",
@@ -524,36 +113,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1.0, 'CO-OPS stations on the U.S. East Coast')"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 864x533.981 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "figure, axis = pyplot.subplots(1, 1)\n",
     "figure.set_size_inches(12, 12 / 1.61803398875)\n",
@@ -582,9 +148,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -592,642 +157,7 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
-       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "</symbol>\n",
-       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
-       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-array-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: '►';\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: '(';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: ')';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:  (t: 6, nos_id: 112)\n",
-       "Coordinates:\n",
-       "  * t        (t) datetime64[ns] 2022-04-02T12:00:00 ... 2022-04-02T12:30:00\n",
-       "  * nos_id   (nos_id) object &#x27;9044036&#x27; &#x27;9075035&#x27; ... &#x27;8573364&#x27; &#x27;8519483&#x27;\n",
-       "    nws_id   (nos_id) &lt;U5 &#x27;FWNM4&#x27; &#x27;ESVM4&#x27; &#x27;OCTN6&#x27; ... &#x27;NCDV2&#x27; &#x27;TCBM2&#x27; &#x27;BGNN6&#x27;\n",
-       "    x        (nos_id) float64 -83.09 -83.85 -78.73 ... -77.04 -76.25 -74.14\n",
-       "    y        (nos_id) float64 42.3 43.64 43.34 42.09 ... 38.98 38.32 39.21 40.64\n",
-       "Data variables:\n",
-       "    v        (nos_id, t) float32 175.1 175.1 175.1 175.1 ... 2.579 2.611 2.631\n",
-       "    s        (nos_id, t) float32 0.0 0.0 0.0 0.0 0.0 ... 0.026 0.02 0.024 0.027\n",
-       "    f        (nos_id, t) object &#x27;0,0,0,0&#x27; &#x27;0,0,0,0&#x27; ... &#x27;0,0,0,0&#x27; &#x27;0,0,0,0&#x27;\n",
-       "    q        (nos_id, t) object &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; ... &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-13b8fdc8-b9bd-47e6-a844-a3bd9ebf8f3f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-13b8fdc8-b9bd-47e6-a844-a3bd9ebf8f3f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>t</span>: 6</li><li><span class='xr-has-index'>nos_id</span>: 112</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d2ff9ebd-6217-4b6b-87b4-6aa4de104e8c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d2ff9ebd-6217-4b6b-87b4-6aa4de104e8c' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-04-02T12:00:00 ... 2022-04-...</div><input id='attrs-1bcd2b0c-41b5-4aa6-8caa-f0f0ce888975' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1bcd2b0c-41b5-4aa6-8caa-f0f0ce888975' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8816017d-6b75-421f-aad3-538284d89239' class='xr-var-data-in' type='checkbox'><label for='data-8816017d-6b75-421f-aad3-538284d89239' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-04-02T12:00:00.000000000&#x27;, &#x27;2022-04-02T12:06:00.000000000&#x27;,\n",
-       "       &#x27;2022-04-02T12:12:00.000000000&#x27;, &#x27;2022-04-02T12:18:00.000000000&#x27;,\n",
-       "       &#x27;2022-04-02T12:24:00.000000000&#x27;, &#x27;2022-04-02T12:30:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nos_id</span></div><div class='xr-var-dims'>(nos_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;9044036&#x27; &#x27;9075035&#x27; ... &#x27;8519483&#x27;</div><input id='attrs-f9032744-773f-450a-b7ba-5a518aa9dea8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f9032744-773f-450a-b7ba-5a518aa9dea8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4771bea1-1c99-465a-830a-4384a75989cc' class='xr-var-data-in' type='checkbox'><label for='data-4771bea1-1c99-465a-830a-4384a75989cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;9044036&#x27;, &#x27;9075035&#x27;, &#x27;9052076&#x27;, &#x27;9044020&#x27;, &#x27;9044049&#x27;, &#x27;9014090&#x27;,\n",
-       "       &#x27;8311030&#x27;, &#x27;9034052&#x27;, &#x27;9063009&#x27;, &#x27;9052030&#x27;, &#x27;9014080&#x27;, &#x27;9063007&#x27;,\n",
-       "       &#x27;9063090&#x27;, &#x27;9014096&#x27;, &#x27;8577330&#x27;, &#x27;8419317&#x27;, &#x27;9044030&#x27;, &#x27;8467150&#x27;,\n",
-       "       &#x27;9063053&#x27;, &#x27;8726520&#x27;, &#x27;8594900&#x27;, &#x27;9063012&#x27;, &#x27;9014087&#x27;, &#x27;9014070&#x27;,\n",
-       "       &#x27;8447930&#x27;, &#x27;9075002&#x27;, &#x27;8570283&#x27;, &#x27;8454000&#x27;, &#x27;8540433&#x27;, &#x27;8726724&#x27;,\n",
-       "       &#x27;8571892&#x27;, &#x27;9063028&#x27;, &#x27;9052058&#x27;, &#x27;8534720&#x27;, &#x27;8518750&#x27;, &#x27;8557380&#x27;,\n",
-       "       &#x27;8465705&#x27;, &#x27;8410140&#x27;, &#x27;8454049&#x27;, &#x27;8447435&#x27;, &#x27;8545240&#x27;, &#x27;8418150&#x27;,\n",
-       "       &#x27;8727520&#x27;, &#x27;8728690&#x27;, &#x27;8555889&#x27;, &#x27;8726607&#x27;, &#x27;8720030&#x27;, &#x27;8726384&#x27;,\n",
-       "       &#x27;8725520&#x27;, &#x27;8726674&#x27;, &#x27;8419870&#x27;, &#x27;8518962&#x27;, &#x27;8551910&#x27;, &#x27;8461490&#x27;,\n",
-       "       &#x27;8413320&#x27;, &#x27;8510560&#x27;, &#x27;8443970&#x27;, &#x27;8661070&#x27;, &#x27;8452944&#x27;, &#x27;8632200&#x27;,\n",
-       "       &#x27;8452660&#x27;, &#x27;8571421&#x27;, &#x27;9014098&#x27;, &#x27;9063063&#x27;, &#x27;8536110&#x27;, &#x27;9063085&#x27;,\n",
-       "       &#x27;8574680&#x27;, &#x27;8449130&#x27;, &#x27;8670870&#x27;, &#x27;8411060&#x27;, &#x27;8531680&#x27;, &#x27;8537121&#x27;,\n",
-       "       &#x27;8722956&#x27;, &#x27;8548989&#x27;, &#x27;8636580&#x27;, &#x27;9075014&#x27;, &#x27;9063020&#x27;, &#x27;8546252&#x27;,\n",
-       "       &#x27;8658120&#x27;, &#x27;8658163&#x27;, &#x27;8447386&#x27;, &#x27;8652587&#x27;, &#x27;8651370&#x27;, &#x27;8654467&#x27;,\n",
-       "       &#x27;9063038&#x27;, &#x27;8635750&#x27;, &#x27;8539094&#x27;, &#x27;8665530&#x27;, &#x27;8311062&#x27;, &#x27;8656483&#x27;,\n",
-       "       &#x27;8631044&#x27;, &#x27;8725110&#x27;, &#x27;8721604&#x27;, &#x27;8722670&#x27;, &#x27;8720226&#x27;, &#x27;8723214&#x27;,\n",
-       "       &#x27;8720357&#x27;, &#x27;8516945&#x27;, &#x27;8638610&#x27;, &#x27;9052000&#x27;, &#x27;8637689&#x27;, &#x27;8720219&#x27;,\n",
-       "       &#x27;8638901&#x27;, &#x27;8720218&#x27;, &#x27;8551762&#x27;, &#x27;8573927&#x27;, &#x27;8639348&#x27;, &#x27;9063079&#x27;,\n",
-       "       &#x27;8575512&#x27;, &#x27;8635027&#x27;, &#x27;8573364&#x27;, &#x27;8519483&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nws_id</span></div><div class='xr-var-dims'>(nos_id)</div><div class='xr-var-dtype'>&lt;U5</div><div class='xr-var-preview xr-preview'>&#x27;FWNM4&#x27; &#x27;ESVM4&#x27; ... &#x27;TCBM2&#x27; &#x27;BGNN6&#x27;</div><input id='attrs-60fcae85-6922-40da-b8ce-cf16485be40c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60fcae85-6922-40da-b8ce-cf16485be40c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb0c008b-c418-4f9a-8dfd-77c92e2d4d97' class='xr-var-data-in' type='checkbox'><label for='data-fb0c008b-c418-4f9a-8dfd-77c92e2d4d97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;FWNM4&#x27;, &#x27;ESVM4&#x27;, &#x27;OCTN6&#x27;, &#x27;GRTM4&#x27;, &#x27;WMPM4&#x27;, &#x27;MBRM4&#x27;, &#x27;OBGN6&#x27;,\n",
-       "       &#x27;SCSM4&#x27;, &#x27;AMFN6&#x27;, &#x27;OSGN6&#x27;, &#x27;SCRM4&#x27;, &#x27;NGAN6&#x27;, &#x27;FPPM4&#x27;, &#x27;DUPM4&#x27;,\n",
-       "       &#x27;SLIM2&#x27;, &#x27;WELM1&#x27;, &#x27;WDTM4&#x27;, &#x27;BRHC3&#x27;, &#x27;FAIO1&#x27;, &#x27;SAPF1&#x27;, &#x27;WASD2&#x27;,\n",
-       "       &#x27;NIAN6&#x27;, &#x27;PHXM4&#x27;, &#x27;AGCM4&#x27;, &#x27;BZBM3&#x27;, &#x27;LKPM4&#x27;, &#x27;OCIM2&#x27;, &#x27;FOXR1&#x27;,\n",
-       "       &#x27;MRCP1&#x27;, &#x27;CWBF1&#x27;, &#x27;CAMM2&#x27;, &#x27;PSTN6&#x27;, &#x27;RCRN6&#x27;, &#x27;ACYN4&#x27;, &#x27;BATN6&#x27;,\n",
-       "       &#x27;LWSD1&#x27;, &#x27;NWHC3&#x27;, &#x27;PSBM1&#x27;, &#x27;QPTR1&#x27;, &#x27;CHTM3&#x27;, &#x27;PHBP1&#x27;, &#x27;CASM1&#x27;,\n",
-       "       &#x27;CKYF1&#x27;, &#x27;APCF1&#x27;, &#x27;BRND1&#x27;, &#x27;OPTF1&#x27;, &#x27;FRDF1&#x27;, &#x27;PMAF1&#x27;, &#x27;FMRF1&#x27;,\n",
-       "       &#x27;EBEF1&#x27;, &#x27;SEIM1&#x27;, &#x27;TKPN6&#x27;, &#x27;RDYD1&#x27;, &#x27;NLNC3&#x27;, &#x27;ATGM1&#x27;, &#x27;MTKN6&#x27;,\n",
-       "       &#x27;BHBM3&#x27;, &#x27;MROS1&#x27;, &#x27;CPTR1&#x27;, &#x27;KPTV2&#x27;, &#x27;NWPR1&#x27;, &#x27;BISM2&#x27;, &#x27;FTGM4&#x27;,\n",
-       "       &#x27;CNDO1&#x27;, &#x27;CMAN4&#x27;, &#x27;THRO1&#x27;, &#x27;BLTM2&#x27;, &#x27;NTKM3&#x27;, &#x27;FPKG1&#x27;, &#x27;CFWM1&#x27;,\n",
-       "       &#x27;SDHN4&#x27;, &#x27;SJSN4&#x27;, &#x27;PEGF1&#x27;, &#x27;NBLP1&#x27;, &#x27;WNDV2&#x27;, &#x27;HRBM4&#x27;, &#x27;BUFN6&#x27;,\n",
-       "       &#x27;BDSP1&#x27;, &#x27;WLON7&#x27;, &#x27;JMPN7&#x27;, &#x27;FRVM3&#x27;, &#x27;ORIN7&#x27;, &#x27;DUKN7&#x27;, &#x27;HCGN7&#x27;,\n",
-       "       &#x27;EREP1&#x27;, &#x27;LWTV2&#x27;, &#x27;BDRN4&#x27;, &#x27;CHTS1&#x27;, &#x27;ALXN6&#x27;, &#x27;BFTN7&#x27;, &#x27;WAHV2&#x27;,\n",
-       "       &#x27;NPSF1&#x27;, &#x27;TRDF1&#x27;, &#x27;LKWF1&#x27;, &#x27;MSBF1&#x27;, &#x27;VAKF1&#x27;, &#x27;BKBF1&#x27;, &#x27;KPTN6&#x27;,\n",
-       "       &#x27;SWPV2&#x27;, &#x27;CAVN6&#x27;, &#x27;YKTV2&#x27;, &#x27;DMSF1&#x27;, &#x27;CHBV2&#x27;, &#x27;MYPF1&#x27;, &#x27;DELD1&#x27;,\n",
-       "       &#x27;CHCM2&#x27;, &#x27;MNPV2&#x27;, &#x27;MRHO1&#x27;, &#x27;APAM2&#x27;, &#x27;NCDV2&#x27;, &#x27;TCBM2&#x27;, &#x27;BGNN6&#x27;],\n",
-       "      dtype=&#x27;&lt;U5&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(nos_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-83.09 -83.85 ... -76.25 -74.14</div><input id='attrs-e1245ad5-366f-4fd2-8b44-da0a8895d5ca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e1245ad5-366f-4fd2-8b44-da0a8895d5ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a58d8c85-bd28-4501-8887-4f1fbe099f4b' class='xr-var-data-in' type='checkbox'><label for='data-a58d8c85-bd28-4501-8887-4f1fbe099f4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-83.09329987, -83.84680176, -78.72733307, -83.18669128,\n",
-       "       -82.93000031, -82.42040253, -75.49443817, -82.87924957,\n",
-       "       -79.06136322, -76.51183319, -82.48555756, -79.05992126,\n",
-       "       -83.25689697, -82.42169952, -76.45082855, -70.56330109,\n",
-       "       -83.14749908, -73.18170166, -81.28105927, -82.62689209,\n",
-       "       -77.021698  , -79.01389313, -82.44332886, -82.5266571 ,\n",
-       "       -70.67111206, -82.49330902, -75.09166718, -71.40119934,\n",
-       "       -75.40943909, -82.83170319, -76.06829834, -79.04733276,\n",
-       "       -77.62574768, -74.41829681, -74.01416779, -75.12000275,\n",
-       "       -72.90830231, -66.98290253, -71.41100311, -69.95082855,\n",
-       "       -75.14170074, -70.24417114, -83.03170013, -84.98169708,\n",
-       "       -75.11329651, -82.55278015, -81.46582794, -82.5625    ,\n",
-       "       -81.87120056, -82.42140198, -70.74111176, -73.93920135,\n",
-       "       -75.57330322, -72.08999634, -68.20427704, -71.95939636,\n",
-       "       -71.05027771, -78.91831207, -71.34329987, -75.98844147,\n",
-       "       -71.3266983 , -76.03829956, -82.42250061, -81.63546753,\n",
-       "       -74.95999908, -83.47228241, -76.57830048, -70.09638977,\n",
-       "       -80.90170288, -67.20467377, -74.00943756, -75.375     ,\n",
-       "       -80.11669922, -74.75170135, -76.29000092, -82.64305878,\n",
-       "       -78.89047241, -75.07499695, -77.95361328, -77.78668976,\n",
-       "       -71.16410065, -75.54805756, -75.74669647, -75.70417023,\n",
-       "       -80.07582855, -76.46460724, -74.86969757, -79.92360687,\n",
-       "       -75.93453217, -76.66999817, -75.68582916, -81.80747223,\n",
-       "       -80.59306335, -80.03417206, -81.65830231, -80.16179657,\n",
-       "       -81.68888855, -73.76499939, -76.33000183, -76.33197021,\n",
-       "       -76.47881317, -81.5582962 , -76.08329773, -81.42788696,\n",
-       "       -75.58830261, -75.80999756, -76.30168915, -82.73139191,\n",
-       "       -76.48155975, -77.03669739, -76.24500275, -74.14170074])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(nos_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>42.3 43.64 43.34 ... 39.21 40.64</div><input id='attrs-afed06e4-d13c-4b82-ad7b-dfeb6925b0bf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-afed06e4-d13c-4b82-ad7b-dfeb6925b0bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd4e023c-68cd-4767-8917-7239eb8e6ea6' class='xr-var-data-in' type='checkbox'><label for='data-dd4e023c-68cd-4767-8917-7239eb8e6ea6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([42.2983017 , 43.64039993, 43.33839035, 42.09169006, 42.35749817,\n",
-       "       42.97380066, 44.70286179, 42.47322083, 43.0810585 , 43.46416855,\n",
-       "       42.81222153, 43.09991837, 41.96009827, 43.00329971, 38.31721878,\n",
-       "       43.31999969, 42.20230865, 41.1733017 , 41.75975037, 27.76061058,\n",
-       "       38.87329865, 43.07691956, 42.94527817, 42.62110901, 41.52360916,\n",
-       "       43.1416893 , 38.32833099, 41.80709839, 39.8116684 , 27.97830009,\n",
-       "       38.57329941, 42.69131088, 43.26903152, 39.35499954, 40.70056152,\n",
-       "       38.78170013, 41.28329849, 44.90459824, 41.58679962, 41.68806076,\n",
-       "       39.93330002, 43.65805817, 29.13500023, 29.72669983, 38.98669815,\n",
-       "       27.85778046, 30.67139053, 27.63833046, 26.64769936, 27.92309952,\n",
-       "       43.07971954, 42.01390076, 39.55830002, 41.3614006 , 44.39218903,\n",
-       "       41.0483017 , 42.35388947, 33.65499878, 41.71670151, 37.16519165,\n",
-       "       41.50500107, 38.22000122, 43.00690079, 41.54085922, 38.96829987,\n",
-       "       41.69356155, 39.26670074, 41.28527832, 32.0367012 , 44.6570282 ,\n",
-       "       40.46694183, 39.30500031, 26.08169937, 40.13669968, 37.61619949,\n",
-       "       43.84638977, 42.87744141, 39.98329926, 34.22750092, 34.21331024,\n",
-       "       41.70429993, 35.79499817, 36.18330002, 35.20864105, 42.1538887 ,\n",
-       "       37.99539185, 40.08169937, 32.78083038, 44.33110809, 34.72000122,\n",
-       "       37.60778046, 26.13167   , 28.41583061, 26.61277962, 30.31999969,\n",
-       "       25.73139954, 30.19241905, 40.81031036, 36.94670105, 44.1301918 ,\n",
-       "       37.22650146, 30.38669968, 37.03290176, 30.39817047, 39.58169937,\n",
-       "       39.52669907, 36.77830887, 41.54364014, 38.98328018, 38.31999969,\n",
-       "       39.2132988 , 40.63669968])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3bdf39a1-d883-46e4-b273-f8cde4ab980f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3bdf39a1-d883-46e4-b273-f8cde4ab980f' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(nos_id, t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>175.1 175.1 175.1 ... 2.611 2.631</div><input id='attrs-8d93136d-8f23-450f-a80a-8013ce9172b2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8d93136d-8f23-450f-a80a-8013ce9172b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d3de9da-dc93-46cd-829e-85c2a74b85cd' class='xr-var-data-in' type='checkbox'><label for='data-6d3de9da-dc93-46cd-829e-85c2a74b85cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.75089e+02,  1.75088e+02,  1.75089e+02,  1.75090e+02,\n",
-       "         1.75091e+02,  1.75091e+02],\n",
-       "       [ 1.76669e+02,  1.76669e+02,  1.76669e+02,  1.76670e+02,\n",
-       "         1.76671e+02,  1.76668e+02],\n",
-       "       [ 7.50860e+01,          nan,  7.50840e+01,  7.50780e+01,\n",
-       "         7.50850e+01,  7.50890e+01],\n",
-       "       [ 1.74685e+02,  1.74683e+02,  1.74678e+02,  1.74677e+02,\n",
-       "         1.74682e+02,  1.74685e+02],\n",
-       "       [ 1.75304e+02,  1.75304e+02,  1.75304e+02,  1.75304e+02,\n",
-       "         1.75304e+02,  1.75304e+02],\n",
-       "       [ 1.76327e+02,  1.76321e+02,  1.76317e+02,  1.76314e+02,\n",
-       "         1.76308e+02,  1.76306e+02],\n",
-       "       [ 7.46720e+01,  7.46730e+01,  7.46730e+01,  7.46750e+01,\n",
-       "         7.46770e+01,  7.46770e+01],\n",
-       "       [ 1.75360e+02,  1.75359e+02,  1.75358e+02,  1.75360e+02,\n",
-       "         1.75360e+02,  1.75361e+02],\n",
-       "       [ 1.70448e+02,  1.70435e+02,  1.70433e+02,  1.70441e+02,\n",
-       "         1.70439e+02,  1.70439e+02],\n",
-       "       [ 7.50870e+01,  7.50850e+01,  7.50680e+01,  7.50870e+01,\n",
-       "         7.50950e+01,  7.50780e+01],\n",
-       "...\n",
-       "       [ 2.01300e+00,  2.03200e+00,  2.05900e+00,  2.08400e+00,\n",
-       "         2.08900e+00,  2.09600e+00],\n",
-       "       [ 3.79900e+00,  3.82300e+00,  3.85500e+00,  3.89500e+00,\n",
-       "         3.92400e+00,  3.94100e+00],\n",
-       "       [ 6.55200e+00,  6.55700e+00,  6.56300e+00,  6.57000e+00,\n",
-       "         6.58100e+00,  6.59500e+00],\n",
-       "       [ 8.67000e-01,  8.72000e-01,  8.85000e-01,  9.08000e-01,\n",
-       "         9.03000e-01,  9.21000e-01],\n",
-       "       [ 7.05400e+00,  7.08000e+00,  7.10400e+00,  7.12200e+00,\n",
-       "         7.14400e+00,  7.17000e+00],\n",
-       "       [ 1.74591e+02,  1.74595e+02,  1.74594e+02,  1.74598e+02,\n",
-       "         1.74597e+02,  1.74591e+02],\n",
-       "       [ 1.56100e+00,  1.55200e+00,  1.54700e+00,  1.53500e+00,\n",
-       "         1.53300e+00,  1.53000e+00],\n",
-       "       [ 5.05200e+00,  5.04200e+00,  5.03000e+00,  5.01700e+00,\n",
-       "         5.00600e+00,  4.99600e+00],\n",
-       "       [ 1.28900e+00,  1.28600e+00,  1.29300e+00,  1.29400e+00,\n",
-       "         1.29500e+00,  1.30100e+00],\n",
-       "       [ 2.47100e+00,  2.50900e+00,  2.54400e+00,  2.57900e+00,\n",
-       "         2.61100e+00,  2.63100e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>s</span></div><div class='xr-var-dims'>(nos_id, t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 0.02 0.024 0.027</div><input id='attrs-c2e20437-8e3f-4636-a88b-7a9deea8f2b6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2e20437-8e3f-4636-a88b-7a9deea8f2b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-726b640f-4cac-4196-bc22-0b836495ed56' class='xr-var-data-in' type='checkbox'><label for='data-726b640f-4cac-4196-bc22-0b836495ed56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.   , 0.   , 0.   , 0.   , 0.   , 0.   ],\n",
-       "       [0.   , 0.   , 0.   , 0.   , 0.001, 0.002],\n",
-       "       [0.001,   nan, 0.006, 0.002, 0.003, 0.005],\n",
-       "       [0.   , 0.001, 0.001, 0.   , 0.001, 0.   ],\n",
-       "       [0.   , 0.   , 0.   , 0.   , 0.   , 0.   ],\n",
-       "       [0.001, 0.   , 0.001, 0.001, 0.001, 0.   ],\n",
-       "       [0.   , 0.   , 0.   , 0.001, 0.   , 0.   ],\n",
-       "       [0.001, 0.001, 0.001, 0.001, 0.001, 0.001],\n",
-       "       [0.   , 0.005, 0.001, 0.   , 0.   , 0.001],\n",
-       "       [0.002, 0.005, 0.003, 0.004, 0.002, 0.002],\n",
-       "       [0.002, 0.005, 0.018, 0.003, 0.002, 0.003],\n",
-       "       [0.003, 0.008, 0.007, 0.006, 0.005, 0.006],\n",
-       "       [0.   , 0.001, 0.001, 0.   , 0.002, 0.   ],\n",
-       "       [0.   , 0.002, 0.001, 0.001, 0.   , 0.   ],\n",
-       "       [0.007, 0.007, 0.008, 0.009, 0.009, 0.012],\n",
-       "       [0.01 , 0.004, 0.008, 0.011, 0.009, 0.001],\n",
-       "       [0.   , 0.001, 0.001, 0.001, 0.001, 0.   ],\n",
-       "       [0.01 , 0.014, 0.012, 0.021, 0.015, 0.018],\n",
-       "       [0.   , 0.   , 0.   , 0.001, 0.001, 0.   ],\n",
-       "       [0.003, 0.002, 0.002, 0.003, 0.002, 0.002],\n",
-       "...\n",
-       "       [0.017, 0.012, 0.026, 0.027, 0.03 , 0.012],\n",
-       "       [0.042, 0.034, 0.042, 0.046, 0.035, 0.043],\n",
-       "       [0.006, 0.007, 0.006, 0.007, 0.008, 0.007],\n",
-       "       [0.005, 0.005, 0.006, 0.006, 0.005, 0.006],\n",
-       "       [0.001, 0.001, 0.001, 0.002, 0.002, 0.002],\n",
-       "       [0.015, 0.015, 0.016, 0.016, 0.014, 0.019],\n",
-       "       [0.006, 0.008, 0.007, 0.006, 0.005, 0.029],\n",
-       "       [0.011, 0.01 , 0.012, 0.01 , 0.011, 0.01 ],\n",
-       "       [0.005, 0.006, 0.005, 0.006, 0.005, 0.007],\n",
-       "       [0.005, 0.005, 0.006, 0.005, 0.004, 0.004],\n",
-       "       [0.068, 0.078, 0.059, 0.076, 0.088, 0.08 ],\n",
-       "       [0.01 , 0.01 , 0.006, 0.005, 0.005, 0.01 ],\n",
-       "       [0.02 , 0.   , 0.   , 0.   , 0.   , 0.   ],\n",
-       "       [0.004, 0.002, 0.004, 0.003, 0.005, 0.003],\n",
-       "       [0.008, 0.01 , 0.007, 0.007, 0.006, 0.009],\n",
-       "       [0.001, 0.003, 0.001, 0.002, 0.001, 0.001],\n",
-       "       [0.006, 0.007, 0.006, 0.006, 0.01 , 0.01 ],\n",
-       "       [0.005, 0.003, 0.005, 0.006, 0.004, 0.002],\n",
-       "       [0.006, 0.005, 0.006, 0.006, 0.006, 0.006],\n",
-       "       [0.026, 0.027, 0.026, 0.02 , 0.024, 0.027]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>f</span></div><div class='xr-var-dims'>(nos_id, t)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;0,0,0,0&#x27; &#x27;0,0,0,0&#x27; ... &#x27;0,0,0,0&#x27;</div><input id='attrs-5780cbd5-8a1e-4d0c-9a61-694c7eed77d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5780cbd5-8a1e-4d0c-9a61-694c7eed77d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba69798e-1b93-427b-b94f-5532c43e4e61' class='xr-var-data-in' type='checkbox'><label for='data-ba69798e-1b93-427b-b94f-5532c43e4e61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, nan, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,1,0,0&#x27;, &#x27;0,1,0,0&#x27;, &#x27;0,1,0,0&#x27;, &#x27;0,1,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;1,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;1,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "...\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;1,0,0,0&#x27;, &#x27;1,0,0,0&#x27;, &#x27;1,0,0,0&#x27;, &#x27;1,0,0,0&#x27;, &#x27;1,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;],\n",
-       "       [&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;]],\n",
-       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>q</span></div><div class='xr-var-dims'>(nos_id, t)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; ... &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27;</div><input id='attrs-5fcc7597-9a2d-486b-90a2-578bb5431eb6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5fcc7597-9a2d-486b-90a2-578bb5431eb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a320f6c-85da-459d-abaf-4bc4a97a5a76' class='xr-var-data-in' type='checkbox'><label for='data-8a320f6c-85da-459d-abaf-4bc4a97a5a76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, nan, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;p&#x27;, &#x27;p&#x27;, &#x27;p&#x27;, &#x27;p&#x27;, &#x27;p&#x27;, &#x27;p&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "...\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;],\n",
-       "       [&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;]], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0b3d1818-8e79-4997-a2dc-21df0bc00a51' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0b3d1818-8e79-4997-a2dc-21df0bc00a51' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:  (t: 6, nos_id: 112)\n",
-       "Coordinates:\n",
-       "  * t        (t) datetime64[ns] 2022-04-02T12:00:00 ... 2022-04-02T12:30:00\n",
-       "  * nos_id   (nos_id) object '9044036' '9075035' ... '8573364' '8519483'\n",
-       "    nws_id   (nos_id) <U5 'FWNM4' 'ESVM4' 'OCTN6' ... 'NCDV2' 'TCBM2' 'BGNN6'\n",
-       "    x        (nos_id) float64 -83.09 -83.85 -78.73 ... -77.04 -76.25 -74.14\n",
-       "    y        (nos_id) float64 42.3 43.64 43.34 42.09 ... 38.98 38.32 39.21 40.64\n",
-       "Data variables:\n",
-       "    v        (nos_id, t) float32 175.1 175.1 175.1 175.1 ... 2.579 2.611 2.631\n",
-       "    s        (nos_id, t) float32 0.0 0.0 0.0 0.0 0.0 ... 0.026 0.02 0.024 0.027\n",
-       "    f        (nos_id, t) object '0,0,0,0' '0,0,0,0' ... '0,0,0,0' '0,0,0,0'\n",
-       "    q        (nos_id, t) object 'v' 'v' 'v' 'v' 'v' 'v' ... 'v' 'v' 'v' 'v' 'v'"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from datetime import datetime\n",
     "from searvey.coops import coops_product_within_region\n",
@@ -1243,9 +173,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -1253,30 +182,7 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1.0, 'maximum water levels observed by CO-OPS stations on the U.S. East Coast between 2022-04-02 12:00:00 and 2022-04-02 12:30:00')"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 864x533.981 with 2 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas\n",
     "\n",
@@ -1309,9 +215,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -1319,400 +224,7 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
-       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
-       "</symbol>\n",
-       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
-       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-array-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: '►';\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: '(';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: ')';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:  (nos_id: 1, t: 6)\n",
-       "Coordinates:\n",
-       "  * nos_id   (nos_id) object &#x27;1612480&#x27;\n",
-       "  * t        (t) datetime64[ns] 2022-04-02T12:00:00 ... 2022-04-02T12:30:00\n",
-       "    nws_id   (nos_id) &lt;U5 &#x27;MOKH1&#x27;\n",
-       "    x        (nos_id) float64 -157.8\n",
-       "    y        (nos_id) float64 21.43\n",
-       "Data variables:\n",
-       "    v        (nos_id, t) float32 1.406 1.409 1.414 1.417 1.417 1.422\n",
-       "    s        (nos_id, t) float32 0.001 0.002 0.002 0.002 0.001 0.002\n",
-       "    f        (nos_id, t) object &#x27;0,0,0,0&#x27; &#x27;0,0,0,0&#x27; ... &#x27;0,0,0,0&#x27; &#x27;0,0,0,0&#x27;\n",
-       "    q        (nos_id, t) object &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9192c99b-883e-417d-8d8a-f80bbcc51286' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9192c99b-883e-417d-8d8a-f80bbcc51286' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nos_id</span>: 1</li><li><span class='xr-has-index'>t</span>: 6</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3accd1c3-047b-4c44-a311-bc34af7ab86f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3accd1c3-047b-4c44-a311-bc34af7ab86f' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nos_id</span></div><div class='xr-var-dims'>(nos_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;1612480&#x27;</div><input id='attrs-60d211d4-3de9-4e90-ab34-75216be420af' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60d211d4-3de9-4e90-ab34-75216be420af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d98d0210-3631-457f-ac02-c40a9af106e4' class='xr-var-data-in' type='checkbox'><label for='data-d98d0210-3631-457f-ac02-c40a9af106e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1612480&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-04-02T12:00:00 ... 2022-04-...</div><input id='attrs-fc595448-5e69-4d3b-9ac4-ba278dc0c919' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fc595448-5e69-4d3b-9ac4-ba278dc0c919' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a63b3e05-7247-40e4-9f88-11bdce0b718a' class='xr-var-data-in' type='checkbox'><label for='data-a63b3e05-7247-40e4-9f88-11bdce0b718a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-04-02T12:00:00.000000000&#x27;, &#x27;2022-04-02T12:06:00.000000000&#x27;,\n",
-       "       &#x27;2022-04-02T12:12:00.000000000&#x27;, &#x27;2022-04-02T12:18:00.000000000&#x27;,\n",
-       "       &#x27;2022-04-02T12:24:00.000000000&#x27;, &#x27;2022-04-02T12:30:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nws_id</span></div><div class='xr-var-dims'>(nos_id)</div><div class='xr-var-dtype'>&lt;U5</div><div class='xr-var-preview xr-preview'>&#x27;MOKH1&#x27;</div><input id='attrs-7723c5c0-fa71-4389-8a1e-1f37af1d123d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7723c5c0-fa71-4389-8a1e-1f37af1d123d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47053ea0-893c-4e07-a499-a9926e4681da' class='xr-var-data-in' type='checkbox'><label for='data-47053ea0-893c-4e07-a499-a9926e4681da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;MOKH1&#x27;], dtype=&#x27;&lt;U5&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(nos_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-157.8</div><input id='attrs-0bb12c9c-faba-45d1-a24a-e430a7c4ce49' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0bb12c9c-faba-45d1-a24a-e430a7c4ce49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1d86f8b-7557-4836-b5c2-ddf164c7f4df' class='xr-var-data-in' type='checkbox'><label for='data-f1d86f8b-7557-4836-b5c2-ddf164c7f4df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-157.78999329])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(nos_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>21.43</div><input id='attrs-b2a830fd-7b60-4349-8c8a-ddb36e48a5ff' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2a830fd-7b60-4349-8c8a-ddb36e48a5ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8c08394-03ec-4f78-88e6-23e869b8cd11' class='xr-var-data-in' type='checkbox'><label for='data-a8c08394-03ec-4f78-88e6-23e869b8cd11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([21.43305969])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7f9845ae-3448-4d40-8dec-df757471929c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7f9845ae-3448-4d40-8dec-df757471929c' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(nos_id, t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.406 1.409 1.414 1.417 1.417 1.422</div><input id='attrs-f80fb6d0-7bd4-4bb2-a4c7-74ebc61eeb54' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f80fb6d0-7bd4-4bb2-a4c7-74ebc61eeb54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6349bc95-fa75-44e9-8bb0-8c8b7b60c67c' class='xr-var-data-in' type='checkbox'><label for='data-6349bc95-fa75-44e9-8bb0-8c8b7b60c67c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.406, 1.409, 1.414, 1.417, 1.417, 1.422]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>s</span></div><div class='xr-var-dims'>(nos_id, t)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.001 0.002 0.002 0.002 0.001 0.002</div><input id='attrs-9e32cb3d-2484-442b-8ceb-7609a26748f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9e32cb3d-2484-442b-8ceb-7609a26748f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae0c277f-51e9-463d-a8cf-3906b1cf055d' class='xr-var-data-in' type='checkbox'><label for='data-ae0c277f-51e9-463d-a8cf-3906b1cf055d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.001, 0.002, 0.002, 0.002, 0.001, 0.002]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>f</span></div><div class='xr-var-dims'>(nos_id, t)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;0,0,0,0&#x27; &#x27;0,0,0,0&#x27; ... &#x27;0,0,0,0&#x27;</div><input id='attrs-53625c6a-7dc7-4cda-811b-a811a6ca5293' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53625c6a-7dc7-4cda-811b-a811a6ca5293' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d83a710-3020-4b5a-8e9f-a5a29f2a7069' class='xr-var-data-in' type='checkbox'><label for='data-4d83a710-3020-4b5a-8e9f-a5a29f2a7069' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;, &#x27;0,0,0,0&#x27;]],\n",
-       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>q</span></div><div class='xr-var-dims'>(nos_id, t)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27; &#x27;v&#x27;</div><input id='attrs-4f58ab4d-d902-4f29-bb00-5a62d2ca40b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4f58ab4d-d902-4f29-bb00-5a62d2ca40b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfb0d91d-fe66-4437-8ebf-5cc31255ab78' class='xr-var-data-in' type='checkbox'><label for='data-dfb0d91d-fe66-4437-8ebf-5cc31255ab78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;, &#x27;v&#x27;]], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9717e0c5-b288-4d3b-8986-68eff48ebe29' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9717e0c5-b288-4d3b-8986-68eff48ebe29' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:  (nos_id: 1, t: 6)\n",
-       "Coordinates:\n",
-       "  * nos_id   (nos_id) object '1612480'\n",
-       "  * t        (t) datetime64[ns] 2022-04-02T12:00:00 ... 2022-04-02T12:30:00\n",
-       "    nws_id   (nos_id) <U5 'MOKH1'\n",
-       "    x        (nos_id) float64 -157.8\n",
-       "    y        (nos_id) float64 21.43\n",
-       "Data variables:\n",
-       "    v        (nos_id, t) float32 1.406 1.409 1.414 1.417 1.417 1.422\n",
-       "    s        (nos_id, t) float32 0.001 0.002 0.002 0.002 0.001 0.002\n",
-       "    f        (nos_id, t) object '0,0,0,0' '0,0,0,0' ... '0,0,0,0' '0,0,0,0'\n",
-       "    q        (nos_id, t) object 'v' 'v' 'v' 'v' 'v' 'v'"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from searvey.coops import COOPS_Station\n",
     "\n",
@@ -1727,9 +239,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -1737,30 +248,7 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1.0, 'water level observed by CO-OPS station 1612480 (\"Mokuoloe\") between 2022-04-02 12:00:00 and 2022-04-02 12:30:00')"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 864x533.981 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "figure, axis = pyplot.subplots(1, 1)\n",
     "figure.set_size_inches(12, 12 / 1.61803398875)\n",
@@ -1806,7 +294,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.9.16"
   }
  },
  "nbformat": 4,
diff --git a/poetry.lock b/poetry.lock
index 91a17c2..12d2873 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -13,25 +13,35 @@ files = [
 ]
 
