diff --git a/.flake8 b/.flake8
new file mode 100644
index 0000000..afdc694
--- /dev/null
+++ b/.flake8
@@ -0,0 +1,6 @@
+[flake8]
+max-line-length = 89
+import-style-order = google
+inline-quotes = double
+
+ignore=T201
\ No newline at end of file
diff --git a/ecology.xlsx b/ecology.xlsx
new file mode 100644
index 0000000..496414d
Binary files /dev/null and b/ecology.xlsx differ
diff --git a/requirements.txt b/requirements.txt
index cacee3b..0b5bdbc 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,5 @@
 pandas==2.1.3
 numpy==1.26.4
 seaborn==0.12.2
-matplotlib==3.8.2
\ No newline at end of file
+matplotlib==3.8.2
+art==6.2
\ No newline at end of file
diff --git a/spandas/preprocessing.py b/spandas/preprocessing.py
index 0bf0e86..1cb3626 100644
--- a/spandas/preprocessing.py
+++ b/spandas/preprocessing.py
@@ -1,3 +1,301 @@
+# stdlib
+from dataclasses import dataclass
+
+# third party
+from art import tprint
+
+import matplotlib.pyplot as plt
+
+import pandas as pd
+
+
 # write your code here
 # it is preferable to use Classes in this module
 # also use type annotations to make code more clear and efficient to write
+
+
+@dataclass
+class Loggs:
+    """
+    Класс отвечает за вывод логов
+    Каждое поле включает или вылючает логи а конкретном этапе
+
+    test:
+    логи на этапе тестирования датасета на "приколы" (описано в object_to_float_check)
+    cols_selection:
+        Вывод выбранных колонок для очистки от выбросов
+    was_became:
+        Отвечает за вывод логов типа "было-стало" (графики и т.д.)
+    """
+
+    test: bool = False
+    cols_selection: bool = True
+    was_became: bool = True
+
+
+def get_list_of_cols(
+    df: pd.DataFrame, n=2, exclude=["id"], method: int = 1, ignore_strings: bool = True
+):
+    """
+    Returns a list like:
+    [column, column, column ...]
+    where the column is name of selected column
+
+    Parameters
+    ----------
+    df : pd.DataFrame
+        Your main pandas dataframe
+    n : int
+        The maximum allowed number of string values per column
+        len(return[column]) <= n
+    exclude : list[str], default ["id"]
+        The columns you want to exclude from the result
+    method : int in (1, 2), default 1
+        The method of selecting the columns
+    ignore_strings : bool, default True
+        Flag for ignoring strings in columns
+    """
+    if method not in (1, 2):
+        raise ValueError("Method must be 1 or 2")
+
+    result = []
+    if method == 1:
+        for col in df.columns:
+            if col in exclude:
+                continue
+            if df[col].dtype not in ["float64", "int64"] and not ignore_strings:
+                continue
+            if df[col].dtype in ["float64", "int64"]:
+                result.append(col)
+                continue
+            str_count = sum(list(map(lambda x: not str(x).isdigit(), df[col].unique())))
+            if str_count <= n:
+                result.append(col)
+        return result
+    elif method == 2:
+        for col in df.columns:
+            if (ignore_strings or df[col].dtype in ["float64", "int64"]) and df.shape[
+                0
+            ] / 100 < len(df[col].unique()) <= df.shape[0]:
+                result.append(col)
+        return result
+
+
+def mark_outliers(series: pd.Series, method: int = 1):
+    """
+    returns a Series of bool values. True if element is outlier
+
+    Parameters
+    ----------
+    series : pd.Series
+        Column from the pd.Dataframe or any other series with dtype in
+        ("int64", "float64")
+    method : int in (1, ) default 1
+        method of marking the outliers
+    ----------
+    Здесь не используется ignore_string т.к. если он True, то строки и так сохраняются
+    А если он False, то столбцы со строками вообще не должны выбираться, поэтому сюда
+    строковые значения не попадут
+    """
+    if series.dtype not in ["float64", "int64"]:
+        series_without_strings = series[
+            series.apply(lambda x: str(x).isdigit())
+        ].astype("float64")
+    if method == 1:
+        q1 = series_without_strings.quantile(0.25)
+        q3 = series_without_strings.quantile(0.75)
+        iqr = q3 - q1
+        lower_fence = q1 - 1.5 * iqr
+        upper_fence = q3 + 1.5 * iqr
+        return ~series.apply(
+            lambda x: (
+                lower_fence <= float(x) <= upper_fence if str(x).isdigit() else True
+            )
+        )
+    if method == 2:
+        #  here will be some method
+        pass
+
+
+def remove_outliers_from_series(series: pd.Series, method: int = 1):
+    """
+    returns series without outliers
+
+    Parameters
+    ----------
+    series : pd.Series
+        Column from the pd.Dataframe or any other series with dtype in
+        ("int64", "float64")
+    method : int in (1, ) default 1
+        method of marking the outliers
+    """
+    return series[~mark_outliers(series, method=method)]
+
+
+def remove_outliers(df: pd.DataFrame, columns: list[str] = [], method: int = 1):
+    """
+    returns your df without outliers
+
+    Parameters
+    ----------
+    df : pd.DataFrame
+        Your main pandas dataframe
+    method : int in (1, ) default 1
+        method of marking the outliers
+    columns: list[str] default []
+        List of columns you want to clear of outliers
+    """
+    return df[~sum(mark_outliers(df[co], method=method) for co in columns).astype(bool)]
+
+
+def print_distr(
+    df: pd.DataFrame, cols: dict, figsize: tuple[int, int] = (30, 30), bins: int = 100