 [[package]]
-name = "astroid"
-version = "2.14.2"
-description = "An abstract syntax tree for Python with inference support."
+name = "appnope"
+version = "0.1.3"
+description = "Disable App Nap on macOS >= 10.9"
 category = "dev"
 optional = false
-python-versions = ">=3.7.2"
+python-versions = "*"
 files = [
-    {file = "astroid-2.14.2-py3-none-any.whl", hash = "sha256:0e0e3709d64fbffd3037e4ff403580550f14471fd3eaae9fa11cc9a5c7901153"},
-    {file = "astroid-2.14.2.tar.gz", hash = "sha256:a3cf9f02c53dd259144a7e8f3ccd75d67c9a8c716ef183e0c1f291bc5d7bb3cf"},
+    {file = "appnope-0.1.3-py2.py3-none-any.whl", hash = "sha256:265a455292d0bd8a72453494fa24df5a11eb18373a60c7c0430889f22548605e"},
+    {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
 ]
 
-[package.dependencies]
-lazy-object-proxy = ">=1.4.0"
-typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
-wrapt = [
-    {version = ">=1.11,<2", markers = "python_version < \"3.11\""},
-    {version = ">=1.14,<2", markers = "python_version >= \"3.11\""},
+[[package]]
+name = "asttokens"
+version = "2.2.1"
+description = "Annotate AST trees with source code positions"
+category = "dev"
+optional = false
+python-versions = "*"
+files = [
+    {file = "asttokens-2.2.1-py2.py3-none-any.whl", hash = "sha256:6b0ac9e93fb0335014d382b8fa9b3afa7df546984258005da0b9e7095b3deb1c"},
+    {file = "asttokens-2.2.1.tar.gz", hash = "sha256:4622110b2a6f30b77e1473affaa97e711bc2f07d3f10848420ff1898edbe94f3"},
 ]
 
+[package.dependencies]
+six = "*"
+
+[package.extras]
+test = ["astroid", "pytest"]
+
 [[package]]
 name = "attrs"
 version = "22.2.0"
@@ -66,6 +76,18 @@ files = [
 [package.dependencies]
 pytz = {version = ">=2015.7", markers = "python_version < \"3.9\""}
 
+[[package]]
+name = "backcall"
+version = "0.2.0"
+description = "Specifications for callback functions passed in to an API"
+category = "dev"
+optional = false
+python-versions = "*"
+files = [
+    {file = "backcall-0.2.0-py2.py3-none-any.whl", hash = "sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255"},
+    {file = "backcall-0.2.0.tar.gz", hash = "sha256:5cbdbf27be5e7cfadb448baf0aa95508f91f2bbc6c6437cd9cd06e2a4c215e1e"},
+]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.11.2"
@@ -98,28 +120,81 @@ files = [
 ]
 
 [[package]]
-name = "cfgv"
-version = "3.3.1"
-description = "Validate configuration and produce human readable error messages."
+name = "cffi"
+version = "1.15.1"
+description = "Foreign Function Interface for Python calling C code."
 category = "dev"
 optional = false
-python-versions = ">=3.6.1"
+python-versions = "*"
 files = [
-    {file = "cfgv-3.3.1-py2.py3-none-any.whl", hash = "sha256:c6a0883f3917a037485059700b9e75da2464e6c27051014ad85ba6aaa5884426"},
-    {file = "cfgv-3.3.1.tar.gz", hash = "sha256:f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736"},
+    {file = "cffi-1.15.1-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:a66d3508133af6e8548451b25058d5812812ec3798c886bf38ed24a98216fab2"},
+    {file = "cffi-1.15.1-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:470c103ae716238bbe698d67ad020e1db9d9dba34fa5a899b5e21577e6d52ed2"},
+    {file = "cffi-1.15.1-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:9ad5db27f9cabae298d151c85cf2bad1d359a1b9c686a275df03385758e2f914"},
+    {file = "cffi-1.15.1-cp27-cp27m-win32.whl", hash = "sha256:b3bbeb01c2b273cca1e1e0c5df57f12dce9a4dd331b4fa1635b8bec26350bde3"},
+    {file = "cffi-1.15.1-cp27-cp27m-win_amd64.whl", hash = "sha256:e00b098126fd45523dd056d2efba6c5a63b71ffe9f2bbe1a4fe1716e1d0c331e"},
+    {file = "cffi-1.15.1-cp27-cp27mu-manylinux1_i686.whl", hash = "sha256:d61f4695e6c866a23a21acab0509af1cdfd2c013cf256bbf5b6b5e2695827162"},
+    {file = "cffi-1.15.1-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:ed9cb427ba5504c1dc15ede7d516b84757c3e3d7868ccc85121d9310d27eed0b"},
+    {file = "cffi-1.15.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39d39875251ca8f612b6f33e6b1195af86d1b3e60086068be9cc053aa4376e21"},
+    {file = "cffi-1.15.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:285d29981935eb726a4399badae8f0ffdff4f5050eaa6d0cfc3f64b857b77185"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3eb6971dcff08619f8d91607cfc726518b6fa2a9eba42856be181c6d0d9515fd"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:21157295583fe8943475029ed5abdcf71eb3911894724e360acff1d61c1d54bc"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5635bd9cb9731e6d4a1132a498dd34f764034a8ce60cef4f5319c0541159392f"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2012c72d854c2d03e45d06ae57f40d78e5770d252f195b93f581acf3ba44496e"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dd86c085fae2efd48ac91dd7ccffcfc0571387fe1193d33b6394db7ef31fe2a4"},
+    {file = "cffi-1.15.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:fa6693661a4c91757f4412306191b6dc88c1703f780c8234035eac011922bc01"},
+    {file = "cffi-1.15.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:59c0b02d0a6c384d453fece7566d1c7e6b7bae4fc5874ef2ef46d56776d61c9e"},
+    {file = "cffi-1.15.1-cp310-cp310-win32.whl", hash = "sha256:cba9d6b9a7d64d4bd46167096fc9d2f835e25d7e4c121fb2ddfc6528fb0413b2"},
+    {file = "cffi-1.15.1-cp310-cp310-win_amd64.whl", hash = "sha256:ce4bcc037df4fc5e3d184794f27bdaab018943698f4ca31630bc7f84a7b69c6d"},
+    {file = "cffi-1.15.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3d08afd128ddaa624a48cf2b859afef385b720bb4b43df214f85616922e6a5ac"},
+    {file = "cffi-1.15.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3799aecf2e17cf585d977b780ce79ff0dc9b78d799fc694221ce814c2c19db83"},
+    {file = "cffi-1.15.1-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a591fe9e525846e4d154205572a029f653ada1a78b93697f3b5a8f1f2bc055b9"},
+    {file = "cffi-1.15.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3548db281cd7d2561c9ad9984681c95f7b0e38881201e157833a2342c30d5e8c"},
+    {file = "cffi-1.15.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:91fc98adde3d7881af9b59ed0294046f3806221863722ba7d8d120c575314325"},
+    {file = "cffi-1.15.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:94411f22c3985acaec6f83c6df553f2dbe17b698cc7f8ae751ff2237d96b9e3c"},
+    {file = "cffi-1.15.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:03425bdae262c76aad70202debd780501fabeaca237cdfddc008987c0e0f59ef"},
+    {file = "cffi-1.15.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:cc4d65aeeaa04136a12677d3dd0b1c0c94dc43abac5860ab33cceb42b801c1e8"},
+    {file = "cffi-1.15.1-cp311-cp311-win32.whl", hash = "sha256:a0f100c8912c114ff53e1202d0078b425bee3649ae34d7b070e9697f93c5d52d"},
+    {file = "cffi-1.15.1-cp311-cp311-win_amd64.whl", hash = "sha256:04ed324bda3cda42b9b695d51bb7d54b680b9719cfab04227cdd1e04e5de3104"},
+    {file = "cffi-1.15.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:50a74364d85fd319352182ef59c5c790484a336f6db772c1a9231f1c3ed0cbd7"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e263d77ee3dd201c3a142934a086a4450861778baaeeb45db4591ef65550b0a6"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cec7d9412a9102bdc577382c3929b337320c4c4c4849f2c5cdd14d7368c5562d"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4289fc34b2f5316fbb762d75362931e351941fa95fa18789191b33fc4cf9504a"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:173379135477dc8cac4bc58f45db08ab45d228b3363adb7af79436135d028405"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:6975a3fac6bc83c4a65c9f9fcab9e47019a11d3d2cf7f3c0d03431bf145a941e"},
+    {file = "cffi-1.15.1-cp36-cp36m-win32.whl", hash = "sha256:2470043b93ff09bf8fb1d46d1cb756ce6132c54826661a32d4e4d132e1977adf"},
+    {file = "cffi-1.15.1-cp36-cp36m-win_amd64.whl", hash = "sha256:30d78fbc8ebf9c92c9b7823ee18eb92f2e6ef79b45ac84db507f52fbe3ec4497"},
+    {file = "cffi-1.15.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:198caafb44239b60e252492445da556afafc7d1e3ab7a1fb3f0584ef6d742375"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5ef34d190326c3b1f822a5b7a45f6c4535e2f47ed06fec77d3d799c450b2651e"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8102eaf27e1e448db915d08afa8b41d6c7ca7a04b7d73af6514df10a3e74bd82"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5df2768244d19ab7f60546d0c7c63ce1581f7af8b5de3eb3004b9b6fc8a9f84b"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a8c4917bd7ad33e8eb21e9a5bbba979b49d9a97acb3a803092cbc1133e20343c"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0e2642fe3142e4cc4af0799748233ad6da94c62a8bec3a6648bf8ee68b1c7426"},
+    {file = "cffi-1.15.1-cp37-cp37m-win32.whl", hash = "sha256:e229a521186c75c8ad9490854fd8bbdd9a0c9aa3a524326b55be83b54d4e0ad9"},
+    {file = "cffi-1.15.1-cp37-cp37m-win_amd64.whl", hash = "sha256:a0b71b1b8fbf2b96e41c4d990244165e2c9be83d54962a9a1d118fd8657d2045"},
+    {file = "cffi-1.15.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:320dab6e7cb2eacdf0e658569d2575c4dad258c0fcc794f46215e1e39f90f2c3"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1e74c6b51a9ed6589199c787bf5f9875612ca4a8a0785fb2d4a84429badaf22a"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a5c84c68147988265e60416b57fc83425a78058853509c1b0629c180094904a5"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b926aa83d1edb5aa5b427b4053dc420ec295a08e40911296b9eb1b6170f6cca"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:87c450779d0914f2861b8526e035c5e6da0a3199d8f1add1a665e1cbc6fc6d02"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4f2c9f67e9821cad2e5f480bc8d83b8742896f1242dba247911072d4fa94c192"},
+    {file = "cffi-1.15.1-cp38-cp38-win32.whl", hash = "sha256:8b7ee99e510d7b66cdb6c593f21c043c248537a32e0bedf02e01e9553a172314"},
+    {file = "cffi-1.15.1-cp38-cp38-win_amd64.whl", hash = "sha256:00a9ed42e88df81ffae7a8ab6d9356b371399b91dbdf0c3cb1e84c03a13aceb5"},
+    {file = "cffi-1.15.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:54a2db7b78338edd780e7ef7f9f6c442500fb0d41a5a4ea24fff1c929d5af585"},
+    {file = "cffi-1.15.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:fcd131dd944808b5bdb38e6f5b53013c5aa4f334c5cad0c72742f6eba4b73db0"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7473e861101c9e72452f9bf8acb984947aa1661a7704553a9f6e4baa5ba64415"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6c9a799e985904922a4d207a94eae35c78ebae90e128f0c4e521ce339396be9d"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3bcde07039e586f91b45c88f8583ea7cf7a0770df3a1649627bf598332cb6984"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33ab79603146aace82c2427da5ca6e58f2b3f2fb5da893ceac0c42218a40be35"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5d598b938678ebf3c67377cdd45e09d431369c3b1a5b331058c338e201f12b27"},
+    {file = "cffi-1.15.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:db0fbb9c62743ce59a9ff687eb5f4afbe77e5e8403d6697f7446e5f609976f76"},
+    {file = "cffi-1.15.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:98d85c6a2bef81588d9227dde12db8a7f47f639f4a17c9ae08e773aa9c697bf3"},
+    {file = "cffi-1.15.1-cp39-cp39-win32.whl", hash = "sha256:40f4774f5a9d4f5e344f31a32b5096977b5d48560c5592e2f3d2c4374bd543ee"},
+    {file = "cffi-1.15.1-cp39-cp39-win_amd64.whl", hash = "sha256:70df4e3b545a17496c9b3f41f5115e69a4f2e77e94e1d2a8e1070bc0c38c8a3c"},
+    {file = "cffi-1.15.1.tar.gz", hash = "sha256:d400bfb9a37b1351253cb402671cea7e89bdecc294e8016a707f6d1d8ac934f9"},
 ]
 
-[[package]]
-name = "chardet"
-version = "5.1.0"
-description = "Universal encoding detector for Python 3"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "chardet-5.1.0-py3-none-any.whl", hash = "sha256:362777fb014af596ad31334fde1e8c327dfdb076e1960d1694662d46a6917ab9"},
-    {file = "chardet-5.1.0.tar.gz", hash = "sha256:0d62712b956bc154f85fb0a266e2a3c5913c2967e00348701b32411d6def31e5"},
-]
+[package.dependencies]
+pycparser = "*"
 
 [[package]]
 name = "charset-normalizer"
@@ -282,6 +357,114 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "comm"
+version = "0.1.2"
+description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
+category = "dev"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "comm-0.1.2-py3-none-any.whl", hash = "sha256:9f3abf3515112fa7c55a42a6a5ab358735c9dccc8b5910a9d8e3ef5998130666"},
+    {file = "comm-0.1.2.tar.gz", hash = "sha256:3e2f5826578e683999b93716285b3b1f344f157bf75fa9ce0a797564e742f062"},
+]
+
+[package.dependencies]
+traitlets = ">=5.3"
+
+[package.extras]
+test = ["pytest"]
+
+[[package]]
+name = "contourpy"
+version = "1.0.7"
+description = "Python library for calculating contours of 2D quadrilateral grids"
+category = "dev"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "contourpy-1.0.7-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:95c3acddf921944f241b6773b767f1cbce71d03307270e2d769fd584d5d1092d"},
+    {file = "contourpy-1.0.7-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:fc1464c97579da9f3ab16763c32e5c5d5bb5fa1ec7ce509a4ca6108b61b84fab"},
+    {file = "contourpy-1.0.7-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8acf74b5d383414401926c1598ed77825cd530ac7b463ebc2e4f46638f56cce6"},
+    {file = "contourpy-1.0.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1c71fdd8f1c0f84ffd58fca37d00ca4ebaa9e502fb49825484da075ac0b0b803"},
+    {file = "contourpy-1.0.7-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f99e9486bf1bb979d95d5cffed40689cb595abb2b841f2991fc894b3452290e8"},
+    {file = "contourpy-1.0.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:87f4d8941a9564cda3f7fa6a6cd9b32ec575830780677932abdec7bcb61717b0"},
+    {file = "contourpy-1.0.7-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:9e20e5a1908e18aaa60d9077a6d8753090e3f85ca25da6e25d30dc0a9e84c2c6"},
+    {file = "contourpy-1.0.7-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:a877ada905f7d69b2a31796c4b66e31a8068b37aa9b78832d41c82fc3e056ddd"},
+    {file = "contourpy-1.0.7-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6381fa66866b0ea35e15d197fc06ac3840a9b2643a6475c8fff267db8b9f1e69"},
+    {file = "contourpy-1.0.7-cp310-cp310-win32.whl", hash = "sha256:3c184ad2433635f216645fdf0493011a4667e8d46b34082f5a3de702b6ec42e3"},
+    {file = "contourpy-1.0.7-cp310-cp310-win_amd64.whl", hash = "sha256:3caea6365b13119626ee996711ab63e0c9d7496f65641f4459c60a009a1f3e80"},
+    {file = "contourpy-1.0.7-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:ed33433fc3820263a6368e532f19ddb4c5990855e4886088ad84fd7c4e561c71"},
+    {file = "contourpy-1.0.7-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:38e2e577f0f092b8e6774459317c05a69935a1755ecfb621c0a98f0e3c09c9a5"},
+    {file = "contourpy-1.0.7-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ae90d5a8590e5310c32a7630b4b8618cef7563cebf649011da80874d0aa8f414"},
+    {file = "contourpy-1.0.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:130230b7e49825c98edf0b428b7aa1125503d91732735ef897786fe5452b1ec2"},
+    {file = "contourpy-1.0.7-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:58569c491e7f7e874f11519ef46737cea1d6eda1b514e4eb5ac7dab6aa864d02"},
+    {file = "contourpy-1.0.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:54d43960d809c4c12508a60b66cb936e7ed57d51fb5e30b513934a4a23874fae"},
+    {file = "contourpy-1.0.7-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:152fd8f730c31fd67fe0ffebe1df38ab6a669403da93df218801a893645c6ccc"},
+    {file = "contourpy-1.0.7-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:9056c5310eb1daa33fc234ef39ebfb8c8e2533f088bbf0bc7350f70a29bde1ac"},
+    {file = "contourpy-1.0.7-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:a9d7587d2fdc820cc9177139b56795c39fb8560f540bba9ceea215f1f66e1566"},
+    {file = "contourpy-1.0.7-cp311-cp311-win32.whl", hash = "sha256:4ee3ee247f795a69e53cd91d927146fb16c4e803c7ac86c84104940c7d2cabf0"},
+    {file = "contourpy-1.0.7-cp311-cp311-win_amd64.whl", hash = "sha256:5caeacc68642e5f19d707471890f037a13007feba8427eb7f2a60811a1fc1350"},
+    {file = "contourpy-1.0.7-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:fd7dc0e6812b799a34f6d12fcb1000539098c249c8da54f3566c6a6461d0dbad"},
+    {file = "contourpy-1.0.7-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:0f9d350b639db6c2c233d92c7f213d94d2e444d8e8fc5ca44c9706cf72193772"},
+    {file = "contourpy-1.0.7-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:e96a08b62bb8de960d3a6afbc5ed8421bf1a2d9c85cc4ea73f4bc81b4910500f"},
+    {file = "contourpy-1.0.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:031154ed61f7328ad7f97662e48660a150ef84ee1bc8876b6472af88bf5a9b98"},
+    {file = "contourpy-1.0.7-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2e9ebb4425fc1b658e13bace354c48a933b842d53c458f02c86f371cecbedecc"},
+    {file = "contourpy-1.0.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:efb8f6d08ca7998cf59eaf50c9d60717f29a1a0a09caa46460d33b2924839dbd"},
+    {file = "contourpy-1.0.7-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:6c180d89a28787e4b73b07e9b0e2dac7741261dbdca95f2b489c4f8f887dd810"},
+    {file = "contourpy-1.0.7-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:b8d587cc39057d0afd4166083d289bdeff221ac6d3ee5046aef2d480dc4b503c"},
+    {file = "contourpy-1.0.7-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:769eef00437edf115e24d87f8926955f00f7704bede656ce605097584f9966dc"},
+    {file = "contourpy-1.0.7-cp38-cp38-win32.whl", hash = "sha256:62398c80ef57589bdbe1eb8537127321c1abcfdf8c5f14f479dbbe27d0322e66"},
+    {file = "contourpy-1.0.7-cp38-cp38-win_amd64.whl", hash = "sha256:57119b0116e3f408acbdccf9eb6ef19d7fe7baf0d1e9aaa5381489bc1aa56556"},
+    {file = "contourpy-1.0.7-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:30676ca45084ee61e9c3da589042c24a57592e375d4b138bd84d8709893a1ba4"},
+    {file = "contourpy-1.0.7-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3e927b3868bd1e12acee7cc8f3747d815b4ab3e445a28d2e5373a7f4a6e76ba1"},
+    {file = "contourpy-1.0.7-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:366a0cf0fc079af5204801786ad7a1c007714ee3909e364dbac1729f5b0849e5"},
+    {file = "contourpy-1.0.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:89ba9bb365446a22411f0673abf6ee1fea3b2cf47b37533b970904880ceb72f3"},
+    {file = "contourpy-1.0.7-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:71b0bf0c30d432278793d2141362ac853859e87de0a7dee24a1cea35231f0d50"},
+    {file = "contourpy-1.0.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e7281244c99fd7c6f27c1c6bfafba878517b0b62925a09b586d88ce750a016d2"},
+    {file = "contourpy-1.0.7-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b6d0f9e1d39dbfb3977f9dd79f156c86eb03e57a7face96f199e02b18e58d32a"},
+    {file = "contourpy-1.0.7-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:7f6979d20ee5693a1057ab53e043adffa1e7418d734c1532e2d9e915b08d8ec2"},
+    {file = "contourpy-1.0.7-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:5dd34c1ae752515318224cba7fc62b53130c45ac6a1040c8b7c1a223c46e8967"},
+    {file = "contourpy-1.0.7-cp39-cp39-win32.whl", hash = "sha256:c5210e5d5117e9aec8c47d9156d1d3835570dd909a899171b9535cb4a3f32693"},
+    {file = "contourpy-1.0.7-cp39-cp39-win_amd64.whl", hash = "sha256:60835badb5ed5f4e194a6f21c09283dd6e007664a86101431bf870d9e86266c4"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:ce41676b3d0dd16dbcfabcc1dc46090aaf4688fd6e819ef343dbda5a57ef0161"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5a011cf354107b47c58ea932d13b04d93c6d1d69b8b6dce885e642531f847566"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:31a55dccc8426e71817e3fe09b37d6d48ae40aae4ecbc8c7ad59d6893569c436"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:69f8ff4db108815addd900a74df665e135dbbd6547a8a69333a68e1f6e368ac2"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:efe99298ba37e37787f6a2ea868265465410822f7bea163edcc1bd3903354ea9"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:a1e97b86f73715e8670ef45292d7cc033548266f07d54e2183ecb3c87598888f"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cc331c13902d0f50845099434cd936d49d7a2ca76cb654b39691974cb1e4812d"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:24847601071f740837aefb730e01bd169fbcaa610209779a78db7ebb6e6a7051"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:abf298af1e7ad44eeb93501e40eb5a67abbf93b5d90e468d01fc0c4451971afa"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:64757f6460fc55d7e16ed4f1de193f362104285c667c112b50a804d482777edd"},
+    {file = "contourpy-1.0.7.tar.gz", hash = "sha256:d8165a088d31798b59e91117d1f5fc3df8168d8b48c4acc10fc0df0d0bdbcc5e"},
+]
+
+[package.dependencies]
+numpy = ">=1.16"
+
+[package.extras]
+bokeh = ["bokeh", "chromedriver", "selenium"]
+docs = ["furo", "sphinx-copybutton"]
+mypy = ["contourpy[bokeh]", "docutils-stubs", "mypy (==0.991)", "types-Pillow"]
+test = ["Pillow", "matplotlib", "pytest"]
+test-no-images = ["pytest"]
+
+[[package]]
+name = "covdefaults"
+version = "2.2.2"
+description = "A coverage plugin to provide sensible default settings"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "covdefaults-2.2.2-py2.py3-none-any.whl", hash = "sha256:10c193cbf290675961a09166d7cdea8a783655e04009f5493d50685fe6ec82f3"},
+    {file = "covdefaults-2.2.2.tar.gz", hash = "sha256:e543862ee0347769b47b27fa586d690e6b91587a3dcaaf8552fcfb1fac03d061"},
+]
+
+[package.dependencies]
+coverage = ">=6.0.2"
+
 [[package]]
 name = "coverage"
 version = "7.2.1"
@@ -349,6 +532,18 @@ tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.1
 [package.extras]
 toml = ["tomli"]
 
+[[package]]
+name = "cycler"
+version = "0.11.0"
+description = "Composable style cycles"
+category = "dev"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "cycler-0.11.0-py3-none-any.whl", hash = "sha256:3a27e95f763a428a739d2add979fa7494c912a32c17c4c38c4d5f082cad165a3"},
+    {file = "cycler-0.11.0.tar.gz", hash = "sha256:9c87405839a19696e837b3b818fed3f5f69f16f1eec1a1ad77e043dcea9c772f"},
+]
+
 [[package]]
 name = "dataretrieval"
 version = "1.0.2"
@@ -370,67 +565,61 @@ doc = ["sphinx"]
 test = ["pytest (>5.0.0)", "pytest-cov[all]"]
 
 [[package]]
-name = "deprecated"
-version = "1.2.13"
-description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
-category = "main"
+name = "debugpy"
+version = "1.6.6"
+description = "An implementation of the Debug Adapter Protocol for Python"
+category = "dev"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+python-versions = ">=3.7"
 files = [
-    {file = "Deprecated-1.2.13-py2.py3-none-any.whl", hash = "sha256:64756e3e14c8c5eea9795d93c524551432a0be75629f8f29e67ab8caf076c76d"},
-    {file = "Deprecated-1.2.13.tar.gz", hash = "sha256:43ac5335da90c31c24ba028af536a91d41d53f9e6901ddb021bcc572ce44e38d"},
+    {file = "debugpy-1.6.6-cp310-cp310-macosx_11_0_x86_64.whl", hash = "sha256:0ea1011e94416e90fb3598cc3ef5e08b0a4dd6ce6b9b33ccd436c1dffc8cd664"},
+    {file = "debugpy-1.6.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dff595686178b0e75580c24d316aa45a8f4d56e2418063865c114eef651a982e"},
+    {file = "debugpy-1.6.6-cp310-cp310-win32.whl", hash = "sha256:87755e173fcf2ec45f584bb9d61aa7686bb665d861b81faa366d59808bbd3494"},
+    {file = "debugpy-1.6.6-cp310-cp310-win_amd64.whl", hash = "sha256:72687b62a54d9d9e3fb85e7a37ea67f0e803aaa31be700e61d2f3742a5683917"},
+    {file = "debugpy-1.6.6-cp37-cp37m-macosx_10_15_x86_64.whl", hash = "sha256:78739f77c58048ec006e2b3eb2e0cd5a06d5f48c915e2fc7911a337354508110"},
+    {file = "debugpy-1.6.6-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:23c29e40e39ad7d869d408ded414f6d46d82f8a93b5857ac3ac1e915893139ca"},
+    {file = "debugpy-1.6.6-cp37-cp37m-win32.whl", hash = "sha256:7aa7e103610e5867d19a7d069e02e72eb2b3045b124d051cfd1538f1d8832d1b"},
+    {file = "debugpy-1.6.6-cp37-cp37m-win_amd64.whl", hash = "sha256:f6383c29e796203a0bba74a250615ad262c4279d398e89d895a69d3069498305"},
+    {file = "debugpy-1.6.6-cp38-cp38-macosx_10_15_x86_64.whl", hash = "sha256:23363e6d2a04d726bbc1400bd4e9898d54419b36b2cdf7020e3e215e1dcd0f8e"},
+    {file = "debugpy-1.6.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9b5d1b13d7c7bf5d7cf700e33c0b8ddb7baf030fcf502f76fc061ddd9405d16c"},
+    {file = "debugpy-1.6.6-cp38-cp38-win32.whl", hash = "sha256:70ab53918fd907a3ade01909b3ed783287ede362c80c75f41e79596d5ccacd32"},
+    {file = "debugpy-1.6.6-cp38-cp38-win_amd64.whl", hash = "sha256:c05349890804d846eca32ce0623ab66c06f8800db881af7a876dc073ac1c2225"},
+    {file = "debugpy-1.6.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a771739902b1ae22a120dbbb6bd91b2cae6696c0e318b5007c5348519a4211c6"},
+    {file = "debugpy-1.6.6-cp39-cp39-win32.whl", hash = "sha256:549ae0cb2d34fc09d1675f9b01942499751d174381b6082279cf19cdb3c47cbe"},
+    {file = "debugpy-1.6.6-cp39-cp39-win_amd64.whl", hash = "sha256:de4a045fbf388e120bb6ec66501458d3134f4729faed26ff95de52a754abddb1"},
+    {file = "debugpy-1.6.6-py2.py3-none-any.whl", hash = "sha256:be596b44448aac14eb3614248c91586e2bc1728e020e82ef3197189aae556115"},
+    {file = "debugpy-1.6.6.zip", hash = "sha256:b9c2130e1c632540fbf9c2c88341493797ddf58016e7cba02e311de9b0a96b67"},
 ]
 
-[package.dependencies]
-wrapt = ">=1.10,<2"
-
-[package.extras]
-dev = ["PyTest", "PyTest (<5)", "PyTest-Cov", "PyTest-Cov (<2.6)", "bump2version (<1)", "configparser (<5)", "importlib-metadata (<3)", "importlib-resources (<4)", "sphinx (<2)", "sphinxcontrib-websupport (<2)", "tox", "zipp (<2)"]
-
 [[package]]
-name = "deptry"
-version = "0.8.0"
-description = "A command line utility to check for obsolete, missing and transitive dependencies in a Python project."
+name = "decorator"
+version = "5.1.1"
+description = "Decorators for Humans"
 category = "dev"
 optional = false
-python-versions = ">=3.7,<4.0"
+python-versions = ">=3.5"
 files = [
-    {file = "deptry-0.8.0-py3-none-any.whl", hash = "sha256:12f161748907781a5f6e6931694b40db7af7e0aa4b7888334a677cd4670daf7a"},
-    {file = "deptry-0.8.0.tar.gz", hash = "sha256:b15a31d4bc2c074de834ba4207b2f03e49a4bea8cb73e14e7376a26431b9c606"},
+    {file = "decorator-5.1.1-py3-none-any.whl", hash = "sha256:b8c3f85900b9dc423225913c5aace94729fe1fa9763b38939a95226f02d37186"},
+    {file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"},
 ]
 
-[package.dependencies]
-chardet = ">=4.0.0"
-click = ">=8.0.0,<9.0.0"
-pathspec = ">=0.9.0"
-tomli = {version = ">=2.0.1,<3.0.0", markers = "python_version < \"3.11\""}
-
 [[package]]
-name = "dill"
-version = "0.3.6"
-description = "serialize all of python"
-category = "dev"
+name = "deprecated"
+version = "1.2.13"
+description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
+category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
-    {file = "dill-0.3.6-py3-none-any.whl", hash = "sha256:a07ffd2351b8c678dfc4a856a3005f8067aea51d6ba6c700796a4d9e280f39f0"},
-    {file = "dill-0.3.6.tar.gz", hash = "sha256:e5db55f3687856d8fbdab002ed78544e1c4559a130302693d839dfe8f93f2373"},
+    {file = "Deprecated-1.2.13-py2.py3-none-any.whl", hash = "sha256:64756e3e14c8c5eea9795d93c524551432a0be75629f8f29e67ab8caf076c76d"},
+    {file = "Deprecated-1.2.13.tar.gz", hash = "sha256:43ac5335da90c31c24ba028af536a91d41d53f9e6901ddb021bcc572ce44e38d"},
 ]
 
-[package.extras]
-graph = ["objgraph (>=1.7.2)"]
+[package.dependencies]
+wrapt = ">=1.10,<2"
 
-[[package]]
-name = "distlib"
-version = "0.3.6"
-description = "Distribution utilities"
-category = "dev"
-optional = false
-python-versions = "*"
-files = [
-    {file = "distlib-0.3.6-py2.py3-none-any.whl", hash = "sha256:f35c4b692542ca110de7ef0bea44d73981caeb34ca0b9b6b2e6d7790dda8f80e"},
-    {file = "distlib-0.3.6.tar.gz", hash = "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46"},
-]
+[package.extras]
+dev = ["PyTest", "PyTest (<5)", "PyTest-Cov", "PyTest-Cov (<2.6)", "bump2version (<1)", "configparser (<5)", "importlib-metadata (<3)", "importlib-resources (<4)", "sphinx (<2)", "sphinxcontrib-websupport (<2)", "tox", "zipp (<2)"]
 
 [[package]]
 name = "docutils"
@@ -444,18 +633,6 @@ files = [
     {file = "docutils-0.19.tar.gz", hash = "sha256:33995a6753c30b7f577febfc2c50411fec6aac7f7ffeb7c4cfe5991072dcf9e6"},
 ]
 
-[[package]]
-name = "dodgy"
-version = "0.2.1"
-description = "Dodgy: Searches for dodgy looking lines in Python code"
-category = "dev"
-optional = false
-python-versions = "*"
-files = [
-    {file = "dodgy-0.2.1-py3-none-any.whl", hash = "sha256:51f54c0fd886fa3854387f354b19f429d38c04f984f38bc572558b703c0542a6"},
-    {file = "dodgy-0.2.1.tar.gz", hash = "sha256:28323cbfc9352139fdd3d316fa17f325cc0e9ac74438cbba51d70f9b48f86c3a"},
-]
-
 [[package]]
 name = "dunamai"
 version = "1.16.0"
@@ -518,20 +695,19 @@ files = [
 testing = ["pre-commit"]
 
 [[package]]
-name = "filelock"
-version = "3.9.0"
-description = "A platform independent file lock."
+name = "executing"
+version = "1.2.0"
+description = "Get the currently executing AST node of a frame, and other information"
 category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = "*"
 files = [
-    {file = "filelock-3.9.0-py3-none-any.whl", hash = "sha256:f58d535af89bb9ad5cd4df046f741f8553a418c01a7856bf0d173bbc9f6bd16d"},
-    {file = "filelock-3.9.0.tar.gz", hash = "sha256:7b319f24340b51f55a2bf7a12ac0755a9b03e718311dac567a0f4f7fabd2f5de"},
+    {file = "executing-1.2.0-py2.py3-none-any.whl", hash = "sha256:0314a69e37426e3608aada02473b4161d4caf5a4b244d1d0c48072b8fee7bacc"},
+    {file = "executing-1.2.0.tar.gz", hash = "sha256:19da64c18d2d851112f09c287f8d3dbbdf725ab0e569077efb6cdcbd3497c107"},
 ]
 
 [package.extras]
-docs = ["furo (>=2022.12.7)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"]
-testing = ["covdefaults (>=2.2.2)", "coverage (>=7.0.1)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-timeout (>=2.1)"]
+tests = ["asttokens", "littleutils", "pytest", "rich"]
 
 [[package]]
 name = "fiona"
@@ -579,36 +755,30 @@ s3 = ["boto3 (>=1.3.1)"]
 test = ["Fiona[s3]", "pytest (>=7)", "pytest-cov", "pytz"]
 
 [[package]]
-name = "flake8"
-version = "2.3.0"
-description = "the modular source code checker: pep8, pyflakes and co"
+name = "fonttools"
+version = "4.38.0"
+description = "Tools to manipulate font files"
 category = "dev"
 optional = false
-python-versions = "*"
-files = [
-    {file = "flake8-2.3.0-py2.py3-none-any.whl", hash = "sha256:c99cc9716d6655d9c8bcb1e77632b8615bf0abd282d7abd9f5c2148cad7fc669"},
-    {file = "flake8-2.3.0.tar.gz", hash = "sha256:5ee1a43ccd0716d6061521eec6937c983efa027793013e572712c4da55c7c83e"},
-]
-
-[package.dependencies]
-mccabe = ">=0.2.1"
-pep8 = ">=1.5.7"
-pyflakes = ">=0.8.1"
-
-[[package]]
-name = "flake8-polyfill"
-version = "1.0.2"
-description = "Polyfill package for Flake8 plugins"
-category = "dev"
-optional = false
-python-versions = "*"
+python-versions = ">=3.7"
 files = [
-    {file = "flake8-polyfill-1.0.2.tar.gz", hash = "sha256:e44b087597f6da52ec6393a709e7108b2905317d0c0b744cdca6208e670d8eda"},
-    {file = "flake8_polyfill-1.0.2-py2.py3-none-any.whl", hash = "sha256:12be6a34ee3ab795b19ca73505e7b55826d5f6ad7230d31b18e106400169b9e9"},
+    {file = "fonttools-4.38.0-py3-none-any.whl", hash = "sha256:820466f43c8be8c3009aef8b87e785014133508f0de64ec469e4efb643ae54fb"},
+    {file = "fonttools-4.38.0.zip", hash = "sha256:2bb244009f9bf3fa100fc3ead6aeb99febe5985fa20afbfbaa2f8946c2fbdaf1"},
 ]
 
-[package.dependencies]
-flake8 = "*"
+[package.extras]
+all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=14.0.0)", "xattr", "zopfli (>=0.1.4)"]
+graphite = ["lz4 (>=1.7.4.2)"]
+interpolatable = ["munkres", "scipy"]
+lxml = ["lxml (>=4.0,<5)"]
+pathops = ["skia-pathops (>=0.5.0)"]
+plot = ["matplotlib"]
+repacker = ["uharfbuzz (>=0.23.0)"]
+symfont = ["sympy"]
+type1 = ["xattr"]
+ufo = ["fs (>=2.2.0,<3)"]
+unicode = ["unicodedata2 (>=14.0.0)"]
+woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
 