+) -> tuple[bool, str]:
+    """
+    Дим, эта функция (или целый блок, их бы в отдельный подмодуль вынести)
+    Пока что она вызывается автоматически в data_preprocessing в конце, в was-became
+    logging части
+    Параметры там, всё остальное, всё поменяешь, пока-что док не нужен т.к. вызывается
+    автоматически
+    """
+    try:
+        _, axes = plt.subplots(
+            (len(cols) // 2) + (1 if len(cols) % 2 > 0 else 0),
+            2,
+            figsize=figsize,
+        )
+        i, j, max_i = (
+            0,
+            0,
+            (len(cols) // 2) + (1 if len(cols) % 2 > 0 else 0),
+        )
+        for col in cols:
+            col_of_nums = df[col].apply(
+                lambda x: (-1000 if (not str(x).isdigit() or x != x) else float(x))
+            )  # x != x only when x is NaN
+            axes[i, j].hist(col_of_nums, bins=bins)
+            axes[i, j].set_xlabel(f"Значение переменной {col}")
+            axes[i, j].set_ylabel("Частота")
+            axes[i, j].set_title(f"График распределения переменной {col}")
+            i += 1
+            if i == max_i:
+                j += 1
+                i = 0
+        plt.tight_layout()
+        plt.show()
+    except Exception as ex:
+        return False, str(ex)
+    return True, ""
+
+
+def data_preprocessing(
+    df: pd.DataFrame,
+    n: int = 2,
+    logging: Loggs = Loggs(),
+    select_method: int = 1,
+    delete_method: int = 1,
+    save_deleted: bool = True,
+    ignore_strings: bool = True,
+    exclude: list[str] = ["id"],
+):
+    """
+    Returns two values: clear dataframe and dict of deleted values
+
+    clear_df = pd.Dataframe without outliers
+
+    deleted = {  # not empty only if save_deleted is True
+        method: "iqr" or smthg else
+        column: {
+            count: (count of deleted elements)
+            deleted: {
+                id: value,
+                id: value,
+                ...
+            }
+        },
+        ...
+    }
+
+
+    Parameters
+    ----------
+    df : pd.DataFrame
+        Your main pandas dataframe
+    n : int
+        The maximum allowed number of string values per column (for selection columns)
+    exclude : list[str], default ["id"]
+        The columns you want to exclude
+    select_method : int in (1, 2), default 1
+        The method of selecting the columns
+    delete_method : int in (1, ), default 1
+        The method of deleting the outliers
+    ignore_strings : bool, default True
+        Flag for ignoring strings in columns
+    save_deleted : bool, default True
+        Flag for saving and returns deleted values
+    logging : Loggs
+        object of class Loggs (it consists of flags for logging, look class Loggs)
+    """
+    df = object_to_float_check(df, logging=logging.test)
+
+    cols = get_list_of_cols(
+        df=df, n=n, exclude=exclude, method=select_method, ignore_strings=ignore_strings
+    )
+
+    if logging.cols_selection:
+        tprint("Selected cols:")
+        print()
+        print(*cols, sep=" | ")
+        tprint("__________")
+
+    clear_df = df.copy(deep=True)
+    deleted = {}
+    for col in cols:
+        marks = mark_outliers(clear_df[col], method=delete_method)
+        if save_deleted:
+            deleted[col] = {}
+            deleted[col]["count"] = sum(marks)
+            deleted[col]["deleted"] = dict(
+                zip(
+                    list(clear_df[marks][col].keys()), list(clear_df[marks][col].values)
+                )
+            )
+            print(f"column: {col} => deleted: {deleted[col]['count']}")
+        clear_df = clear_df[~marks]
+    if logging.was_became:
+        tprint("WAS:")
+        print_distr(df, cols, (10, 13))
+        tprint("__________")
+        tprint("BECAME:")
+        print_distr(clear_df, cols, (10, 13))
+    return clear_df, deleted
+
+
+def object_to_float_check(df: pd.DataFrame, autofix: bool = True, logging=False):
+    """
+    Герман попросил
+    Идея в чём, в датасете могут быть столбцы типа object но при этом в них только числа
+    Эта фанка это находит и меняет тип столбца
+    Всегда вызывается автоматически из data_preprocessing
+
+    Parameters
+    ----------
+    df : pd.DataFrame
+        Your main pandas dataframe
+    autofix : bool default True
+        Flag for autofixing the problem
+    logging : bool default False
+        Flag for logging the process
+    """
+    testing = df.select_dtypes(include="object")
+    bad_columns = []
+    for col in testing.columns:
+        if sum(testing[col].apply(lambda x: not str(x).isdigit())) == 0:
+            bad_columns.append(col)
+    if bad_columns and logging:
+        print(f'Найдены "плохие столбцы" вот их список: {" | ".join(bad_columns)}')
+    if autofix:
+        for col in bad_columns:
+            df[col] = df[col].astype(float)
+
+    return df
diff --git a/test.ipynb b/test.ipynb
new file mode 100644
index 0000000..025a843
--- /dev/null
+++ b/test.ipynb
@@ -0,0 +1,1293 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from spandas.preprocessing import data_preprocessing, Loggs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Здесь пример быстрого использования библиотеки"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "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>id</th>\n",
+       "      <th>a4a</th>\n",
+       "      <th>a6a</th>\n",
+       "      <th>a2</th>\n",
+       "      <th>a0</th>\n",
+       "      <th>b1</th>\n",
+       "      <th>b5</th>\n",