 [[package]]
 name = "geopandas"
@@ -651,21 +821,6 @@ chardet = ["chardet (>=2.2)"]
 genshi = ["genshi"]
 lxml = ["lxml"]
 
-[[package]]
-name = "identify"
-version = "2.5.18"
-description = "File identification library for Python"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "identify-2.5.18-py2.py3-none-any.whl", hash = "sha256:93aac7ecf2f6abf879b8f29a8002d3c6de7086b8c28d88e1ad15045a15ab63f9"},
-    {file = "identify-2.5.18.tar.gz", hash = "sha256:89e144fa560cc4cffb6ef2ab5e9fb18ed9f9b3cb054384bab4b95c12f6c309fe"},
-]
-
-[package.extras]
-license = ["ukkonen"]
-
 [[package]]
 name = "idna"
 version = "3.4"
@@ -710,6 +865,25 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker
 perf = ["ipython"]
 testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
 
+[[package]]
+name = "importlib-resources"
+version = "5.12.0"
+description = "Read resources from Python packages"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_resources-5.12.0-py3-none-any.whl", hash = "sha256:7b1deeebbf351c7578e09bf2f63fa2ce8b5ffec296e0d349139d43cca061a81a"},
+    {file = "importlib_resources-5.12.0.tar.gz", hash = "sha256:4be82589bf5c1d7999aedf2a45159d10cb3ca4f19b2271f8792bc8e6da7b22f6"},
+]
+
+[package.dependencies]
+zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -723,22 +897,97 @@ files = [
 ]
 
 [[package]]
-name = "isort"
-version = "5.12.0"
-description = "A Python utility / library to sort Python imports."
+name = "ipykernel"
+version = "6.21.2"
+description = "IPython Kernel for Jupyter"
+category = "dev"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "ipykernel-6.21.2-py3-none-any.whl", hash = "sha256:430d00549b6aaf49bd0f5393150691edb1815afa62d457ee6b1a66b25cb17874"},
+    {file = "ipykernel-6.21.2.tar.gz", hash = "sha256:6e9213484e4ce1fb14267ee435e18f23cc3a0634e635b9fb4ed4677b84e0fdf8"},
+]
+
+[package.dependencies]
+appnope = {version = "*", markers = "platform_system == \"Darwin\""}
+comm = ">=0.1.1"
+debugpy = ">=1.6.5"
+ipython = ">=7.23.1"
+jupyter-client = ">=6.1.12"
+jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+matplotlib-inline = ">=0.1"
+nest-asyncio = "*"
+packaging = "*"
+psutil = "*"
+pyzmq = ">=20"
+tornado = ">=6.1"
+traitlets = ">=5.4.0"
+
+[package.extras]
+cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
+pyqt5 = ["pyqt5"]
+pyside6 = ["pyside6"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"]
+
+[[package]]
+name = "ipython"
+version = "8.11.0"
+description = "IPython: Productive Interactive Computing"
 category = "dev"
 optional = false
-python-versions = ">=3.8.0"
+python-versions = ">=3.8"
 files = [
-    {file = "isort-5.12.0-py3-none-any.whl", hash = "sha256:f84c2818376e66cf843d497486ea8fed8700b340f308f076c6fb1229dff318b6"},
-    {file = "isort-5.12.0.tar.gz", hash = "sha256:8bef7dde241278824a6d83f44a544709b065191b95b6e50894bdc722fcba0504"},
+    {file = "ipython-8.11.0-py3-none-any.whl", hash = "sha256:5b54478e459155a326bf5f42ee4f29df76258c0279c36f21d71ddb560f88b156"},
+    {file = "ipython-8.11.0.tar.gz", hash = "sha256:735cede4099dbc903ee540307b9171fbfef4aa75cfcacc5a273b2cda2f02be04"},
 ]
 
+[package.dependencies]
+appnope = {version = "*", markers = "sys_platform == \"darwin\""}
+backcall = "*"
+colorama = {version = "*", markers = "sys_platform == \"win32\""}
+decorator = "*"
+jedi = ">=0.16"
+matplotlib-inline = "*"
+pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
+pickleshare = "*"
+prompt-toolkit = ">=3.0.30,<3.0.37 || >3.0.37,<3.1.0"
+pygments = ">=2.4.0"
+stack-data = "*"
+traitlets = ">=5"
+
 [package.extras]
-colors = ["colorama (>=0.4.3)"]
-pipfile-deprecated-finder = ["pip-shims (>=0.5.2)", "pipreqs", "requirementslib"]
-plugins = ["setuptools"]
-requirements-deprecated-finder = ["pip-api", "pipreqs"]
+all = ["black", "curio", "docrepr", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.21)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
+black = ["black"]
+doc = ["docrepr", "ipykernel", "matplotlib", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
+kernel = ["ipykernel"]
+nbconvert = ["nbconvert"]
+nbformat = ["nbformat"]
+notebook = ["ipywidgets", "notebook"]
+parallel = ["ipyparallel"]
+qtconsole = ["qtconsole"]
+test = ["pytest (<7.1)", "pytest-asyncio", "testpath"]
+test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.21)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"]
+
+[[package]]
+name = "jedi"
+version = "0.18.2"
+description = "An autocompletion tool for Python that can be used for text editors."
+category = "dev"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "jedi-0.18.2-py2.py3-none-any.whl", hash = "sha256:203c1fd9d969ab8f2119ec0a3342e0b49910045abe6af0a3ae83a5764d54639e"},
+    {file = "jedi-0.18.2.tar.gz", hash = "sha256:bae794c30d07f6d910d32a7048af09b5a39ed740918da923c6b780790ebac612"},
+]
+
+[package.dependencies]
+parso = ">=0.8.0,<0.9.0"
+
+[package.extras]
+docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"]
+qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
+testing = ["Django (<3.1)", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 
 [[package]]
 name = "jinja2"
@@ -759,49 +1008,126 @@ MarkupSafe = ">=2.0"
 i18n = ["Babel (>=2.7)"]
 
 [[package]]
-name = "lazy-object-proxy"
-version = "1.9.0"
-description = "A fast and thorough lazy object proxy."
+name = "jupyter-client"
+version = "8.0.3"
+description = "Jupyter protocol implementation and client libraries"
+category = "dev"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_client-8.0.3-py3-none-any.whl", hash = "sha256:be48ac6bd659cbbddb7a674cf06b3b8afbf53f228253cf58bde604c03bd487b0"},
+    {file = "jupyter_client-8.0.3.tar.gz", hash = "sha256:ed65498bea6d876ef9d8da3e0db3dd33c5d129f5b2645f56ae03993782966bd0"},
+]
+
+[package.dependencies]
+importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
+jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+python-dateutil = ">=2.8.2"
+pyzmq = ">=23.0"
+tornado = ">=6.2"
+traitlets = ">=5.3"
+
+[package.extras]
+docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["codecov", "coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
+
+[[package]]
+name = "jupyter-core"
+version = "5.2.0"
+description = "Jupyter core package. A base package on which Jupyter projects rely."
+category = "dev"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_core-5.2.0-py3-none-any.whl", hash = "sha256:4bdc2928c37f6917130c667d8b8708f20aee539d8283c6be72aabd2a4b4c83b0"},
+    {file = "jupyter_core-5.2.0.tar.gz", hash = "sha256:1407cdb4c79ee467696c04b76633fc1884015fa109323365a6372c8e890cc83f"},
+]
+
+[package.dependencies]
+platformdirs = ">=2.5"
+pywin32 = {version = ">=1.0", markers = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\""}
+traitlets = ">=5.3"
+
+[package.extras]
+docs = ["myst-parser", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"]
+test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"]
+
+[[package]]
+name = "kiwisolver"
+version = "1.4.4"
+description = "A fast implementation of the Cassowary constraint solver"
 category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "lazy-object-proxy-1.9.0.tar.gz", hash = "sha256:659fb5809fa4629b8a1ac5106f669cfc7bef26fbb389dda53b3e010d1ac4ebae"},
-    {file = "lazy_object_proxy-1.9.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b40387277b0ed2d0602b8293b94d7257e17d1479e257b4de114ea11a8cb7f2d7"},
-    {file = "lazy_object_proxy-1.9.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e8c6cfb338b133fbdbc5cfaa10fe3c6aeea827db80c978dbd13bc9dd8526b7d4"},
-    {file = "lazy_object_proxy-1.9.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:721532711daa7db0d8b779b0bb0318fa87af1c10d7fe5e52ef30f8eff254d0cd"},
-    {file = "lazy_object_proxy-1.9.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:66a3de4a3ec06cd8af3f61b8e1ec67614fbb7c995d02fa224813cb7afefee701"},
-    {file = "lazy_object_proxy-1.9.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:1aa3de4088c89a1b69f8ec0dcc169aa725b0ff017899ac568fe44ddc1396df46"},
-    {file = "lazy_object_proxy-1.9.0-cp310-cp310-win32.whl", hash = "sha256:f0705c376533ed2a9e5e97aacdbfe04cecd71e0aa84c7c0595d02ef93b6e4455"},
-    {file = "lazy_object_proxy-1.9.0-cp310-cp310-win_amd64.whl", hash = "sha256:ea806fd4c37bf7e7ad82537b0757999264d5f70c45468447bb2b91afdbe73a6e"},
-    {file = "lazy_object_proxy-1.9.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:946d27deaff6cf8452ed0dba83ba38839a87f4f7a9732e8f9fd4107b21e6ff07"},
-    {file = "lazy_object_proxy-1.9.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:79a31b086e7e68b24b99b23d57723ef7e2c6d81ed21007b6281ebcd1688acb0a"},
-    {file = "lazy_object_proxy-1.9.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f699ac1c768270c9e384e4cbd268d6e67aebcfae6cd623b4d7c3bfde5a35db59"},
-    {file = "lazy_object_proxy-1.9.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:bfb38f9ffb53b942f2b5954e0f610f1e721ccebe9cce9025a38c8ccf4a5183a4"},
-    {file = "lazy_object_proxy-1.9.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:189bbd5d41ae7a498397287c408617fe5c48633e7755287b21d741f7db2706a9"},
-    {file = "lazy_object_proxy-1.9.0-cp311-cp311-win32.whl", hash = "sha256:81fc4d08b062b535d95c9ea70dbe8a335c45c04029878e62d744bdced5141586"},
-    {file = "lazy_object_proxy-1.9.0-cp311-cp311-win_amd64.whl", hash = "sha256:f2457189d8257dd41ae9b434ba33298aec198e30adf2dcdaaa3a28b9994f6adb"},
-    {file = "lazy_object_proxy-1.9.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:d9e25ef10a39e8afe59a5c348a4dbf29b4868ab76269f81ce1674494e2565a6e"},
-    {file = "lazy_object_proxy-1.9.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cbf9b082426036e19c6924a9ce90c740a9861e2bdc27a4834fd0a910742ac1e8"},
-    {file = "lazy_object_proxy-1.9.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f5fa4a61ce2438267163891961cfd5e32ec97a2c444e5b842d574251ade27d2"},
-    {file = "lazy_object_proxy-1.9.0-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:8fa02eaab317b1e9e03f69aab1f91e120e7899b392c4fc19807a8278a07a97e8"},
-    {file = "lazy_object_proxy-1.9.0-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:e7c21c95cae3c05c14aafffe2865bbd5e377cfc1348c4f7751d9dc9a48ca4bda"},
-    {file = "lazy_object_proxy-1.9.0-cp37-cp37m-win32.whl", hash = "sha256:f12ad7126ae0c98d601a7ee504c1122bcef553d1d5e0c3bfa77b16b3968d2734"},
-    {file = "lazy_object_proxy-1.9.0-cp37-cp37m-win_amd64.whl", hash = "sha256:edd20c5a55acb67c7ed471fa2b5fb66cb17f61430b7a6b9c3b4a1e40293b1671"},
-    {file = "lazy_object_proxy-1.9.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:2d0daa332786cf3bb49e10dc6a17a52f6a8f9601b4cf5c295a4f85854d61de63"},
-    {file = "lazy_object_proxy-1.9.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9cd077f3d04a58e83d04b20e334f678c2b0ff9879b9375ed107d5d07ff160171"},
-    {file = "lazy_object_proxy-1.9.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:660c94ea760b3ce47d1855a30984c78327500493d396eac4dfd8bd82041b22be"},
-    {file = "lazy_object_proxy-1.9.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:212774e4dfa851e74d393a2370871e174d7ff0ebc980907723bb67d25c8a7c30"},
-    {file = "lazy_object_proxy-1.9.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:f0117049dd1d5635bbff65444496c90e0baa48ea405125c088e93d9cf4525b11"},
-    {file = "lazy_object_proxy-1.9.0-cp38-cp38-win32.whl", hash = "sha256:0a891e4e41b54fd5b8313b96399f8b0e173bbbfc03c7631f01efbe29bb0bcf82"},
-    {file = "lazy_object_proxy-1.9.0-cp38-cp38-win_amd64.whl", hash = "sha256:9990d8e71b9f6488e91ad25f322898c136b008d87bf852ff65391b004da5e17b"},
-    {file = "lazy_object_proxy-1.9.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9e7551208b2aded9c1447453ee366f1c4070602b3d932ace044715d89666899b"},
-    {file = "lazy_object_proxy-1.9.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5f83ac4d83ef0ab017683d715ed356e30dd48a93746309c8f3517e1287523ef4"},
-    {file = "lazy_object_proxy-1.9.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7322c3d6f1766d4ef1e51a465f47955f1e8123caee67dd641e67d539a534d006"},
-    {file = "lazy_object_proxy-1.9.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:18b78ec83edbbeb69efdc0e9c1cb41a3b1b1ed11ddd8ded602464c3fc6020494"},
-    {file = "lazy_object_proxy-1.9.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:09763491ce220c0299688940f8dc2c5d05fd1f45af1e42e636b2e8b2303e4382"},
-    {file = "lazy_object_proxy-1.9.0-cp39-cp39-win32.whl", hash = "sha256:9090d8e53235aa280fc9239a86ae3ea8ac58eff66a705fa6aa2ec4968b95c821"},
-    {file = "lazy_object_proxy-1.9.0-cp39-cp39-win_amd64.whl", hash = "sha256:db1c1722726f47e10e0b5fdbf15ac3b8adb58c091d12b3ab713965795036985f"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:2f5e60fabb7343a836360c4f0919b8cd0d6dbf08ad2ca6b9cf90bf0c76a3c4f6"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:10ee06759482c78bdb864f4109886dff7b8a56529bc1609d4f1112b93fe6423c"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c79ebe8f3676a4c6630fd3f777f3cfecf9289666c84e775a67d1d358578dc2e3"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:abbe9fa13da955feb8202e215c4018f4bb57469b1b78c7a4c5c7b93001699938"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:7577c1987baa3adc4b3c62c33bd1118c3ef5c8ddef36f0f2c950ae0b199e100d"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f8ad8285b01b0d4695102546b342b493b3ccc6781fc28c8c6a1bb63e95d22f09"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8ed58b8acf29798b036d347791141767ccf65eee7f26bde03a71c944449e53de"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a68b62a02953b9841730db7797422f983935aeefceb1679f0fc85cbfbd311c32"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-win32.whl", hash = "sha256:e92a513161077b53447160b9bd8f522edfbed4bd9759e4c18ab05d7ef7e49408"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-win_amd64.whl", hash = "sha256:3fe20f63c9ecee44560d0e7f116b3a747a5d7203376abeea292ab3152334d004"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:e0ea21f66820452a3f5d1655f8704a60d66ba1191359b96541eaf457710a5fc6"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:bc9db8a3efb3e403e4ecc6cd9489ea2bac94244f80c78e27c31dcc00d2790ac2"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d5b61785a9ce44e5a4b880272baa7cf6c8f48a5180c3e81c59553ba0cb0821ca"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c2dbb44c3f7e6c4d3487b31037b1bdbf424d97687c1747ce4ff2895795c9bf69"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6295ecd49304dcf3bfbfa45d9a081c96509e95f4b9d0eb7ee4ec0530c4a96514"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4bd472dbe5e136f96a4b18f295d159d7f26fd399136f5b17b08c4e5f498cd494"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bf7d9fce9bcc4752ca4a1b80aabd38f6d19009ea5cbda0e0856983cf6d0023f5"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:78d6601aed50c74e0ef02f4204da1816147a6d3fbdc8b3872d263338a9052c51"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:877272cf6b4b7e94c9614f9b10140e198d2186363728ed0f701c6eee1baec1da"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:db608a6757adabb32f1cfe6066e39b3706d8c3aa69bbc353a5b61edad36a5cb4"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:5853eb494c71e267912275e5586fe281444eb5e722de4e131cddf9d442615626"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:f0a1dbdb5ecbef0d34eb77e56fcb3e95bbd7e50835d9782a45df81cc46949750"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:283dffbf061a4ec60391d51e6155e372a1f7a4f5b15d59c8505339454f8989e4"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-win32.whl", hash = "sha256:d06adcfa62a4431d404c31216f0f8ac97397d799cd53800e9d3efc2fbb3cf14e"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-win_amd64.whl", hash = "sha256:e7da3fec7408813a7cebc9e4ec55afed2d0fd65c4754bc376bf03498d4e92686"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:62ac9cc684da4cf1778d07a89bf5f81b35834cb96ca523d3a7fb32509380cbf6"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:41dae968a94b1ef1897cb322b39360a0812661dba7c682aa45098eb8e193dbdf"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:02f79693ec433cb4b5f51694e8477ae83b3205768a6fb48ffba60549080e295b"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d0611a0a2a518464c05ddd5a3a1a0e856ccc10e67079bb17f265ad19ab3c7597"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:db5283d90da4174865d520e7366801a93777201e91e79bacbac6e6927cbceede"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:1041feb4cda8708ce73bb4dcb9ce1ccf49d553bf87c3954bdfa46f0c3f77252c"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-win32.whl", hash = "sha256:a553dadda40fef6bfa1456dc4be49b113aa92c2a9a9e8711e955618cd69622e3"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-win_amd64.whl", hash = "sha256:03baab2d6b4a54ddbb43bba1a3a2d1627e82d205c5cf8f4c924dc49284b87166"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:841293b17ad704d70c578f1f0013c890e219952169ce8a24ebc063eecf775454"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:f4f270de01dd3e129a72efad823da90cc4d6aafb64c410c9033aba70db9f1ff0"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:f9f39e2f049db33a908319cf46624a569b36983c7c78318e9726a4cb8923b26c"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c97528e64cb9ebeff9701e7938653a9951922f2a38bd847787d4a8e498cc83ae"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1d1573129aa0fd901076e2bfb4275a35f5b7aa60fbfb984499d661ec950320b0"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ad881edc7ccb9d65b0224f4e4d05a1e85cf62d73aab798943df6d48ab0cd79a1"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b428ef021242344340460fa4c9185d0b1f66fbdbfecc6c63eff4b7c29fad429d"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:2e407cb4bd5a13984a6c2c0fe1845e4e41e96f183e5e5cd4d77a857d9693494c"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-win32.whl", hash = "sha256:75facbe9606748f43428fc91a43edb46c7ff68889b91fa31f53b58894503a191"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-win_amd64.whl", hash = "sha256:5bce61af018b0cb2055e0e72e7d65290d822d3feee430b7b8203d8a855e78766"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:8c808594c88a025d4e322d5bb549282c93c8e1ba71b790f539567932722d7bd8"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f0a71d85ecdd570ded8ac3d1c0f480842f49a40beb423bb8014539a9f32a5897"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:b533558eae785e33e8c148a8d9921692a9fe5aa516efbdff8606e7d87b9d5824"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:efda5fc8cc1c61e4f639b8067d118e742b812c930f708e6667a5ce0d13499e29"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:7c43e1e1206cd421cd92e6b3280d4385d41d7166b3ed577ac20444b6995a445f"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bc8d3bd6c72b2dd9decf16ce70e20abcb3274ba01b4e1c96031e0c4067d1e7cd"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4ea39b0ccc4f5d803e3337dd46bcce60b702be4d86fd0b3d7531ef10fd99a1ac"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:968f44fdbf6dd757d12920d63b566eeb4d5b395fd2d00d29d7ef00a00582aac9"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-win32.whl", hash = "sha256:da7e547706e69e45d95e116e6939488d62174e033b763ab1496b4c29b76fabea"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-win_amd64.whl", hash = "sha256:ba59c92039ec0a66103b1d5fe588fa546373587a7d68f5c96f743c3396afc04b"},
+    {file = "kiwisolver-1.4.4-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:91672bacaa030f92fc2f43b620d7b337fd9a5af28b0d6ed3f77afc43c4a64b5a"},
+    {file = "kiwisolver-1.4.4-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:787518a6789009c159453da4d6b683f468ef7a65bbde796bcea803ccf191058d"},
+    {file = "kiwisolver-1.4.4-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:da152d8cdcab0e56e4f45eb08b9aea6455845ec83172092f09b0e077ece2cf7a"},
+    {file = "kiwisolver-1.4.4-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:ecb1fa0db7bf4cff9dac752abb19505a233c7f16684c5826d1f11ebd9472b871"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:28bc5b299f48150b5f822ce68624e445040595a4ac3d59251703779836eceff9"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:81e38381b782cc7e1e46c4e14cd997ee6040768101aefc8fa3c24a4cc58e98f8"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:2a66fdfb34e05b705620dd567f5a03f239a088d5a3f321e7b6ac3239d22aa286"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:872b8ca05c40d309ed13eb2e582cab0c5a05e81e987ab9c521bf05ad1d5cf5cb"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:70e7c2e7b750585569564e2e5ca9845acfaa5da56ac46df68414f29fea97be9f"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:9f85003f5dfa867e86d53fac6f7e6f30c045673fa27b603c397753bebadc3008"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2e307eb9bd99801f82789b44bb45e9f541961831c7311521b13a6c85afc09767"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b1792d939ec70abe76f5054d3f36ed5656021dcad1322d1cc996d4e54165cef9"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f6cb459eea32a4e2cf18ba5fcece2dbdf496384413bc1bae15583f19e567f3b2"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:36dafec3d6d6088d34e2de6b85f9d8e2324eb734162fba59d2ba9ed7a2043d5b"},
+    {file = "kiwisolver-1.4.4.tar.gz", hash = "sha256:d41997519fcba4a1e46eb4a2fe31bc12f0ff957b2b81bac28db24744f333e955"},
 ]
 
 [[package]]
@@ -1004,17 +1330,83 @@ files = [
 ]
 
 [[package]]
-name = "mccabe"
-version = "0.6.1"
-description = "McCabe checker, plugin for flake8"
+name = "matplotlib"
+version = "3.7.0"
+description = "Python plotting package"
 category = "dev"
 optional = false
-python-versions = "*"
+python-versions = ">=3.8"
 files = [
-    {file = "mccabe-0.6.1-py2.py3-none-any.whl", hash = "sha256:ab8a6258860da4b6677da4bd2fe5dc2c659cff31b3ee4f7f5d64e79735b80d42"},
-    {file = "mccabe-0.6.1.tar.gz", hash = "sha256:dd8d182285a0fe56bace7f45b5e7d1a6ebcbf524e8f3bd87eb0f125271b8831f"},
+    {file = "matplotlib-3.7.0-cp310-cp310-macosx_10_12_universal2.whl", hash = "sha256:3da8b9618188346239e51f1ea6c0f8f05c6e218cfcc30b399dd7dd7f52e8bceb"},
+    {file = "matplotlib-3.7.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:c0592ba57217c22987b7322df10f75ef95bc44dce781692b4b7524085de66019"},
+    {file = "matplotlib-3.7.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:21269450243d6928da81a9bed201f0909432a74e7d0d65db5545b9fa8a0d0223"},
+    {file = "matplotlib-3.7.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:eb2e76cd429058d8954121c334dddfcd11a6186c6975bca61f3f248c99031b05"},
+    {file = "matplotlib-3.7.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:de20eb1247725a2f889173d391a6d9e7e0f2540feda24030748283108b0478ec"},
+    {file = "matplotlib-3.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c5465735eaaafd1cfaec3fed60aee776aeb3fd3992aa2e49f4635339c931d443"},
+    {file = "matplotlib-3.7.0-cp310-cp310-win32.whl", hash = "sha256:092e6abc80cdf8a95f7d1813e16c0e99ceda8d5b195a3ab859c680f3487b80a2"},
+    {file = "matplotlib-3.7.0-cp310-cp310-win_amd64.whl", hash = "sha256:4f640534ec2760e270801056bc0d8a10777c48b30966eef78a7c35d8590915ba"},
+    {file = "matplotlib-3.7.0-cp311-cp311-macosx_10_12_universal2.whl", hash = "sha256:f336e7014889c38c59029ebacc35c59236a852e4b23836708cfd3f43d1eaeed5"},
+    {file = "matplotlib-3.7.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:3a10428d4f8d1a478ceabd652e61a175b2fdeed4175ab48da4a7b8deb561e3fa"},
+    {file = "matplotlib-3.7.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:46ca923e980f76d34c1c633343a72bb042d6ba690ecc649aababf5317997171d"},
+    {file = "matplotlib-3.7.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c849aa94ff2a70fb71f318f48a61076d1205c6013b9d3885ade7f992093ac434"},
+    {file = "matplotlib-3.7.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:827e78239292e561cfb70abf356a9d7eaf5bf6a85c97877f254009f20b892f89"},
+    {file = "matplotlib-3.7.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:691ef1f15360e439886186d0db77b5345b24da12cbc4fc57b26c4826db4d6cab"},
+    {file = "matplotlib-3.7.0-cp311-cp311-win32.whl", hash = "sha256:21a8aeac39b4a795e697265d800ce52ab59bdeb6bb23082e2d971f3041074f02"},
+    {file = "matplotlib-3.7.0-cp311-cp311-win_amd64.whl", hash = "sha256:01681566e95b9423021b49dea6a2395c16fa054604eacb87f0f4c439750f9114"},
+    {file = "matplotlib-3.7.0-cp38-cp38-macosx_10_12_universal2.whl", hash = "sha256:cf119eee4e57389fba5ac8b816934e95c256535e55f0b21628b4205737d1de85"},
+    {file = "matplotlib-3.7.0-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:21bd4033c40b95abd5b8453f036ed5aa70856e56ecbd887705c37dce007a4c21"},
+    {file = "matplotlib-3.7.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:111ef351f28fd823ed7177632070a6badd6f475607122bc9002a526f2502a0b5"},
+    {file = "matplotlib-3.7.0-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:f91d35b3ef51d29d9c661069b9e4ba431ce283ffc533b981506889e144b5b40e"},
+    {file = "matplotlib-3.7.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:0a776462a4a63c0bfc9df106c15a0897aa2dbab6795c693aa366e8e283958854"},
+    {file = "matplotlib-3.7.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0dfd4a0cbd151f6439e6d7f8dca5292839ca311e7e650596d073774847ca2e4f"},
+    {file = "matplotlib-3.7.0-cp38-cp38-win32.whl", hash = "sha256:56b7b79488209041a9bf7ddc34f1b069274489ce69e34dc63ae241d0d6b4b736"},
+    {file = "matplotlib-3.7.0-cp38-cp38-win_amd64.whl", hash = "sha256:8665855f3919c80551f377bc16df618ceabf3ef65270bc14b60302dce88ca9ab"},
+    {file = "matplotlib-3.7.0-cp39-cp39-macosx_10_12_universal2.whl", hash = "sha256:f910d924da8b9fb066b5beae0b85e34ed1b6293014892baadcf2a51da1c65807"},
+    {file = "matplotlib-3.7.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:cf6346644e8fe234dc847e6232145dac199a650d3d8025b3ef65107221584ba4"},
+    {file = "matplotlib-3.7.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3d1e52365d8d5af699f04581ca191112e1d1220a9ce4386b57d807124d8b55e6"},
+    {file = "matplotlib-3.7.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c869b646489c6a94375714032e5cec08e3aa8d3f7d4e8ef2b0fb50a52b317ce6"},
+    {file = "matplotlib-3.7.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f4ddac5f59e78d04b20469bc43853a8e619bb6505c7eac8ffb343ff2c516d72f"},
+    {file = "matplotlib-3.7.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fb0304c1cd802e9a25743414c887e8a7cd51d96c9ec96d388625d2cd1c137ae3"},
+    {file = "matplotlib-3.7.0-cp39-cp39-win32.whl", hash = "sha256:a06a6c9822e80f323549c6bc9da96d4f233178212ad9a5f4ab87fd153077a507"},
+    {file = "matplotlib-3.7.0-cp39-cp39-win_amd64.whl", hash = "sha256:cb52aa97b92acdee090edfb65d1cb84ea60ab38e871ba8321a10bbcebc2a3540"},
+    {file = "matplotlib-3.7.0-pp38-pypy38_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3493b48e56468c39bd9c1532566dff3b8062952721b7521e1f394eb6791495f4"},
+    {file = "matplotlib-3.7.0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7d0dcd1a0bf8d56551e8617d6dc3881d8a1c7fb37d14e5ec12cbb293f3e6170a"},
+    {file = "matplotlib-3.7.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:51fb664c37714cbaac69c16d6b3719f517a13c96c3f76f4caadd5a0aa7ed0329"},
+    {file = "matplotlib-3.7.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:4497d88c559b76da320b7759d64db442178beeea06a52dc0c629086982082dcd"},
+    {file = "matplotlib-3.7.0-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:9d85355c48ef8b9994293eb7c00f44aa8a43cad7a297fbf0770a25cdb2244b91"},
+    {file = "matplotlib-3.7.0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:03eb2c8ff8d85da679b71e14c7c95d16d014c48e0c0bfa14db85f6cdc5c92aad"},
+    {file = "matplotlib-3.7.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:71b751d06b2ed1fd017de512d7439c0259822864ea16731522b251a27c0b2ede"},
+    {file = "matplotlib-3.7.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:b51ab8a5d5d3bbd4527af633a638325f492e09e45e78afdf816ef55217a09664"},
+    {file = "matplotlib-3.7.0.tar.gz", hash = "sha256:8f6efd313430d7ef70a38a3276281cb2e8646b3a22b3b21eb227da20e15e6813"},
 ]
 
+[package.dependencies]
+contourpy = ">=1.0.1"
+cycler = ">=0.10"
+fonttools = ">=4.22.0"
+importlib-resources = {version = ">=3.2.0", markers = "python_version < \"3.10\""}
+kiwisolver = ">=1.0.1"
+numpy = ">=1.20"
+packaging = ">=20.0"
+pillow = ">=6.2.0"
+pyparsing = ">=2.3.1"
+python-dateutil = ">=2.7"
+
+[[package]]
+name = "matplotlib-inline"
+version = "0.1.6"
+description = "Inline Matplotlib backend for Jupyter"
+category = "dev"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "matplotlib-inline-0.1.6.tar.gz", hash = "sha256:f887e5f10ba98e8d2b150ddcf4702c1e5f8b3a20005eb0f74bfdbd360ee6f304"},
+    {file = "matplotlib_inline-0.1.6-py3-none-any.whl", hash = "sha256:f1f41aab5328aa5aaea9b16d083b128102f8712542f819fe7e6a420ff581b311"},
+]
+
+[package.dependencies]
+traitlets = "*"
+
 [[package]]
 name = "mistune"
 version = "0.8.4"
@@ -1190,20 +1582,17 @@ files = [
 ]
 
 [[package]]
-name = "nodeenv"
-version = "1.7.0"
-description = "Node.js virtual environment builder"
+name = "nest-asyncio"
+version = "1.5.6"
+description = "Patch asyncio to allow nested event loops"
 category = "dev"
 optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
+python-versions = ">=3.5"
 files = [
-    {file = "nodeenv-1.7.0-py2.py3-none-any.whl", hash = "sha256:27083a7b96a25f2f5e1d8cb4b6317ee8aeda3bdd121394e5ac54e498028a042e"},
-    {file = "nodeenv-1.7.0.tar.gz", hash = "sha256:e0e7f7dfb85fc5394c6fe1e8fa98131a2473e04311a45afb6508f7cf1836fa2b"},
+    {file = "nest_asyncio-1.5.6-py3-none-any.whl", hash = "sha256:b9a953fb40dceaa587d109609098db21900182b16440652454a146cffb06e8b8"},
+    {file = "nest_asyncio-1.5.6.tar.gz", hash = "sha256:d267cc1ff794403f7df692964d1d2a3fa9418ffea2a3f6859a439ff482fef290"},
 ]
 
-[package.dependencies]
-setuptools = "*"
-
 [[package]]
 name = "numpy"
 version = "1.24.2"
@@ -1304,43 +1693,138 @@ pytz = ">=2020.1"
 test = ["hypothesis (>=5.5.3)", "pytest (>=6.0)", "pytest-xdist (>=1.31)"]
 
 [[package]]
-name = "pathspec"
-version = "0.11.0"
-description = "Utility library for gitignore style pattern matching of file paths."
+name = "parso"
+version = "0.8.3"
+description = "A Python Parser"
 category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.6"
 files = [
-    {file = "pathspec-0.11.0-py3-none-any.whl", hash = "sha256:3a66eb970cbac598f9e5ccb5b2cf58930cd8e3ed86d393d541eaf2d8b1705229"},
-    {file = "pathspec-0.11.0.tar.gz", hash = "sha256:64d338d4e0914e91c1792321e6907b5a593f1ab1851de7fc269557a21b30ebbc"},
+    {file = "parso-0.8.3-py2.py3-none-any.whl", hash = "sha256:c001d4636cd3aecdaf33cbb40aebb59b094be2a74c556778ef5576c175e19e75"},
+    {file = "parso-0.8.3.tar.gz", hash = "sha256:8c07be290bb59f03588915921e29e8a50002acaf2cdc5fa0e0114f91709fafa0"},
 ]
 
+[package.extras]
+qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
+testing = ["docopt", "pytest (<6.0.0)"]
+
 [[package]]
-name = "pep8"
-version = "1.7.1"
-description = "Python style guide checker"
+name = "pexpect"
+version = "4.8.0"
+description = "Pexpect allows easy control of interactive console applications."
 category = "dev"
 optional = false
 python-versions = "*"
 files = [
-    {file = "pep8-1.7.1-py2.py3-none-any.whl", hash = "sha256:b22cfae5db09833bb9bd7c8463b53e1a9c9b39f12e304a8d0bba729c501827ee"},
-    {file = "pep8-1.7.1.tar.gz", hash = "sha256:fe249b52e20498e59e0b5c5256aa52ee99fc295b26ec9eaa85776ffdb9fe6374"},
+    {file = "pexpect-4.8.0-py2.py3-none-any.whl", hash = "sha256:0b48a55dcb3c05f3329815901ea4fc1537514d6ba867a152b581d69ae3710937"},
+    {file = "pexpect-4.8.0.tar.gz", hash = "sha256:fc65a43959d153d0114afe13997d439c22823a27cefceb5ff35c2178c6784c0c"},
 ]
 
+[package.dependencies]
+ptyprocess = ">=0.5"
+
 [[package]]
-name = "pep8-naming"
-version = "0.10.0"
-description = "Check PEP-8 naming conventions, plugin for flake8"
+name = "pickleshare"
+version = "0.7.5"
+description = "Tiny 'shelve'-like database with concurrency support"
 category = "dev"
 optional = false
 python-versions = "*"
 files = [
-    {file = "pep8-naming-0.10.0.tar.gz", hash = "sha256:f3b4a5f9dd72b991bf7d8e2a341d2e1aa3a884a769b5aaac4f56825c1763bf3a"},
-    {file = "pep8_naming-0.10.0-py2.py3-none-any.whl", hash = "sha256:5d9f1056cb9427ce344e98d1a7f5665710e2f20f748438e308995852cfa24164"},
+    {file = "pickleshare-0.7.5-py2.py3-none-any.whl", hash = "sha256:9649af414d74d4df115d5d718f82acb59c9d418196b7b4290ed47a12ce62df56"},
+    {file = "pickleshare-0.7.5.tar.gz", hash = "sha256:87683d47965c1da65cdacaf31c8441d12b8044cdec9aca500cd78fc2c683afca"},
 ]
 
-[package.dependencies]
-flake8-polyfill = ">=1.0.2,<2"
+[[package]]
+name = "pillow"
+version = "9.4.0"
+description = "Python Imaging Library (Fork)"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "Pillow-9.4.0-1-cp310-cp310-macosx_10_10_x86_64.whl", hash = "sha256:1b4b4e9dda4f4e4c4e6896f93e84a8f0bcca3b059de9ddf67dac3c334b1195e1"},
+    {file = "Pillow-9.4.0-1-cp311-cp311-macosx_10_10_x86_64.whl", hash = "sha256:fb5c1ad6bad98c57482236a21bf985ab0ef42bd51f7ad4e4538e89a997624e12"},
+    {file = "Pillow-9.4.0-1-cp37-cp37m-macosx_10_10_x86_64.whl", hash = "sha256:f0caf4a5dcf610d96c3bd32932bfac8aee61c96e60481c2a0ea58da435e25acd"},
+    {file = "Pillow-9.4.0-1-cp38-cp38-macosx_10_10_x86_64.whl", hash = "sha256:3f4cc516e0b264c8d4ccd6b6cbc69a07c6d582d8337df79be1e15a5056b258c9"},
+    {file = "Pillow-9.4.0-1-cp39-cp39-macosx_10_10_x86_64.whl", hash = "sha256:b8c2f6eb0df979ee99433d8b3f6d193d9590f735cf12274c108bd954e30ca858"},
+    {file = "Pillow-9.4.0-1-pp38-pypy38_pp73-macosx_10_10_x86_64.whl", hash = "sha256:b70756ec9417c34e097f987b4d8c510975216ad26ba6e57ccb53bc758f490dab"},
+    {file = "Pillow-9.4.0-1-pp39-pypy39_pp73-macosx_10_10_x86_64.whl", hash = "sha256:43521ce2c4b865d385e78579a082b6ad1166ebed2b1a2293c3be1d68dd7ca3b9"},
+    {file = "Pillow-9.4.0-2-cp310-cp310-macosx_10_10_x86_64.whl", hash = "sha256:9d9a62576b68cd90f7075876f4e8444487db5eeea0e4df3ba298ee38a8d067b0"},
+    {file = "Pillow-9.4.0-2-cp311-cp311-macosx_10_10_x86_64.whl", hash = "sha256:87708d78a14d56a990fbf4f9cb350b7d89ee8988705e58e39bdf4d82c149210f"},
+    {file = "Pillow-9.4.0-2-cp37-cp37m-macosx_10_10_x86_64.whl", hash = "sha256:8a2b5874d17e72dfb80d917213abd55d7e1ed2479f38f001f264f7ce7bae757c"},
+    {file = "Pillow-9.4.0-2-cp38-cp38-macosx_10_10_x86_64.whl", hash = "sha256:83125753a60cfc8c412de5896d10a0a405e0bd88d0470ad82e0869ddf0cb3848"},
+    {file = "Pillow-9.4.0-2-cp39-cp39-macosx_10_10_x86_64.whl", hash = "sha256:9e5f94742033898bfe84c93c831a6f552bb629448d4072dd312306bab3bd96f1"},
+    {file = "Pillow-9.4.0-2-pp38-pypy38_pp73-macosx_10_10_x86_64.whl", hash = "sha256:013016af6b3a12a2f40b704677f8b51f72cb007dac785a9933d5c86a72a7fe33"},
+    {file = "Pillow-9.4.0-2-pp39-pypy39_pp73-macosx_10_10_x86_64.whl", hash = "sha256:99d92d148dd03fd19d16175b6d355cc1b01faf80dae93c6c3eb4163709edc0a9"},
+    {file = "Pillow-9.4.0-cp310-cp310-macosx_10_10_x86_64.whl", hash = "sha256:2968c58feca624bb6c8502f9564dd187d0e1389964898f5e9e1fbc8533169157"},
+    {file = "Pillow-9.4.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c5c1362c14aee73f50143d74389b2c158707b4abce2cb055b7ad37ce60738d47"},
+    {file = "Pillow-9.4.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd752c5ff1b4a870b7661234694f24b1d2b9076b8bf337321a814c612665f343"},
+    {file = "Pillow-9.4.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9a3049a10261d7f2b6514d35bbb7a4dfc3ece4c4de14ef5876c4b7a23a0e566d"},
+    {file = "Pillow-9.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:16a8df99701f9095bea8a6c4b3197da105df6f74e6176c5b410bc2df2fd29a57"},
+    {file = "Pillow-9.4.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:94cdff45173b1919350601f82d61365e792895e3c3a3443cf99819e6fbf717a5"},
+    {file = "Pillow-9.4.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:ed3e4b4e1e6de75fdc16d3259098de7c6571b1a6cc863b1a49e7d3d53e036070"},
+    {file = "Pillow-9.4.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:d5b2f8a31bd43e0f18172d8ac82347c8f37ef3e0b414431157718aa234991b28"},
+    {file = "Pillow-9.4.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:09b89ddc95c248ee788328528e6a2996e09eaccddeeb82a5356e92645733be35"},
+    {file = "Pillow-9.4.0-cp310-cp310-win32.whl", hash = "sha256:f09598b416ba39a8f489c124447b007fe865f786a89dbfa48bb5cf395693132a"},
+    {file = "Pillow-9.4.0-cp310-cp310-win_amd64.whl", hash = "sha256:f6e78171be3fb7941f9910ea15b4b14ec27725865a73c15277bc39f5ca4f8391"},
+    {file = "Pillow-9.4.0-cp311-cp311-macosx_10_10_x86_64.whl", hash = "sha256:3fa1284762aacca6dc97474ee9c16f83990b8eeb6697f2ba17140d54b453e133"},
+    {file = "Pillow-9.4.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:eaef5d2de3c7e9b21f1e762f289d17b726c2239a42b11e25446abf82b26ac132"},
+    {file = "Pillow-9.4.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a4dfdae195335abb4e89cc9762b2edc524f3c6e80d647a9a81bf81e17e3fb6f0"},
+    {file = "Pillow-9.4.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6abfb51a82e919e3933eb137e17c4ae9c0475a25508ea88993bb59faf82f3b35"},
+    {file = "Pillow-9.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:451f10ef963918e65b8869e17d67db5e2f4ab40e716ee6ce7129b0cde2876eab"},
+    {file = "Pillow-9.4.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:6663977496d616b618b6cfa43ec86e479ee62b942e1da76a2c3daa1c75933ef4"},
+    {file = "Pillow-9.4.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:60e7da3a3ad1812c128750fc1bc14a7ceeb8d29f77e0a2356a8fb2aa8925287d"},
+    {file = "Pillow-9.4.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:19005a8e58b7c1796bc0167862b1f54a64d3b44ee5d48152b06bb861458bc0f8"},
+    {file = "Pillow-9.4.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:f715c32e774a60a337b2bb8ad9839b4abf75b267a0f18806f6f4f5f1688c4b5a"},
+    {file = "Pillow-9.4.0-cp311-cp311-win32.whl", hash = "sha256:b222090c455d6d1a64e6b7bb5f4035c4dff479e22455c9eaa1bdd4c75b52c80c"},
+    {file = "Pillow-9.4.0-cp311-cp311-win_amd64.whl", hash = "sha256:ba6612b6548220ff5e9df85261bddc811a057b0b465a1226b39bfb8550616aee"},
+    {file = "Pillow-9.4.0-cp37-cp37m-macosx_10_10_x86_64.whl", hash = "sha256:5f532a2ad4d174eb73494e7397988e22bf427f91acc8e6ebf5bb10597b49c493"},
+    {file = "Pillow-9.4.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5dd5a9c3091a0f414a963d427f920368e2b6a4c2f7527fdd82cde8ef0bc7a327"},
+    {file = "Pillow-9.4.0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ef21af928e807f10bf4141cad4746eee692a0dd3ff56cfb25fce076ec3cc8abe"},
+    {file = "Pillow-9.4.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:847b114580c5cc9ebaf216dd8c8dbc6b00a3b7ab0131e173d7120e6deade1f57"},
+    {file = "Pillow-9.4.0-cp37-cp37m-manylinux_2_28_aarch64.whl", hash = "sha256:653d7fb2df65efefbcbf81ef5fe5e5be931f1ee4332c2893ca638c9b11a409c4"},
+    {file = "Pillow-9.4.0-cp37-cp37m-manylinux_2_28_x86_64.whl", hash = "sha256:46f39cab8bbf4a384ba7cb0bc8bae7b7062b6a11cfac1ca4bc144dea90d4a9f5"},
+    {file = "Pillow-9.4.0-cp37-cp37m-win32.whl", hash = "sha256:7ac7594397698f77bce84382929747130765f66406dc2cd8b4ab4da68ade4c6e"},
+    {file = "Pillow-9.4.0-cp37-cp37m-win_amd64.whl", hash = "sha256:46c259e87199041583658457372a183636ae8cd56dbf3f0755e0f376a7f9d0e6"},
+    {file = "Pillow-9.4.0-cp38-cp38-macosx_10_10_x86_64.whl", hash = "sha256:0e51f608da093e5d9038c592b5b575cadc12fd748af1479b5e858045fff955a9"},
+    {file = "Pillow-9.4.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:765cb54c0b8724a7c12c55146ae4647e0274a839fb6de7bcba841e04298e1011"},
+    {file = "Pillow-9.4.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:519e14e2c49fcf7616d6d2cfc5c70adae95682ae20f0395e9280db85e8d6c4df"},
+    {file = "Pillow-9.4.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d197df5489004db87d90b918033edbeee0bd6df3848a204bca3ff0a903bef837"},
+    {file = "Pillow-9.4.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0845adc64fe9886db00f5ab68c4a8cd933ab749a87747555cec1c95acea64b0b"},
+    {file = "Pillow-9.4.0-cp38-cp38-manylinux_2_28_aarch64.whl", hash = "sha256:e1339790c083c5a4de48f688b4841f18df839eb3c9584a770cbd818b33e26d5d"},
+    {file = "Pillow-9.4.0-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:a96e6e23f2b79433390273eaf8cc94fec9c6370842e577ab10dabdcc7ea0a66b"},
+    {file = "Pillow-9.4.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:7cfc287da09f9d2a7ec146ee4d72d6ea1342e770d975e49a8621bf54eaa8f30f"},
+    {file = "Pillow-9.4.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:d7081c084ceb58278dd3cf81f836bc818978c0ccc770cbbb202125ddabec6628"},
+    {file = "Pillow-9.4.0-cp38-cp38-win32.whl", hash = "sha256:df41112ccce5d47770a0c13651479fbcd8793f34232a2dd9faeccb75eb5d0d0d"},
+    {file = "Pillow-9.4.0-cp38-cp38-win_amd64.whl", hash = "sha256:7a21222644ab69ddd9967cfe6f2bb420b460dae4289c9d40ff9a4896e7c35c9a"},
+    {file = "Pillow-9.4.0-cp39-cp39-macosx_10_10_x86_64.whl", hash = "sha256:0f3269304c1a7ce82f1759c12ce731ef9b6e95b6df829dccd9fe42912cc48569"},
+    {file = "Pillow-9.4.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:cb362e3b0976dc994857391b776ddaa8c13c28a16f80ac6522c23d5257156bed"},
+    {file = "Pillow-9.4.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a2e0f87144fcbbe54297cae708c5e7f9da21a4646523456b00cc956bd4c65815"},
+    {file = "Pillow-9.4.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:28676836c7796805914b76b1837a40f76827ee0d5398f72f7dcc634bae7c6264"},
+    {file = "Pillow-9.4.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0884ba7b515163a1a05440a138adeb722b8a6ae2c2b33aea93ea3118dd3a899e"},
+    {file = "Pillow-9.4.0-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:53dcb50fbdc3fb2c55431a9b30caeb2f7027fcd2aeb501459464f0214200a503"},
+    {file = "Pillow-9.4.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:e8c5cf126889a4de385c02a2c3d3aba4b00f70234bfddae82a5eaa3ee6d5e3e6"},
+    {file = "Pillow-9.4.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:6c6b1389ed66cdd174d040105123a5a1bc91d0aa7059c7261d20e583b6d8cbd2"},
+    {file = "Pillow-9.4.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:0dd4c681b82214b36273c18ca7ee87065a50e013112eea7d78c7a1b89a739153"},
+    {file = "Pillow-9.4.0-cp39-cp39-win32.whl", hash = "sha256:6d9dfb9959a3b0039ee06c1a1a90dc23bac3b430842dcb97908ddde05870601c"},
+    {file = "Pillow-9.4.0-cp39-cp39-win_amd64.whl", hash = "sha256:54614444887e0d3043557d9dbc697dbb16cfb5a35d672b7a0fcc1ed0cf1c600b"},
+    {file = "Pillow-9.4.0-pp38-pypy38_pp73-macosx_10_10_x86_64.whl", hash = "sha256:b9b752ab91e78234941e44abdecc07f1f0d8f51fb62941d32995b8161f68cfe5"},
+    {file = "Pillow-9.4.0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d3b56206244dc8711f7e8b7d6cad4663917cd5b2d950799425076681e8766286"},
+    {file = "Pillow-9.4.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aabdab8ec1e7ca7f1434d042bf8b1e92056245fb179790dc97ed040361f16bfd"},
+    {file = "Pillow-9.4.0-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:db74f5562c09953b2c5f8ec4b7dfd3f5421f31811e97d1dbc0a7c93d6e3a24df"},
+    {file = "Pillow-9.4.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:e9d7747847c53a16a729b6ee5e737cf170f7a16611c143d95aa60a109a59c336"},
+    {file = "Pillow-9.4.0-pp39-pypy39_pp73-macosx_10_10_x86_64.whl", hash = "sha256:b52ff4f4e002f828ea6483faf4c4e8deea8d743cf801b74910243c58acc6eda3"},
+    {file = "Pillow-9.4.0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:575d8912dca808edd9acd6f7795199332696d3469665ef26163cd090fa1f8bfa"},
+    {file = "Pillow-9.4.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c3c4ed2ff6760e98d262e0cc9c9a7f7b8a9f61aa4d47c58835cdaf7b0b8811bb"},
+    {file = "Pillow-9.4.0-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:e621b0246192d3b9cb1dc62c78cfa4c6f6d2ddc0ec207d43c0dedecb914f152a"},
+    {file = "Pillow-9.4.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:8f127e7b028900421cad64f51f75c051b628db17fb00e099eb148761eed598c9"},
+    {file = "Pillow-9.4.0.tar.gz", hash = "sha256:a1c2d7780448eb93fbcc3789bf3916aa5720d942e37945f4056680317f1cd23e"},
+]
+
+[package.extras]
+docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-issues (>=3.0.1)", "sphinx-removed-in", "sphinxext-opengraph"]
+tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "platformdirs"
@@ -1375,71 +1859,84 @@ dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
-name = "pre-commit"
-version = "3.1.1"
-description = "A framework for managing and maintaining multi-language pre-commit hooks."
+name = "prompt-toolkit"
+version = "3.0.38"
+description = "Library for building powerful interactive command lines in Python"
 category = "dev"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.7.0"
 files = [
-    {file = "pre_commit-3.1.1-py2.py3-none-any.whl", hash = "sha256:b80254e60668e1dd1f5c03a1c9e0413941d61f568a57d745add265945f65bfe8"},
-    {file = "pre_commit-3.1.1.tar.gz", hash = "sha256:d63e6537f9252d99f65755ae5b79c989b462d511ebbc481b561db6a297e1e865"},
+    {file = "prompt_toolkit-3.0.38-py3-none-any.whl", hash = "sha256:45ea77a2f7c60418850331366c81cf6b5b9cf4c7fd34616f733c5427e6abbb1f"},
+    {file = "prompt_toolkit-3.0.38.tar.gz", hash = "sha256:23ac5d50538a9a38c8bde05fecb47d0b403ecd0662857a86f886f798563d5b9b"},
 ]
 
 [package.dependencies]
-cfgv = ">=2.0.0"
-identify = ">=1.0.0"
-nodeenv = ">=0.11.1"
-pyyaml = ">=5.1"
-virtualenv = ">=20.10.0"
+wcwidth = "*"
 
 [[package]]
-name = "prospector"
-version = "1.7.7"
-description = ""
+name = "psutil"
+version = "5.9.4"
+description = "Cross-platform lib for process and system monitoring in Python."
 category = "dev"
 optional = false
-python-versions = ">=3.6.2,<4.0"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
-    {file = "prospector-1.7.7-py3-none-any.whl", hash = "sha256:2dec5dac06f136880a3710996c0886dcc99e739007bbc05afc32884973f5c058"},
-    {file = "prospector-1.7.7.tar.gz", hash = "sha256:c04b3d593e7c525cf9a742fed62afbe02e2874f0e42f2f56a49378fd94037360"},
+    {file = "psutil-5.9.4-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:c1ca331af862803a42677c120aff8a814a804e09832f166f226bfd22b56feee8"},
+    {file = "psutil-5.9.4-cp27-cp27m-manylinux2010_i686.whl", hash = "sha256:68908971daf802203f3d37e78d3f8831b6d1014864d7a85937941bb35f09aefe"},
+    {file = "psutil-5.9.4-cp27-cp27m-manylinux2010_x86_64.whl", hash = "sha256:3ff89f9b835100a825b14c2808a106b6fdcc4b15483141482a12c725e7f78549"},
+    {file = "psutil-5.9.4-cp27-cp27m-win32.whl", hash = "sha256:852dd5d9f8a47169fe62fd4a971aa07859476c2ba22c2254d4a1baa4e10b95ad"},
+    {file = "psutil-5.9.4-cp27-cp27m-win_amd64.whl", hash = "sha256:9120cd39dca5c5e1c54b59a41d205023d436799b1c8c4d3ff71af18535728e94"},
+    {file = "psutil-5.9.4-cp27-cp27mu-manylinux2010_i686.whl", hash = "sha256:6b92c532979bafc2df23ddc785ed116fced1f492ad90a6830cf24f4d1ea27d24"},
+    {file = "psutil-5.9.4-cp27-cp27mu-manylinux2010_x86_64.whl", hash = "sha256:efeae04f9516907be44904cc7ce08defb6b665128992a56957abc9b61dca94b7"},
+    {file = "psutil-5.9.4-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:54d5b184728298f2ca8567bf83c422b706200bcbbfafdc06718264f9393cfeb7"},
+    {file = "psutil-5.9.4-cp36-abi3-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:16653106f3b59386ffe10e0bad3bb6299e169d5327d3f187614b1cb8f24cf2e1"},
+    {file = "psutil-5.9.4-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:54c0d3d8e0078b7666984e11b12b88af2db11d11249a8ac8920dd5ef68a66e08"},
+    {file = "psutil-5.9.4-cp36-abi3-win32.whl", hash = "sha256:149555f59a69b33f056ba1c4eb22bb7bf24332ce631c44a319cec09f876aaeff"},
+    {file = "psutil-5.9.4-cp36-abi3-win_amd64.whl", hash = "sha256:fd8522436a6ada7b4aad6638662966de0d61d241cb821239b2ae7013d41a43d4"},
+    {file = "psutil-5.9.4-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:6001c809253a29599bc0dfd5179d9f8a5779f9dffea1da0f13c53ee568115e1e"},
+    {file = "psutil-5.9.4.tar.gz", hash = "sha256:3d7f9739eb435d4b1338944abe23f49584bde5395f27487d2ee25ad9a8774a62"},
 ]
 
-[package.dependencies]
-dodgy = ">=0.2.1,<0.3.0"
-mccabe = ">=0.6.0,<0.7.0"
-pep8-naming = ">=0.3.3,<=0.10.0"
-pycodestyle = ">=2.6.0,<2.9.0"
-pydocstyle = ">=2.0.0"
-pyflakes = ">=2.2.0,<3"
-pylint = ">=2.8.3"
-pylint-celery = "0.3"
-pylint-django = ">=2.5,<2.6"
-pylint-flask = "0.6"
-pylint-plugin-utils = ">=0.7,<0.8"
-PyYAML = "*"
-requirements-detector = ">=0.7,<0.8"
-setoptconf-tmp = ">=0.3.1,<0.4.0"
-toml = ">=0.10.2,<0.11.0"
+[package.extras]
+test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
+
+[[package]]
+name = "ptyprocess"
+version = "0.7.0"
+description = "Run a subprocess in a pseudo terminal"
+category = "dev"
+optional = false
+python-versions = "*"
+files = [
+    {file = "ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35"},
+    {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"},
+]
+
+[[package]]
+name = "pure-eval"
+version = "0.2.2"
+description = "Safely evaluate AST nodes without side effects"
+category = "dev"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pure_eval-0.2.2-py3-none-any.whl", hash = "sha256:01eaab343580944bc56080ebe0a674b39ec44a945e6d09ba7db3cb8cec289350"},
+    {file = "pure_eval-0.2.2.tar.gz", hash = "sha256:2b45320af6dfaa1750f543d714b6d1c520a1688dec6fd24d339063ce0aaa9ac3"},
+]
 
 [package.extras]
-with-bandit = ["bandit (>=1.5.1)"]
-with-everything = ["bandit (>=1.5.1)", "frosted (>=1.4.1)", "mypy (>=0.600)", "pyroma (>=2.4)", "vulture (>=1.5)"]
-with-frosted = ["frosted (>=1.4.1)"]
-with-mypy = ["mypy (>=0.600)"]
-with-pyroma = ["pyroma (>=2.4)"]
-with-vulture = ["vulture (>=1.5)"]
+tests = ["pytest"]
 
 [[package]]
-name = "pycodestyle"
-version = "2.8.0"
-description = "Python style guide checker"
+name = "pycparser"
+version = "2.21"
+description = "C parser in Python"
 category = "dev"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
-    {file = "pycodestyle-2.8.0-py2.py3-none-any.whl", hash = "sha256:720f8b39dde8b293825e7ff02c475f3077124006db4f440dcbc9a20b76548a20"},
-    {file = "pycodestyle-2.8.0.tar.gz", hash = "sha256:eddd5847ef438ea1c7870ca7eb78a9d47ce0cdb4851a5523949f2601d0cbbe7f"},
+    {file = "pycparser-2.21-py2.py3-none-any.whl", hash = "sha256:8ee45429555515e1f6b185e78100aea234072576aa43ab53aefcae078162fca9"},
+    {file = "pycparser-2.21.tar.gz", hash = "sha256:e644fdec12f7872f86c58ff790da456218b10f863970249516d60a5eaca77206"},
 ]
 
 [[package]]
@@ -1495,36 +1992,6 @@ typing-extensions = ">=4.2.0"
 dotenv = ["python-dotenv (>=0.10.4)"]
 email = ["email-validator (>=1.0.3)"]
 
-[[package]]
-name = "pydocstyle"
-version = "6.3.0"
-description = "Python docstring style checker"
-category = "dev"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "pydocstyle-6.3.0-py3-none-any.whl", hash = "sha256:118762d452a49d6b05e194ef344a55822987a462831ade91ec5c06fd2169d019"},
-    {file = "pydocstyle-6.3.0.tar.gz", hash = "sha256:7ce43f0c0ac87b07494eb9c0b462c0b73e6ff276807f204d6b53edc72b7e44e1"},
-]
-
-[package.dependencies]
-snowballstemmer = ">=2.2.0"
-
-[package.extras]
-toml = ["tomli (>=1.2.3)"]
-
-[[package]]
-name = "pyflakes"
-version = "2.5.0"
-description = "passive checker of Python programs"
-category = "dev"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "pyflakes-2.5.0-py2.py3-none-any.whl", hash = "sha256:4579f67d887f804e67edb544428f264b7b24f435b263c4614f384135cea553d2"},
-    {file = "pyflakes-2.5.0.tar.gz", hash = "sha256:491feb020dca48ccc562a8c0cbe8df07ee13078df59813b83959cbdada312ea3"},
-]
-
 [[package]]
 name = "pygments"
 version = "2.14.0"
@@ -1541,99 +2008,19 @@ files = [
 plugins = ["importlib-metadata"]
 
 [[package]]
-name = "pylint"
-version = "2.16.2"
-description = "python code static checker"
+name = "pyparsing"
+version = "3.0.9"
+description = "pyparsing module - Classes and methods to define and execute parsing grammars"
 category = "dev"
 optional = false
-python-versions = ">=3.7.2"
+python-versions = ">=3.6.8"
 files = [
-    {file = "pylint-2.16.2-py3-none-any.whl", hash = "sha256:ff22dde9c2128cd257c145cfd51adeff0be7df4d80d669055f24a962b351bbe4"},
-    {file = "pylint-2.16.2.tar.gz", hash = "sha256:13b2c805a404a9bf57d002cd5f054ca4d40b0b87542bdaba5e05321ae8262c84"},
+    {file = "pyparsing-3.0.9-py3-none-any.whl", hash = "sha256:5026bae9a10eeaefb61dab2f09052b9f4307d44aee4eda64b309723d8d206bbc"},
+    {file = "pyparsing-3.0.9.tar.gz", hash = "sha256:2b020ecf7d21b687f219b71ecad3631f644a47f01403fa1d1036b0c6416d70fb"},
 ]
 
-[package.dependencies]
-astroid = ">=2.14.2,<=2.16.0-dev0"
-colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
-dill = [
-    {version = ">=0.2", markers = "python_version < \"3.11\""},
-    {version = ">=0.3.6", markers = "python_version >= \"3.11\""},
-]
-isort = ">=4.2.5,<6"
-mccabe = ">=0.6,<0.8"
-platformdirs = ">=2.2.0"
-tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
-tomlkit = ">=0.10.1"
-typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""}
-
 [package.extras]
-spelling = ["pyenchant (>=3.2,<4.0)"]
-testutils = ["gitpython (>3)"]
-
-[[package]]
-name = "pylint-celery"
-version = "0.3"
-description = "pylint-celery is a Pylint plugin to aid Pylint in recognising and understandingerrors caused when using the Celery library"
-category = "dev"
-optional = false
-python-versions = "*"
-files = [
-    {file = "pylint-celery-0.3.tar.gz", hash = "sha256:41e32094e7408d15c044178ea828dd524beedbdbe6f83f712c5e35bde1de4beb"},
-]
-
-[package.dependencies]
-astroid = ">=1.0"
-pylint = ">=1.0"
-pylint-plugin-utils = ">=0.2.1"
-
-[[package]]
-name = "pylint-django"
-version = "2.5.3"
-description = "A Pylint plugin to help Pylint understand the Django web framework"
-category = "dev"
-optional = false
-python-versions = "*"
-files = [
-    {file = "pylint-django-2.5.3.tar.gz", hash = "sha256:0ac090d106c62fe33782a1d01bda1610b761bb1c9bf5035ced9d5f23a13d8591"},
-    {file = "pylint_django-2.5.3-py3-none-any.whl", hash = "sha256:56b12b6adf56d548412445bd35483034394a1a94901c3f8571980a13882299d5"},
-]
-
-[package.dependencies]
-pylint = ">=2.0,<3"
-pylint-plugin-utils = ">=0.7"
-
-[package.extras]
-for-tests = ["coverage", "django-tables2", "django-tastypie", "factory-boy", "pylint (>=2.13)", "pytest", "wheel"]
-with-django = ["Django"]
-
-[[package]]
-name = "pylint-flask"
-version = "0.6"
-description = "pylint-flask is a Pylint plugin to aid Pylint in recognizing and understanding errors caused when using Flask"
-category = "dev"
-optional = false
-python-versions = "*"
-files = [
-    {file = "pylint-flask-0.6.tar.gz", hash = "sha256:f4d97de2216bf7bfce07c9c08b166e978fe9f2725de2a50a9845a97de7e31517"},
-]
-
-[package.dependencies]
-pylint-plugin-utils = ">=0.2.1"
-
-[[package]]
-name = "pylint-plugin-utils"
-version = "0.7"
-description = "Utilities and helpers for writing Pylint plugins"
-category = "dev"
-optional = false
-python-versions = ">=3.6.2"
-files = [
-    {file = "pylint-plugin-utils-0.7.tar.gz", hash = "sha256:ce48bc0516ae9415dd5c752c940dfe601b18fe0f48aa249f2386adfa95a004dd"},
-    {file = "pylint_plugin_utils-0.7-py3-none-any.whl", hash = "sha256:b3d43e85ab74c4f48bb46ae4ce771e39c3a20f8b3d56982ab17aa73b4f98d535"},
-]
-
-[package.dependencies]
-pylint = ">=1.7"
+diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
 name = "pyproj"
@@ -1791,6 +2178,30 @@ files = [
     {file = "pytz-2022.7.1.tar.gz", hash = "sha256:01a0681c4b9684a28304615eba55d1ab31ae00bf68ec157ec3708a8182dbbcd0"},
 ]
 
+[[package]]
+name = "pywin32"
+version = "305"
+description = "Python for Window Extensions"
+category = "dev"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pywin32-305-cp310-cp310-win32.whl", hash = "sha256:421f6cd86e84bbb696d54563c48014b12a23ef95a14e0bdba526be756d89f116"},
+    {file = "pywin32-305-cp310-cp310-win_amd64.whl", hash = "sha256:73e819c6bed89f44ff1d690498c0a811948f73777e5f97c494c152b850fad478"},
+    {file = "pywin32-305-cp310-cp310-win_arm64.whl", hash = "sha256:742eb905ce2187133a29365b428e6c3b9001d79accdc30aa8969afba1d8470f4"},
+    {file = "pywin32-305-cp311-cp311-win32.whl", hash = "sha256:19ca459cd2e66c0e2cc9a09d589f71d827f26d47fe4a9d09175f6aa0256b51c2"},
+    {file = "pywin32-305-cp311-cp311-win_amd64.whl", hash = "sha256:326f42ab4cfff56e77e3e595aeaf6c216712bbdd91e464d167c6434b28d65990"},
+    {file = "pywin32-305-cp311-cp311-win_arm64.whl", hash = "sha256:4ecd404b2c6eceaca52f8b2e3e91b2187850a1ad3f8b746d0796a98b4cea04db"},
+    {file = "pywin32-305-cp36-cp36m-win32.whl", hash = "sha256:48d8b1659284f3c17b68587af047d110d8c44837736b8932c034091683e05863"},
+    {file = "pywin32-305-cp36-cp36m-win_amd64.whl", hash = "sha256:13362cc5aa93c2beaf489c9c9017c793722aeb56d3e5166dadd5ef82da021fe1"},
+    {file = "pywin32-305-cp37-cp37m-win32.whl", hash = "sha256:a55db448124d1c1484df22fa8bbcbc45c64da5e6eae74ab095b9ea62e6d00496"},
+    {file = "pywin32-305-cp37-cp37m-win_amd64.whl", hash = "sha256:109f98980bfb27e78f4df8a51a8198e10b0f347257d1e265bb1a32993d0c973d"},
+    {file = "pywin32-305-cp38-cp38-win32.whl", hash = "sha256:9dd98384da775afa009bc04863426cb30596fd78c6f8e4e2e5bbf4edf8029504"},
+    {file = "pywin32-305-cp38-cp38-win_amd64.whl", hash = "sha256:56d7a9c6e1a6835f521788f53b5af7912090674bb84ef5611663ee1595860fc7"},
+    {file = "pywin32-305-cp39-cp39-win32.whl", hash = "sha256:9d968c677ac4d5cbdaa62fd3014ab241718e619d8e36ef8e11fb930515a1e918"},
+    {file = "pywin32-305-cp39-cp39-win_amd64.whl", hash = "sha256:50768c6b7c3f0b38b7fb14dd4104da93ebced5f1a50dc0e834594bff6fbe1271"},
+]
+
 [[package]]
 name = "pyyaml"
 version = "6.0"
@@ -1841,6 +2252,96 @@ files = [
     {file = "PyYAML-6.0.tar.gz", hash = "sha256:68fb519c14306fec9720a2a5b45bc9f0c8d1b9c72adf45c37baedfcd949c35a2"},
 ]
 
+[[package]]
+name = "pyzmq"
+version = "25.0.0"
+description = "Python bindings for 0MQ"
+category = "dev"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "pyzmq-25.0.0-cp310-cp310-macosx_10_15_universal2.whl", hash = "sha256:2d05d904f03ddf1e0d83d97341354dfe52244a619b5a1440a5f47a5b3451e84e"},
+    {file = "pyzmq-25.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0a154ef810d44f9d28868be04641f837374a64e7449df98d9208e76c260c7ef1"},
+    {file = "pyzmq-25.0.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:487305c2a011fdcf3db1f24e8814bb76d23bc4d2f46e145bc80316a59a9aa07d"},
+    {file = "pyzmq-25.0.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2e7b87638ee30ab13230e37ce5331b3e730b1e0dda30120b9eeec3540ed292c8"},
+    {file = "pyzmq-25.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75243e422e85a62f0ab7953dc315452a56b2c6a7e7d1a3c3109ac3cc57ed6b47"},
+    {file = "pyzmq-25.0.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:31e523d067ce44a04e876bed3ff9ea1ff8d1b6636d16e5fcace9d22f8c564369"},
+    {file = "pyzmq-25.0.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:8539216173135e9e89f6b1cc392e74e6b935b91e8c76106cf50e7a02ab02efe5"},
+    {file = "pyzmq-25.0.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:2754fa68da08a854f4816e05160137fa938a2347276471103d31e04bcee5365c"},
+    {file = "pyzmq-25.0.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:4a1bc30f0c18444d51e9b0d0dd39e3a4e7c53ee74190bebef238cd58de577ea9"},
+    {file = "pyzmq-25.0.0-cp310-cp310-win32.whl", hash = "sha256:01d53958c787cfea34091fcb8ef36003dbb7913b8e9f8f62a0715234ebc98b70"},
+    {file = "pyzmq-25.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:58fc3ad5e1cfd2e6d24741fbb1e216b388115d31b0ca6670f894187f280b6ba6"},
+    {file = "pyzmq-25.0.0-cp311-cp311-macosx_10_15_universal2.whl", hash = "sha256:e4bba04ea779a3d7ef25a821bb63fd0939142c88e7813e5bd9c6265a20c523a2"},
+    {file = "pyzmq-25.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:af1fbfb7ad6ac0009ccee33c90a1d303431c7fb594335eb97760988727a37577"},
+    {file = "pyzmq-25.0.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:85456f0d8f3268eecd63dede3b99d5bd8d3b306310c37d4c15141111d22baeaf"},
+    {file = "pyzmq-25.0.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0645b5a2d2a06fd8eb738018490c514907f7488bf9359c6ee9d92f62e844b76f"},
+    {file = "pyzmq-25.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f72ea279b2941a5203e935a4588b9ba8a48aeb9a926d9dfa1986278bd362cb8"},
+    {file = "pyzmq-25.0.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:4e295f7928a31ae0f657e848c5045ba6d693fe8921205f408ca3804b1b236968"},
+    {file = "pyzmq-25.0.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:ac97e7d647d5519bcef48dd8d3d331f72975afa5c4496c95f6e854686f45e2d9"},
+    {file = "pyzmq-25.0.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:656281d496aaf9ca4fd4cea84e6d893e3361057c4707bd38618f7e811759103c"},
+    {file = "pyzmq-25.0.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:1f6116991568aac48b94d6d8aaed6157d407942ea385335a6ed313692777fb9d"},
+    {file = "pyzmq-25.0.0-cp311-cp311-win32.whl", hash = "sha256:0282bba9aee6e0346aa27d6c69b5f7df72b5a964c91958fc9e0c62dcae5fdcdc"},
+    {file = "pyzmq-25.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:526f884a27e8bba62fe1f4e07c62be2cfe492b6d432a8fdc4210397f8cf15331"},
+    {file = "pyzmq-25.0.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:ccb3e1a863222afdbda42b7ca8ac8569959593d7abd44f5a709177d6fa27d266"},
+    {file = "pyzmq-25.0.0-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4046d03100aca266e70d54a35694cb35d6654cfbef633e848b3c4a8d64b9d187"},
+    {file = "pyzmq-25.0.0-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3100dddcada66ec5940ed6391ebf9d003cc3ede3d320748b2737553019f58230"},
+    {file = "pyzmq-25.0.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:7877264aa851c19404b1bb9dbe6eed21ea0c13698be1eda3784aab3036d1c861"},
+    {file = "pyzmq-25.0.0-cp36-cp36m-musllinux_1_1_aarch64.whl", hash = "sha256:5049e75cc99db65754a3da5f079230fb8889230cf09462ec972d884d1704a3ed"},
+    {file = "pyzmq-25.0.0-cp36-cp36m-musllinux_1_1_i686.whl", hash = "sha256:81f99fb1224d36eb91557afec8cdc2264e856f3464500b55749020ce4c848ef2"},
+    {file = "pyzmq-25.0.0-cp36-cp36m-musllinux_1_1_x86_64.whl", hash = "sha256:a1cd4a95f176cdc0ee0a82d49d5830f13ae6015d89decbf834c273bc33eeb3d3"},
+    {file = "pyzmq-25.0.0-cp36-cp36m-win32.whl", hash = "sha256:926236ca003aec70574754f39703528947211a406f5c6c8b3e50eca04a9e87fc"},
+    {file = "pyzmq-25.0.0-cp36-cp36m-win_amd64.whl", hash = "sha256:94f0a7289d0f5c80807c37ebb404205e7deb737e8763eb176f4770839ee2a287"},
+    {file = "pyzmq-25.0.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:f3f96d452e9580cb961ece2e5a788e64abaecb1232a80e61deffb28e105ff84a"},
+    {file = "pyzmq-25.0.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:930e6ad4f2eaac31a3d0c2130619d25db754b267487ebc186c6ad18af2a74018"},
+    {file = "pyzmq-25.0.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e1081d7030a1229c8ff90120346fb7599b54f552e98fcea5170544e7c6725aab"},
+    {file = "pyzmq-25.0.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:531866c491aee5a1e967c286cfa470dffac1e2a203b1afda52d62b58782651e9"},
+    {file = "pyzmq-25.0.0-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:fc7c1421c5b1c916acf3128bf3cc7ea7f5018b58c69a6866d70c14190e600ce9"},
+    {file = "pyzmq-25.0.0-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:9a2d5e419bd39a1edb6cdd326d831f0120ddb9b1ff397e7d73541bf393294973"},
+    {file = "pyzmq-25.0.0-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:183e18742be3621acf8908903f689ec520aee3f08449bfd29f583010ca33022b"},
+    {file = "pyzmq-25.0.0-cp37-cp37m-win32.whl", hash = "sha256:02f5cb60a7da1edd5591a15efa654ffe2303297a41e1b40c3c8942f8f11fc17c"},
+    {file = "pyzmq-25.0.0-cp37-cp37m-win_amd64.whl", hash = "sha256:cac602e02341eaaf4edfd3e29bd3fdef672e61d4e6dfe5c1d065172aee00acee"},
+    {file = "pyzmq-25.0.0-cp38-cp38-macosx_10_15_universal2.whl", hash = "sha256:e14df47c1265356715d3d66e90282a645ebc077b70b3806cf47efcb7d1d630cb"},
+    {file = "pyzmq-25.0.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:293a7c2128690f496057f1f1eb6074f8746058d13588389981089ec45d8fdc77"},
+    {file = "pyzmq-25.0.0-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:731b208bc9412deeb553c9519dca47136b5a01ca66667cafd8733211941b17e4"},
+    {file = "pyzmq-25.0.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:b055a1cddf8035966ad13aa51edae5dc8f1bba0b5d5e06f7a843d8b83dc9b66b"},
+    {file = "pyzmq-25.0.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:17e1cb97d573ea84d7cd97188b42ca6f611ab3ee600f6a75041294ede58e3d20"},
+    {file = "pyzmq-25.0.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:60ecbfe7669d3808ffa8a7dd1487d6eb8a4015b07235e3b723d4b2a2d4de7203"},
+    {file = "pyzmq-25.0.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:4c25c95416133942280faaf068d0fddfd642b927fb28aaf4ab201a738e597c1e"},
+    {file = "pyzmq-25.0.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:be05504af0619d1cffa500af1e0ede69fb683f301003851f5993b5247cc2c576"},
+    {file = "pyzmq-25.0.0-cp38-cp38-win32.whl", hash = "sha256:6bf3842af37af43fa953e96074ebbb5315f6a297198f805d019d788a1021dbc8"},
+    {file = "pyzmq-25.0.0-cp38-cp38-win_amd64.whl", hash = "sha256:b90bb8dfbbd138558f1f284fecfe328f7653616ff9a972433a00711d9475d1a9"},
+    {file = "pyzmq-25.0.0-cp39-cp39-macosx_10_15_universal2.whl", hash = "sha256:62b9e80890c0d2408eb42d5d7e1fc62a5ce71be3288684788f74cf3e59ffd6e2"},
+    {file = "pyzmq-25.0.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:484c2c4ee02c1edc07039f42130bd16e804b1fe81c4f428e0042e03967f40c20"},
+    {file = "pyzmq-25.0.0-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:9ca6db34b26c4d3e9b0728841ec9aa39484eee272caa97972ec8c8e231b20c7e"},
+    {file = "pyzmq-25.0.0-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:610d2d112acd4e5501fac31010064a6c6efd716ceb968e443cae0059eb7b86de"},
+    {file = "pyzmq-25.0.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3594c0ff604e685d7e907860b61d0e10e46c74a9ffca168f6e9e50ea934ee440"},
+    {file = "pyzmq-25.0.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:c21a5f4e54a807df5afdef52b6d24ec1580153a6bcf0607f70a6e1d9fa74c5c3"},
+    {file = "pyzmq-25.0.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:4725412e27612f0d7d7c2f794d89807ad0227c2fc01dd6146b39ada49c748ef9"},
+    {file = "pyzmq-25.0.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:4d3d604fe0a67afd1aff906e54da557a5203368a99dcc50a70eef374f1d2abef"},
+    {file = "pyzmq-25.0.0-cp39-cp39-win32.whl", hash = "sha256:3670e8c5644768f214a3b598fe46378a4a6f096d5fb82a67dfd3440028460565"},
+    {file = "pyzmq-25.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:e99629a976809fe102ef73e856cf4b2660acd82a412a51e80ba2215e523dfd0a"},
+    {file = "pyzmq-25.0.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:66509c48f7446b640eeae24b60c9c1461799a27b1b0754e438582e36b5af3315"},
+    {file = "pyzmq-25.0.0-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:a9c464cc508177c09a5a6122b67f978f20e2954a21362bf095a0da4647e3e908"},
+    {file = "pyzmq-25.0.0-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:28bcb2e66224a7ac2843eb632e4109d6b161479e7a2baf24e37210461485b4f1"},
+    {file = "pyzmq-25.0.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a0e7ef9ac807db50b4eb6f534c5dcc22f998f5dae920cc28873d2c1d080a4fc9"},
+    {file = "pyzmq-25.0.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:5050f5c50b58a6e38ccaf9263a356f74ef1040f5ca4030225d1cb1a858c5b7b6"},
+    {file = "pyzmq-25.0.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:2a73af6504e0d2805e926abf136ebf536735a13c22f709be7113c2ec65b4bec3"},
+    {file = "pyzmq-25.0.0-pp38-pypy38_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:0e8d00228db627ddd1b418c7afd81820b38575f237128c9650365f2dd6ac3443"},
+    {file = "pyzmq-25.0.0-pp38-pypy38_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:5605621f2181f20b71f13f698944deb26a0a71af4aaf435b34dd90146092d530"},
+    {file = "pyzmq-25.0.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6136bfb0e5a9cf8c60c6ac763eb21f82940a77e6758ea53516c8c7074f4ff948"},
+    {file = "pyzmq-25.0.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:0a90b2480a26aef7c13cff18703ba8d68e181facb40f78873df79e6d42c1facc"},
+    {file = "pyzmq-25.0.0-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:00c94fd4c9dd3c95aace0c629a7fa713627a5c80c1819326b642adf6c4b8e2a2"},
+    {file = "pyzmq-25.0.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:20638121b0bdc80777ce0ec8c1f14f1ffec0697a1f88f0b564fa4a23078791c4"},
+    {file = "pyzmq-25.0.0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b6f75b4b8574f3a8a0d6b4b52606fc75b82cb4391471be48ab0b8677c82f9ed4"},
+    {file = "pyzmq-25.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4cbb885f347eba7ab7681c450dee5b14aed9f153eec224ec0c3f299273d9241f"},
+    {file = "pyzmq-25.0.0-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:c48f257da280b3be6c94e05bd575eddb1373419dbb1a72c3ce64e88f29d1cd6d"},
+    {file = "pyzmq-25.0.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:866eabf7c1315ef2e93e34230db7cbf672e0d7c626b37c11f7e870c8612c3dcc"},
+    {file = "pyzmq-25.0.0.tar.gz", hash = "sha256:f330a1a2c7f89fd4b0aa4dcb7bf50243bf1c8da9a2f1efc31daf57a2046b31f2"},
+]
+
+[package.dependencies]
+cffi = {version = "*", markers = "implementation_name == \"pypy\""}
+
 [[package]]
 name = "requests"
 version = "2.28.2"
@@ -1864,33 +2365,43 @@ socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
-name = "requirements-detector"
-version = "0.7"
-description = "Python tool to find and list requirements of a Python project"
-category = "dev"
-optional = false
-python-versions = "*"
-files = [
-    {file = "requirements-detector-0.7.tar.gz", hash = "sha256:0d1e13e61ed243f9c3c86e6cbb19980bcb3a0e0619cde2ec1f3af70fdbee6f7b"},
+name = "scipy"
+version = "1.10.1"
+description = "Fundamental algorithms for scientific computing in Python"
+category = "dev"
+optional = false
+python-versions = "<3.12,>=3.8"
+files = [
+    {file = "scipy-1.10.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e7354fd7527a4b0377ce55f286805b34e8c54b91be865bac273f527e1b839019"},
+    {file = "scipy-1.10.1-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:4b3f429188c66603a1a5c549fb414e4d3bdc2a24792e061ffbd607d3d75fd84e"},
+    {file = "scipy-1.10.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1553b5dcddd64ba9a0d95355e63fe6c3fc303a8fd77c7bc91e77d61363f7433f"},
+    {file = "scipy-1.10.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c0ff64b06b10e35215abce517252b375e580a6125fd5fdf6421b98efbefb2d2"},
+    {file = "scipy-1.10.1-cp310-cp310-win_amd64.whl", hash = "sha256:fae8a7b898c42dffe3f7361c40d5952b6bf32d10c4569098d276b4c547905ee1"},
+    {file = "scipy-1.10.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0f1564ea217e82c1bbe75ddf7285ba0709ecd503f048cb1236ae9995f64217bd"},
+    {file = "scipy-1.10.1-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:d925fa1c81b772882aa55bcc10bf88324dadb66ff85d548c71515f6689c6dac5"},
+    {file = "scipy-1.10.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:aaea0a6be54462ec027de54fca511540980d1e9eea68b2d5c1dbfe084797be35"},
+    {file = "scipy-1.10.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:15a35c4242ec5f292c3dd364a7c71a61be87a3d4ddcc693372813c0b73c9af1d"},
+    {file = "scipy-1.10.1-cp311-cp311-win_amd64.whl", hash = "sha256:43b8e0bcb877faf0abfb613d51026cd5cc78918e9530e375727bf0625c82788f"},
+    {file = "scipy-1.10.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:5678f88c68ea866ed9ebe3a989091088553ba12c6090244fdae3e467b1139c35"},
+    {file = "scipy-1.10.1-cp38-cp38-macosx_12_0_arm64.whl", hash = "sha256:39becb03541f9e58243f4197584286e339029e8908c46f7221abeea4b749fa88"},
+    {file = "scipy-1.10.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bce5869c8d68cf383ce240e44c1d9ae7c06078a9396df68ce88a1230f93a30c1"},
+    {file = "scipy-1.10.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:07c3457ce0b3ad5124f98a86533106b643dd811dd61b548e78cf4c8786652f6f"},
+    {file = "scipy-1.10.1-cp38-cp38-win_amd64.whl", hash = "sha256:049a8bbf0ad95277ffba9b3b7d23e5369cc39e66406d60422c8cfef40ccc8415"},
+    {file = "scipy-1.10.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:cd9f1027ff30d90618914a64ca9b1a77a431159df0e2a195d8a9e8a04c78abf9"},
+    {file = "scipy-1.10.1-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:79c8e5a6c6ffaf3a2262ef1be1e108a035cf4f05c14df56057b64acc5bebffb6"},
+    {file = "scipy-1.10.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:51af417a000d2dbe1ec6c372dfe688e041a7084da4fdd350aeb139bd3fb55353"},
+    {file = "scipy-1.10.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1b4735d6c28aad3cdcf52117e0e91d6b39acd4272f3f5cd9907c24ee931ad601"},
+    {file = "scipy-1.10.1-cp39-cp39-win_amd64.whl", hash = "sha256:7ff7f37b1bf4417baca958d254e8e2875d0cc23aaadbe65b3d5b3077b0eb23ea"},
+    {file = "scipy-1.10.1.tar.gz", hash = "sha256:2cf9dfb80a7b4589ba4c40ce7588986d6d5cebc5457cad2c2880f6bc2d42f3a5"},
 ]
 
 [package.dependencies]
-astroid = ">=1.4"
-
-[[package]]
-name = "setoptconf-tmp"
-version = "0.3.1"
-description = "A module for retrieving program settings from various sources in a consistant method."
-category = "dev"
-optional = false
-python-versions = "*"
-files = [
-    {file = "setoptconf-tmp-0.3.1.tar.gz", hash = "sha256:e0480addd11347ba52f762f3c4d8afa3e10ad0affbc53e3ffddc0ca5f27d5778"},
-    {file = "setoptconf_tmp-0.3.1-py3-none-any.whl", hash = "sha256:76035d5cd1593d38b9056ae12d460eca3aaa34ad05c315b69145e138ba80a745"},
-]
+numpy = ">=1.19.5,<1.27.0"
 
 [package.extras]
-yaml = ["pyyaml"]
+dev = ["click", "doit (>=0.36.0)", "flake8", "mypy", "pycodestyle", "pydevtool", "rich-click", "typing_extensions"]
+doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-design (>=0.2.0)"]
+test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
 
 [[package]]
 name = "setuptools"
@@ -2149,6 +2660,26 @@ files = [
 lint = ["docutils-stubs", "flake8", "mypy"]
 test = ["pytest"]
 
+[[package]]
+name = "stack-data"
+version = "0.6.2"
+description = "Extract data from python stack frames and tracebacks for informative displays"
+category = "dev"
+optional = false
+python-versions = "*"
+files = [
+    {file = "stack_data-0.6.2-py3-none-any.whl", hash = "sha256:cbb2a53eb64e5785878201a97ed7c7b94883f48b87bfb0bbe8b623c74679e4a8"},
+    {file = "stack_data-0.6.2.tar.gz", hash = "sha256:32d2dd0376772d01b6cb9fc996f3c8b57a357089dec328ed4b6553d037eaf815"},
+]
+
+[package.dependencies]
+asttokens = ">=2.1.0"
+executing = ">=1.2.0"
+pure-eval = "*"
+
+[package.extras]
+tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
+
 [[package]]
 name = "toml"
 version = "0.10.2"
@@ -2174,15 +2705,24 @@ files = [
 ]
 
 [[package]]
-name = "tomlkit"
-version = "0.11.6"
-description = "Style preserving TOML library"
+name = "tornado"
+version = "6.2"
+description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
 category = "dev"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">= 3.7"
 files = [
-    {file = "tomlkit-0.11.6-py3-none-any.whl", hash = "sha256:07de26b0d8cfc18f871aec595fda24d95b08fef89d147caa861939f37230bf4b"},
-    {file = "tomlkit-0.11.6.tar.gz", hash = "sha256:71b952e5721688937fb02cf9d354dbcf0785066149d2855e44531ebdd2b65d73"},
+    {file = "tornado-6.2-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:20f638fd8cc85f3cbae3c732326e96addff0a15e22d80f049e00121651e82e72"},
+    {file = "tornado-6.2-cp37-abi3-macosx_10_9_x86_64.whl", hash = "sha256:87dcafae3e884462f90c90ecc200defe5e580a7fbbb4365eda7c7c1eb809ebc9"},
+    {file = "tornado-6.2-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ba09ef14ca9893954244fd872798b4ccb2367c165946ce2dd7376aebdde8e3ac"},
+    {file = "tornado-6.2-cp37-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b8150f721c101abdef99073bf66d3903e292d851bee51910839831caba341a75"},
+    {file = "tornado-6.2-cp37-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d3a2f5999215a3a06a4fc218026cd84c61b8b2b40ac5296a6db1f1451ef04c1e"},
+    {file = "tornado-6.2-cp37-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:5f8c52d219d4995388119af7ccaa0bcec289535747620116a58d830e7c25d8a8"},
+    {file = "tornado-6.2-cp37-abi3-musllinux_1_1_i686.whl", hash = "sha256:6fdfabffd8dfcb6cf887428849d30cf19a3ea34c2c248461e1f7d718ad30b66b"},
+    {file = "tornado-6.2-cp37-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:1d54d13ab8414ed44de07efecb97d4ef7c39f7438cf5e976ccd356bebb1b5fca"},
+    {file = "tornado-6.2-cp37-abi3-win32.whl", hash = "sha256:5c87076709343557ef8032934ce5f637dbb552efa7b21d08e89ae7619ed0eb23"},
+    {file = "tornado-6.2-cp37-abi3-win_amd64.whl", hash = "sha256:e5f923aa6a47e133d1cf87d60700889d7eae68988704e20c75fb2d65677a8e4b"},
+    {file = "tornado-6.2.tar.gz", hash = "sha256:9b630419bde84ec666bfd7ea0a4cb2a8a651c2d5cccdbdd1972a0c859dfc3c13"},
 ]
 
 [[package]]
@@ -2206,6 +2746,22 @@ notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
 
+[[package]]
+name = "traitlets"
+version = "5.9.0"
+description = "Traitlets Python configuration system"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "traitlets-5.9.0-py3-none-any.whl", hash = "sha256:9e6ec080259b9a5940c797d58b613b5e31441c2257b87c2e795c5228ae80d2d8"},
+    {file = "traitlets-5.9.0.tar.gz", hash = "sha256:f6cde21a9c68cf756af02035f72d5a723bf607e862e7be33ece505abf4a3bad9"},
+]
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"]
+
 [[package]]
 name = "types-requests"
 version = "2.28.11.15"
@@ -2281,26 +2837,17 @@ wrapt = "*"
 yarl = "*"
 
 [[package]]
-name = "virtualenv"
-version = "20.19.0"
-description = "Virtual Python Environment builder"
+name = "wcwidth"
+version = "0.2.6"
+description = "Measures the displayed width of unicode strings in a terminal"
 category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = "*"
 files = [
-    {file = "virtualenv-20.19.0-py3-none-any.whl", hash = "sha256:54eb59e7352b573aa04d53f80fc9736ed0ad5143af445a1e539aada6eb947dd1"},
-    {file = "virtualenv-20.19.0.tar.gz", hash = "sha256:37a640ba82ed40b226599c522d411e4be5edb339a0c0de030c0dc7b646d61590"},
+    {file = "wcwidth-0.2.6-py2.py3-none-any.whl", hash = "sha256:795b138f6875577cd91bba52baf9e445cd5118fd32723b460e30a0af30ea230e"},
+    {file = "wcwidth-0.2.6.tar.gz", hash = "sha256:a5220780a404dbe3353789870978e472cfe477761f06ee55077256e509b156d0"},
 ]
 
-[package.dependencies]
-distlib = ">=0.3.6,<1"
-filelock = ">=3.4.1,<4"
-platformdirs = ">=2.4,<4"
-
-[package.extras]
-docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=22.12)"]
-test = ["covdefaults (>=2.2.2)", "coverage (>=7.1)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23)", "pytest (>=7.2.1)", "pytest-env (>=0.8.1)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.10)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)"]
-
 [[package]]
 name = "webencodings"
 version = "0.5.1"
@@ -2529,5 +3076,5 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.8, <4.0"
-content-hash = "281947ac037b6a5458788dfe7fd54cd42bd39d68b6d7482cc8c26727e00cfb88"
+python-versions = ">=3.8, <3.12"
+content-hash = "39e6bcef33f12e24ea815120249cfd7475866b46e33cc30fb82819c64933a561"
diff --git a/pyproject.toml b/pyproject.toml
index 6f11d6b..cb9750a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -16,6 +16,7 @@ classifiers = [
     "Environment :: Other Environment",
     "Intended Audience :: Developers",
     "Intended Audience :: Science/Research",
+    "Topic :: Scientific/Engineering :: Hydrology",
     "Topic :: Scientific/Engineering :: Atmospheric Science",
     "Programming Language :: Python",
     "Programming Language :: Python :: 3",
@@ -25,65 +26,71 @@ classifiers = [
     "Programming Language :: Python :: 3.11",
 ]
 
-[build-system]
-requires = [
-    "poetry-core>=1.0.0",
-    "poetry-dynamic-versioning",
-]
-build-backend = "poetry_dynamic_versioning.backend"
-
-[tool.poetry-dynamic-versioning]
-enable = true
-
 [tool.poetry.dependencies]
-python = ">=3.8, <4.0"
+python = ">=3.8, <3.12"
+beautifulsoup4 = "*"
+dataretrieval = "*"
 erddapy = "*"
+geopandas = "*"
+html5lib = "*"
+limits = "*"
+lxml = "*"
+numpy = "*"
 pandas = "*"
 pydantic = "*"
 requests = "*"
-beautifulsoup4 = "*"
-geopandas = "*"
-xarray = "*"
 Shapely = "*"
-limits = "*"
 tqdm = "*"
-html5lib = "*"
-numpy = "*"
-lxml = "*"
-dataretrieval = "*"
+xarray = "*"
 
-[tool.poetry.dev-dependencies]
-mypy = ">=0.991"
-pre-commit = ">=2.0"
-prospector = "<1.8"   # due to https://github.com/PyCQA/prospector/issues/557
-pytest = ">=6.0"
-pytest-xdist = "*"
+[tool.poetry.group.dev.dependencies]
+covdefaults = "*"
+coverage = {version = "*", extras = ["toml"]}
+mypy = ">=1"
+pytest = "*"
 pytest-cov = ">=3.0"
 pytest-recording = "*"
+pytest-xdist = "*"
 types-requests = "*"
-sphinx = '*'
-sphinx-rtd-theme = '*'
+
+[tool.poetry.group.docs.dependencies]
 dunamai = "*"
 m2r2 = "*"
-deptry = "*"
+sphinx = '*'
+sphinx-rtd-theme = '*'
 toml = "*"
 
+[tool.poetry.group.jupyter.dependencies]
+ipykernel = "*"
+matplotlib = "*"
+scipy = "*"
+
+[tool.poetry-dynamic-versioning]
+enable = true
+dirty = true
+
+[build-system]
+requires = [
+    "poetry-core>=1.0.0",
+    "poetry-dynamic-versioning",
+]
+build-backend = "poetry_dynamic_versioning.backend"
+
 [tool.black]
 line-length = 108
-target-version = ['py39']
+target-version = ['py38']
 
 [tool.pytest.ini_options]
-minversion = "7.0"
 addopts = "-ra --verbose --showlocals --tb=short"
 testpaths = ["tests"]
 log_cli = true
 filterwarnings = [
     'ignore:distutils Version classes are deprecated. Use packaging.version instead:DeprecationWarning',
+    'ignore:Deprecated call to `pkg_resources.declare_namespace:DeprecationWarning',
 ]
 
-
 [tool.mypy]
-python_version = "3.9"
+python_version = "3.8"
 plugins = ["pydantic.mypy"]
 show_error_codes = true
 show_column_numbers = true
@@ -118,15 +125,27 @@ init_typed = true
 warn_required_dynamic_aliases = true
 warn_untyped_fields = true
 
-
-[tool.deptry]
-ignore_obsolete = []
-ignore_missing = [
-  'CERA_get_active_stations'
+[tool.ruff]
+target-version = "py38"
+line-length = 108
+select = [
+    "E",  # pycodestyle
+    "F",  # pyflakes
+    "C90",  # mccabe
 ]
-ignore_transitive = []
-ignore_misplaced_dev = [
-  'dunamai',
-  'pytest',
-  'toml',
+ignore = [
+    "E501", # line-too-long
 ]
+
+[tool.coverage.run]
+plugins = ["covdefaults"]
+source = ["searvey"]
+concurrency = [
+  "multiprocessing",
+  "thread",
+]
+parallel = true
+sigterm = true
+
+[tool.coverage.report]
+fail_under = 89.5
diff --git a/requirements/requirements-dev.txt b/requirements/requirements-dev.txt
index 92b7de4..f15301c 100644
--- a/requirements/requirements-dev.txt
+++ b/requirements/requirements-dev.txt
@@ -1,109 +1,117 @@
-alabaster==0.7.13 ; python_version >= "3.8" and python_version < "4.0"
-astroid==2.14.2 ; python_version >= "3.8" and python_version < "4.0"
-attrs==22.2.0 ; python_version >= "3.8" and python_version < "4.0"
-babel==2.12.1 ; python_version >= "3.8" and python_version < "4.0"
-beautifulsoup4==4.11.2 ; python_version >= "3.8" and python_version < "4.0"
-certifi==2022.12.7 ; python_version >= "3.8" and python_version < "4"
-cfgv==3.3.1 ; python_version >= "3.8" and python_version < "4.0"
-chardet==5.1.0 ; python_version >= "3.8" and python_version < "4.0"
-charset-normalizer==3.0.1 ; python_version >= "3.8" and python_version < "4"
-click-plugins==1.1.1 ; python_version >= "3.8" and python_version < "4.0"
-click==8.1.3 ; python_version >= "3.8" and python_version < "4.0"
-cligj==0.7.2 ; python_version >= "3.8" and python_version < "4"
-colorama==0.4.6 ; python_version >= "3.8" and python_version < "4.0" and platform_system == "Windows" or python_version >= "3.8" and python_version < "4.0" and sys_platform == "win32"
-coverage[toml]==7.2.1 ; python_version >= "3.8" and python_version < "4.0"
-dataretrieval==1.0.2 ; python_version >= "3.8" and python_version < "4.0"
-deprecated==1.2.13 ; python_version >= "3.8" and python_version < "4.0"
-deptry==0.8.0 ; python_version >= "3.8" and python_version < "4.0"
-dill==0.3.6 ; python_version >= "3.8" and python_version < "4.0"
-distlib==0.3.6 ; python_version >= "3.8" and python_version < "4.0"
-docutils==0.19 ; python_version >= "3.8" and python_version < "4.0"
-dodgy==0.2.1 ; python_version >= "3.8" and python_version < "4.0"
-dunamai==1.16.0 ; python_version >= "3.8" and python_version < "4.0"
-erddapy==1.2.1 ; python_version >= "3.8" and python_version < "4.0"
+alabaster==0.7.13 ; python_version >= "3.8" and python_version < "3.12"
+appnope==0.1.3 ; python_version >= "3.8" and python_version < "3.12" and platform_system == "Darwin" or python_version >= "3.8" and python_version < "3.12" and sys_platform == "darwin"
+asttokens==2.2.1 ; python_version >= "3.8" and python_version < "3.12"
+attrs==22.2.0 ; python_version >= "3.8" and python_version < "3.12"
+babel==2.12.1 ; python_version >= "3.8" and python_version < "3.12"
+backcall==0.2.0 ; python_version >= "3.8" and python_version < "3.12"
+beautifulsoup4==4.11.2 ; python_version >= "3.8" and python_version < "3.12"
+certifi==2022.12.7 ; python_version >= "3.8" and python_version < "3.12"
+cffi==1.15.1 ; python_version >= "3.8" and python_version < "3.12" and implementation_name == "pypy"
+charset-normalizer==3.0.1 ; python_version >= "3.8" and python_version < "3.12"
+click-plugins==1.1.1 ; python_version >= "3.8" and python_version < "3.12"
+click==8.1.3 ; python_version >= "3.8" and python_version < "3.12"
+cligj==0.7.2 ; python_version >= "3.8" and python_version < "3.12"
+colorama==0.4.6 ; python_version >= "3.8" and python_version < "3.12" and platform_system == "Windows" or python_version >= "3.8" and python_version < "3.12" and sys_platform == "win32"
+comm==0.1.2 ; python_version >= "3.8" and python_version < "3.12"
+contourpy==1.0.7 ; python_version >= "3.8" and python_version < "3.12"
+covdefaults==2.2.2 ; python_version >= "3.8" and python_version < "3.12"
+coverage==7.2.1 ; python_version >= "3.8" and python_version < "3.12"
+coverage[toml]==7.2.1 ; python_version >= "3.8" and python_version < "3.12"
+cycler==0.11.0 ; python_version >= "3.8" and python_version < "3.12"
+dataretrieval==1.0.2 ; python_version >= "3.8" and python_version < "3.12"
+debugpy==1.6.6 ; python_version >= "3.8" and python_version < "3.12"
+decorator==5.1.1 ; python_version >= "3.8" and python_version < "3.12"
+deprecated==1.2.13 ; python_version >= "3.8" and python_version < "3.12"
+docutils==0.19 ; python_version >= "3.8" and python_version < "3.12"
+dunamai==1.16.0 ; python_version >= "3.8" and python_version < "3.12"
+erddapy==1.2.1 ; python_version >= "3.8" and python_version < "3.12"
 exceptiongroup==1.1.0 ; python_version >= "3.8" and python_version < "3.11"
-execnet==1.9.0 ; python_version >= "3.8" and python_version < "4.0"
-filelock==3.9.0 ; python_version >= "3.8" and python_version < "4.0"
-fiona==1.9.1 ; python_version >= "3.8" and python_version < "4.0"
-flake8-polyfill==1.0.2 ; python_version >= "3.8" and python_version < "4.0"
-flake8==2.3.0 ; python_version >= "3.8" and python_version < "4.0"
-geopandas==0.12.2 ; python_version >= "3.8" and python_version < "4.0"
-html5lib==1.1 ; python_version >= "3.8" and python_version < "4.0"
-identify==2.5.18 ; python_version >= "3.8" and python_version < "4.0"
-idna==3.4 ; python_version >= "3.8" and python_version < "4"
-imagesize==1.4.1 ; python_version >= "3.8" and python_version < "4.0"
+execnet==1.9.0 ; python_version >= "3.8" and python_version < "3.12"
+executing==1.2.0 ; python_version >= "3.8" and python_version < "3.12"
+fiona==1.9.1 ; python_version >= "3.8" and python_version < "3.12"
+fonttools==4.38.0 ; python_version >= "3.8" and python_version < "3.12"
+geopandas==0.12.2 ; python_version >= "3.8" and python_version < "3.12"
+html5lib==1.1 ; python_version >= "3.8" and python_version < "3.12"
+idna==3.4 ; python_version >= "3.8" and python_version < "3.12"
+imagesize==1.4.1 ; python_version >= "3.8" and python_version < "3.12"
 importlib-metadata==6.0.0 ; python_version >= "3.8" and python_version < "3.10"
-iniconfig==2.0.0 ; python_version >= "3.8" and python_version < "4.0"
-isort==5.12.0 ; python_version >= "3.8" and python_version < "4.0"
-jinja2==3.1.2 ; python_version >= "3.8" and python_version < "4.0"
-lazy-object-proxy==1.9.0 ; python_version >= "3.8" and python_version < "4.0"
-limits==3.2.0 ; python_version >= "3.8" and python_version < "4.0"
-lxml==4.9.2 ; python_version >= "3.8" and python_version < "4.0"
-m2r2==0.3.3.post2 ; python_version >= "3.8" and python_version < "4.0"
-markupsafe==2.1.2 ; python_version >= "3.8" and python_version < "4.0"
-mccabe==0.6.1 ; python_version >= "3.8" and python_version < "4.0"
-mistune==0.8.4 ; python_version >= "3.8" and python_version < "4.0"
-multidict==6.0.4 ; python_version >= "3.8" and python_version < "4.0"
-munch==2.5.0 ; python_version >= "3.8" and python_version < "4.0"
-mypy-extensions==1.0.0 ; python_version >= "3.8" and python_version < "4.0"
-mypy==1.0.1 ; python_version >= "3.8" and python_version < "4.0"
-nodeenv==1.7.0 ; python_version >= "3.8" and python_version < "4.0"
-numpy==1.24.2 ; python_version < "4.0" and python_version >= "3.8"
-packaging==23.0 ; python_version >= "3.8" and python_version < "4.0"
-pandas==1.5.3 ; python_version >= "3.8" and python_version < "4.0"
-pathspec==0.11.0 ; python_version >= "3.8" and python_version < "4.0"
-pep8-naming==0.10.0 ; python_version >= "3.8" and python_version < "4.0"
-pep8==1.7.1 ; python_version >= "3.8" and python_version < "4.0"
-platformdirs==3.0.0 ; python_version >= "3.8" and python_version < "4.0"
-pluggy==1.0.0 ; python_version >= "3.8" and python_version < "4.0"
-pre-commit==3.1.1 ; python_version >= "3.8" and python_version < "4.0"
-prospector==1.7.7 ; python_version >= "3.8" and python_version < "4.0"
-pycodestyle==2.8.0 ; python_version >= "3.8" and python_version < "4.0"
-pydantic==1.10.5 ; python_version >= "3.8" and python_version < "4.0"
-pydocstyle==6.3.0 ; python_version >= "3.8" and python_version < "4.0"
-pyflakes==2.5.0 ; python_version >= "3.8" and python_version < "4.0"
-pygments==2.14.0 ; python_version >= "3.8" and python_version < "4.0"
-pylint-celery==0.3 ; python_version >= "3.8" and python_version < "4.0"
-pylint-django==2.5.3 ; python_version >= "3.8" and python_version < "4.0"
-pylint-flask==0.6 ; python_version >= "3.8" and python_version < "4.0"
-pylint-plugin-utils==0.7 ; python_version >= "3.8" and python_version < "4.0"
-pylint==2.16.2 ; python_version >= "3.8" and python_version < "4.0"
-pyproj==3.4.1 ; python_version >= "3.8" and python_version < "4.0"
-pytest-cov==4.0.0 ; python_version >= "3.8" and python_version < "4.0"
-pytest-recording==0.12.2 ; python_version >= "3.8" and python_version < "4.0"
-pytest-xdist==3.2.0 ; python_version >= "3.8" and python_version < "4.0"
-pytest==7.2.1 ; python_version >= "3.8" and python_version < "4.0"
-python-dateutil==2.8.2 ; python_version >= "3.8" and python_version < "4.0"
-pytz==2022.7.1 ; python_version >= "3.8" and python_version < "4.0"
-pyyaml==6.0 ; python_version >= "3.8" and python_version < "4.0"
-requests==2.28.2 ; python_version >= "3.8" and python_version < "4"
-requirements-detector==0.7 ; python_version >= "3.8" and python_version < "4.0"
-setoptconf-tmp==0.3.1 ; python_version >= "3.8" and python_version < "4.0"
-setuptools==67.4.0 ; python_version >= "3.8" and python_version < "4.0"
-shapely==2.0.1 ; python_version >= "3.8" and python_version < "4.0"
-six==1.16.0 ; python_version >= "3.8" and python_version < "4.0"
-snowballstemmer==2.2.0 ; python_version >= "3.8" and python_version < "4.0"
-soupsieve==2.4 ; python_version >= "3.8" and python_version < "4.0"
-sphinx-rtd-theme==0.5.1 ; python_version >= "3.8" and python_version < "4.0"
-sphinx==6.1.3 ; python_version >= "3.8" and python_version < "4.0"
-sphinxcontrib-applehelp==1.0.4 ; python_version >= "3.8" and python_version < "4.0"
-sphinxcontrib-devhelp==1.0.2 ; python_version >= "3.8" and python_version < "4.0"
-sphinxcontrib-htmlhelp==2.0.1 ; python_version >= "3.8" and python_version < "4.0"
-sphinxcontrib-jsmath==1.0.1 ; python_version >= "3.8" and python_version < "4.0"
-sphinxcontrib-qthelp==1.0.3 ; python_version >= "3.8" and python_version < "4.0"
-sphinxcontrib-serializinghtml==1.1.5 ; python_version >= "3.8" and python_version < "4.0"
-toml==0.10.2 ; python_version >= "3.8" and python_version < "4.0"
+importlib-resources==5.12.0 ; python_version >= "3.8" and python_version < "3.10"
+iniconfig==2.0.0 ; python_version >= "3.8" and python_version < "3.12"
+ipykernel==6.21.2 ; python_version >= "3.8" and python_version < "3.12"
+ipython==8.11.0 ; python_version >= "3.8" and python_version < "3.12"
+jedi==0.18.2 ; python_version >= "3.8" and python_version < "3.12"
+jinja2==3.1.2 ; python_version >= "3.8" and python_version < "3.12"
+jupyter-client==8.0.3 ; python_version >= "3.8" and python_version < "3.12"
+jupyter-core==5.2.0 ; python_version >= "3.8" and python_version < "3.12"
+kiwisolver==1.4.4 ; python_version >= "3.8" and python_version < "3.12"
+limits==3.2.0 ; python_version >= "3.8" and python_version < "3.12"
+lxml==4.9.2 ; python_version >= "3.8" and python_version < "3.12"
+m2r2==0.3.3.post2 ; python_version >= "3.8" and python_version < "3.12"
+markupsafe==2.1.2 ; python_version >= "3.8" and python_version < "3.12"
+matplotlib-inline==0.1.6 ; python_version >= "3.8" and python_version < "3.12"
+matplotlib==3.7.0 ; python_version >= "3.8" and python_version < "3.12"
+mistune==0.8.4 ; python_version >= "3.8" and python_version < "3.12"
+multidict==6.0.4 ; python_version >= "3.8" and python_version < "3.12"
+munch==2.5.0 ; python_version >= "3.8" and python_version < "3.12"
+mypy-extensions==1.0.0 ; python_version >= "3.8" and python_version < "3.12"
+mypy==1.0.1 ; python_version >= "3.8" and python_version < "3.12"
+nest-asyncio==1.5.6 ; python_version >= "3.8" and python_version < "3.12"
+numpy==1.24.2 ; python_version >= "3.8" and python_version < "3.12"
+packaging==23.0 ; python_version >= "3.8" and python_version < "3.12"
+pandas==1.5.3 ; python_version >= "3.8" and python_version < "3.12"
+parso==0.8.3 ; python_version >= "3.8" and python_version < "3.12"
+pexpect==4.8.0 ; python_version >= "3.8" and python_version < "3.12" and sys_platform != "win32"
+pickleshare==0.7.5 ; python_version >= "3.8" and python_version < "3.12"
+pillow==9.4.0 ; python_version >= "3.8" and python_version < "3.12"
+platformdirs==3.0.0 ; python_version >= "3.8" and python_version < "3.12"
+pluggy==1.0.0 ; python_version >= "3.8" and python_version < "3.12"
+prompt-toolkit==3.0.38 ; python_version >= "3.8" and python_version < "3.12"
+psutil==5.9.4 ; python_version >= "3.8" and python_version < "3.12"
+ptyprocess==0.7.0 ; python_version >= "3.8" and python_version < "3.12" and sys_platform != "win32"
+pure-eval==0.2.2 ; python_version >= "3.8" and python_version < "3.12"
+pycparser==2.21 ; python_version >= "3.8" and python_version < "3.12" and implementation_name == "pypy"
+pydantic==1.10.5 ; python_version >= "3.8" and python_version < "3.12"
+pygments==2.14.0 ; python_version >= "3.8" and python_version < "3.12"
+pyparsing==3.0.9 ; python_version >= "3.8" and python_version < "3.12"
+pyproj==3.4.1 ; python_version >= "3.8" and python_version < "3.12"
+pytest-cov==4.0.0 ; python_version >= "3.8" and python_version < "3.12"
+pytest-recording==0.12.2 ; python_version >= "3.8" and python_version < "3.12"
+pytest-xdist==3.2.0 ; python_version >= "3.8" and python_version < "3.12"
+pytest==7.2.1 ; python_version >= "3.8" and python_version < "3.12"
+python-dateutil==2.8.2 ; python_version >= "3.8" and python_version < "3.12"
+pytz==2022.7.1 ; python_version >= "3.8" and python_version < "3.12"
+pywin32==305 ; sys_platform == "win32" and platform_python_implementation != "PyPy" and python_version >= "3.8" and python_version < "3.12"
+pyyaml==6.0 ; python_version >= "3.8" and python_version < "3.12"
+pyzmq==25.0.0 ; python_version >= "3.8" and python_version < "3.12"
+requests==2.28.2 ; python_version >= "3.8" and python_version < "3.12"
+scipy==1.10.1 ; python_version >= "3.8" and python_version < "3.12"
+setuptools==67.4.0 ; python_version >= "3.8" and python_version < "3.12"
+shapely==2.0.1 ; python_version >= "3.8" and python_version < "3.12"
+six==1.16.0 ; python_version >= "3.8" and python_version < "3.12"
+snowballstemmer==2.2.0 ; python_version >= "3.8" and python_version < "3.12"
+soupsieve==2.4 ; python_version >= "3.8" and python_version < "3.12"
+sphinx-rtd-theme==0.5.1 ; python_version >= "3.8" and python_version < "3.12"
+sphinx==6.1.3 ; python_version >= "3.8" and python_version < "3.12"
+sphinxcontrib-applehelp==1.0.4 ; python_version >= "3.8" and python_version < "3.12"
+sphinxcontrib-devhelp==1.0.2 ; python_version >= "3.8" and python_version < "3.12"
+sphinxcontrib-htmlhelp==2.0.1 ; python_version >= "3.8" and python_version < "3.12"
+sphinxcontrib-jsmath==1.0.1 ; python_version >= "3.8" and python_version < "3.12"
+sphinxcontrib-qthelp==1.0.3 ; python_version >= "3.8" and python_version < "3.12"
+sphinxcontrib-serializinghtml==1.1.5 ; python_version >= "3.8" and python_version < "3.12"
+stack-data==0.6.2 ; python_version >= "3.8" and python_version < "3.12"
+toml==0.10.2 ; python_version >= "3.8" and python_version < "3.12"
 tomli==2.0.1 ; python_version >= "3.8" and python_full_version <= "3.11.0a6"
-tomlkit==0.11.6 ; python_version >= "3.8" and python_version < "4.0"
-tqdm==4.64.1 ; python_version >= "3.8" and python_version < "4.0"
-types-requests==2.28.11.15 ; python_version >= "3.8" and python_version < "4.0"
-types-urllib3==1.26.25.8 ; python_version >= "3.8" and python_version < "4.0"
-typing-extensions==4.5.0 ; python_version >= "3.8" and python_version < "4.0"
-urllib3==1.26.14 ; python_version >= "3.8" and python_version < "4"
-vcrpy==4.2.1 ; python_version >= "3.8" and python_version < "4.0"
-virtualenv==20.19.0 ; python_version >= "3.8" and python_version < "4.0"
-webencodings==0.5.1 ; python_version >= "3.8" and python_version < "4.0"
-wrapt==1.15.0 ; python_version < "4.0" and python_version >= "3.8"
-xarray==2023.1.0 ; python_version >= "3.8" and python_version < "4.0"
-yarl==1.8.2 ; python_version >= "3.8" and python_version < "4.0"
+tornado==6.2 ; python_version >= "3.8" and python_version < "3.12"
+tqdm==4.64.1 ; python_version >= "3.8" and python_version < "3.12"
+traitlets==5.9.0 ; python_version >= "3.8" and python_version < "3.12"
+types-requests==2.28.11.15 ; python_version >= "3.8" and python_version < "3.12"
+types-urllib3==1.26.25.8 ; python_version >= "3.8" and python_version < "3.12"
+typing-extensions==4.5.0 ; python_version >= "3.8" and python_version < "3.12"
+urllib3==1.26.14 ; python_version >= "3.8" and python_version < "3.12"
+vcrpy==4.2.1 ; python_version >= "3.8" and python_version < "3.12"
+wcwidth==0.2.6 ; python_version >= "3.8" and python_version < "3.12"
+webencodings==0.5.1 ; python_version >= "3.8" and python_version < "3.12"
+wrapt==1.15.0 ; python_version >= "3.8" and python_version < "3.12"
+xarray==2023.1.0 ; python_version >= "3.8" and python_version < "3.12"
+yarl==1.8.2 ; python_version >= "3.8" and python_version < "3.12"
 zipp==3.15.0 ; python_version >= "3.8" and python_version < "3.10"
diff --git a/requirements/requirements.txt b/requirements/requirements.txt
index 7aa255f..4415bee 100644
--- a/requirements/requirements.txt
+++ b/requirements/requirements.txt
@@ -1,36 +1,36 @@
-attrs==22.2.0 ; python_version >= "3.8" and python_version < "4.0"
-beautifulsoup4==4.11.2 ; python_version >= "3.8" and python_version < "4.0"
-certifi==2022.12.7 ; python_version >= "3.8" and python_version < "4"
-charset-normalizer==3.0.1 ; python_version >= "3.8" and python_version < "4"
-click-plugins==1.1.1 ; python_version >= "3.8" and python_version < "4.0"
-click==8.1.3 ; python_version >= "3.8" and python_version < "4.0"
-cligj==0.7.2 ; python_version >= "3.8" and python_version < "4"
-colorama==0.4.6 ; python_version >= "3.8" and python_version < "4.0" and platform_system == "Windows"
-dataretrieval==1.0.2 ; python_version >= "3.8" and python_version < "4.0"
-deprecated==1.2.13 ; python_version >= "3.8" and python_version < "4.0"
-erddapy==1.2.1 ; python_version >= "3.8" and python_version < "4.0"
-fiona==1.9.1 ; python_version >= "3.8" and python_version < "4.0"
-geopandas==0.12.2 ; python_version >= "3.8" and python_version < "4.0"
-html5lib==1.1 ; python_version >= "3.8" and python_version < "4.0"
-idna==3.4 ; python_version >= "3.8" and python_version < "4"
-limits==3.2.0 ; python_version >= "3.8" and python_version < "4.0"
-lxml==4.9.2 ; python_version >= "3.8" and python_version < "4.0"
-munch==2.5.0 ; python_version >= "3.8" and python_version < "4.0"
-numpy==1.24.2 ; python_version < "4.0" and python_version >= "3.8"
-packaging==23.0 ; python_version >= "3.8" and python_version < "4.0"
-pandas==1.5.3 ; python_version >= "3.8" and python_version < "4.0"
-pydantic==1.10.5 ; python_version >= "3.8" and python_version < "4.0"
-pyproj==3.4.1 ; python_version >= "3.8" and python_version < "4.0"
-python-dateutil==2.8.2 ; python_version >= "3.8" and python_version < "4.0"
-pytz==2022.7.1 ; python_version >= "3.8" and python_version < "4.0"
-requests==2.28.2 ; python_version >= "3.8" and python_version < "4"
-setuptools==67.4.0 ; python_version >= "3.8" and python_version < "4.0"
-shapely==2.0.1 ; python_version >= "3.8" and python_version < "4.0"
-six==1.16.0 ; python_version >= "3.8" and python_version < "4.0"
-soupsieve==2.4 ; python_version >= "3.8" and python_version < "4.0"
-tqdm==4.64.1 ; python_version >= "3.8" and python_version < "4.0"
-typing-extensions==4.5.0 ; python_version >= "3.8" and python_version < "4.0"
-urllib3==1.26.14 ; python_version >= "3.8" and python_version < "4"
-webencodings==0.5.1 ; python_version >= "3.8" and python_version < "4.0"
-wrapt==1.15.0 ; python_version >= "3.8" and python_version < "4.0"
-xarray==2023.1.0 ; python_version >= "3.8" and python_version < "4.0"
+attrs==22.2.0 ; python_version >= "3.8" and python_version < "3.12"
+beautifulsoup4==4.11.2 ; python_version >= "3.8" and python_version < "3.12"
+certifi==2022.12.7 ; python_version >= "3.8" and python_version < "3.12"
+charset-normalizer==3.0.1 ; python_version >= "3.8" and python_version < "3.12"
+click-plugins==1.1.1 ; python_version >= "3.8" and python_version < "3.12"
+click==8.1.3 ; python_version >= "3.8" and python_version < "3.12"
+cligj==0.7.2 ; python_version >= "3.8" and python_version < "3.12"
+colorama==0.4.6 ; python_version >= "3.8" and python_version < "3.12" and platform_system == "Windows"
+dataretrieval==1.0.2 ; python_version >= "3.8" and python_version < "3.12"
+deprecated==1.2.13 ; python_version >= "3.8" and python_version < "3.12"
+erddapy==1.2.1 ; python_version >= "3.8" and python_version < "3.12"
+fiona==1.9.1 ; python_version >= "3.8" and python_version < "3.12"
+geopandas==0.12.2 ; python_version >= "3.8" and python_version < "3.12"
+html5lib==1.1 ; python_version >= "3.8" and python_version < "3.12"
+idna==3.4 ; python_version >= "3.8" and python_version < "3.12"
+limits==3.2.0 ; python_version >= "3.8" and python_version < "3.12"
+lxml==4.9.2 ; python_version >= "3.8" and python_version < "3.12"
+munch==2.5.0 ; python_version >= "3.8" and python_version < "3.12"
+numpy==1.24.2 ; python_version >= "3.8" and python_version < "3.12"
+packaging==23.0 ; python_version >= "3.8" and python_version < "3.12"
+pandas==1.5.3 ; python_version >= "3.8" and python_version < "3.12"
+pydantic==1.10.5 ; python_version >= "3.8" and python_version < "3.12"
+pyproj==3.4.1 ; python_version >= "3.8" and python_version < "3.12"
+python-dateutil==2.8.2 ; python_version >= "3.8" and python_version < "3.12"
+pytz==2022.7.1 ; python_version >= "3.8" and python_version < "3.12"
+requests==2.28.2 ; python_version >= "3.8" and python_version < "3.12"
+setuptools==67.4.0 ; python_version >= "3.8" and python_version < "3.12"
+shapely==2.0.1 ; python_version >= "3.8" and python_version < "3.12"
+six==1.16.0 ; python_version >= "3.8" and python_version < "3.12"
+soupsieve==2.4 ; python_version >= "3.8" and python_version < "3.12"
+tqdm==4.64.1 ; python_version >= "3.8" and python_version < "3.12"
+typing-extensions==4.5.0 ; python_version >= "3.8" and python_version < "3.12"
+urllib3==1.26.14 ; python_version >= "3.8" and python_version < "3.12"
+webencodings==0.5.1 ; python_version >= "3.8" and python_version < "3.12"
+wrapt==1.15.0 ; python_version >= "3.8" and python_version < "3.12"
+xarray==2023.1.0 ; python_version >= "3.8" and python_version < "3.12"
diff --git a/searvey/utils.py b/searvey/utils.py
index f24768d..4692fbd 100644
--- a/searvey/utils.py
+++ b/searvey/utils.py
@@ -1,4 +1,7 @@
+from __future__ import annotations
+
 import itertools
+from typing import Dict
 from typing import Iterable
 from typing import Iterator
 from typing import List
@@ -54,7 +57,7 @@ def get_region_from_bbox_corners(
     # Not the most beautiful code in the world, but Pydantic needs keyword arguments
     # and we want to only pass arguments that have actual values and not None
     # moreover, we create a new object because mypy was complaining about redefining
-    filtered_bbox_kwargs: dict[str, float] = {k: v for (k, v) in bbox_kwargs.items() if v}
+    filtered_bbox_kwargs: Dict[str, float] = {k: v for (k, v) in bbox_kwargs.items() if v}
     bbox = klass(**filtered_bbox_kwargs)
 
     # Create the region
diff --git a/tests/ioc_test.py b/tests/ioc_test.py
index f47309b..f5a9e63 100644
--- a/tests/ioc_test.py
+++ b/tests/ioc_test.py
@@ -1,7 +1,6 @@
 import datetime
 
 import geopandas as gpd
-import numpy as np
 import pandas as pd
 import pytest
 import xarray as xr
diff --git a/tests/multi_test.py b/tests/multi_test.py
index 06be46b..7a00da1 100644
--- a/tests/multi_test.py
+++ b/tests/multi_test.py
@@ -12,7 +12,7 @@
 # Some help functions to test multithreading
 def get_threadname(**kwargs) -> Tuple[str, str]:
     # We add a tiny amount of wait_time to make sure that all the threads are getting used.
-    time.sleep(0.00001)
+    time.sleep(0.001)
     return threading.current_thread().name
 
 
diff --git a/tests/stations_test.py b/tests/stations_test.py
index 1ece8f1..848cd50 100644
--- a/tests/stations_test.py
+++ b/tests/stations_test.py
@@ -2,7 +2,6 @@
 
 import geopandas as gpd
 import pandas as pd
-import pytest
 
 from searvey import stations
 
diff --git a/tests/usgs_test.py b/tests/usgs_test.py
index ded7978..c3d5eb6 100644
--- a/tests/usgs_test.py
+++ b/tests/usgs_test.py
@@ -1,7 +1,6 @@
 import datetime
 
 import geopandas as gpd
-import numpy as np
 import pandas as pd
 import pytest
 import xarray as xr