+       "      <th>b7a</th>\n",
+       "      <th>d1a1x</th>\n",
+       "      <th>g1a</th>\n",
+       "      <th>...</th>\n",
+       "      <th>BMGc23i</th>\n",
+       "      <th>BMGc23j</th>\n",
+       "      <th>BMGc24</th>\n",
+       "      <th>BMGc25</th>\n",
+       "      <th>BMGc27</th>\n",
+       "      <th>BMGd6</th>\n",
+       "      <th>BMGd7</th>\n",
+       "      <th>BMGe1</th>\n",
+       "      <th>BMGe2</th>\n",
+       "      <th>BMGe2u</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>22</td>\n",
+       "      <td>Готовые Металлические Изделия</td>\n",
+       "      <td>Малый</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Производство</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2007</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Производство Готовых Строительных Металлически...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Модернизация машин и оборудования</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>100000</td>\n",
+       "      <td>20000</td>\n",
+       "      <td>Литры</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>29</td>\n",
+       "      <td>Машины и оборудование</td>\n",
+       "      <td>Крупный</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Производство</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2002</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Производство Насосов И Компрессоров</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Модернизация машин и оборудования</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не является приоритетом по сравнению с другими...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>160000</td>\n",
+       "      <td>18500</td>\n",
+       "      <td>Литры</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34</td>\n",
+       "      <td>Другое Производство</td>\n",
+       "      <td>Средний</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Производство</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2005</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Производство Алюминиевых И Медных Проводов, Си...</td>\n",
+       "      <td>100</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нехватка финансовых ресурсов</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>50</td>\n",
+       "      <td>Готовые Металлические Изделия</td>\n",
+       "      <td>Малый</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Другие услуги</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Строительство жилых и нежилых зданий</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Операционный и/ или технический риск</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>56</td>\n",
+       "      <td>Другие Услуги</td>\n",
+       "      <td>Малый</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Другие услуги</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2002</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Оптовая Продажа Офисной Мебели</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Не применимо</td>\n",
+       "      <td>Модернизация машин и оборудования</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нехватка финансовых ресурсов</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>100000</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>Литры</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 48 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   id                            a4a      a6a                             a2  \\\n",
+       "0  22  Готовые Металлические Изделия    Малый  Центральный Федеральный округ   \n",
+       "1  29          Машины и оборудование  Крупный  Центральный Федеральный округ   \n",
+       "2  34            Другое Производство  Средний  Центральный Федеральный округ   \n",
+       "3  50  Готовые Металлические Изделия    Малый  Центральный Федеральный округ   \n",
+       "4  56                  Другие Услуги    Малый  Центральный Федеральный округ   \n",
+       "\n",
+       "              a0                                                 b1    b5  \\\n",
+       "0   Производство  Акционерная компания с неторгуемыми акциями ил...  2007   \n",
+       "1   Производство  Акционерная компания с неторгуемыми акциями ил...  2002   \n",
+       "2   Производство  Акционерная компания с неторгуемыми акциями ил...  2005   \n",
+       "3  Другие услуги  Акционерная компания с неторгуемыми акциями ил...  2015   \n",
+       "4  Другие услуги  Акционерная компания с неторгуемыми акциями ил...  2002   \n",
+       "\n",
+       "   b7a                                              d1a1x  g1a  ... BMGc23i  \\\n",
+       "0  Нет  Производство Готовых Строительных Металлически...    0  ...      Да   \n",
+       "1  Нет                Производство Насосов И Компрессоров    0  ...     Нет   \n",
+       "2  Нет  Производство Алюминиевых И Медных Проводов, Си...  100  ...      Да   \n",
+       "3  Нет               Строительство жилых и нежилых зданий    0  ...     Нет   \n",
+       "4  Нет                     Оптовая Продажа Офисной Мебели    0  ...      Да   \n",
+       "\n",
+       "        BMGc23j                             BMGc24 BMGc25  \\\n",
+       "0           Нет  Модернизация машин и оборудования     Да   \n",
+       "1           Нет  Модернизация машин и оборудования    Нет   \n",
+       "2       Не знаю                                NaN    Нет   \n",
+       "3           Нет                                NaN    Нет   \n",
+       "4  Не применимо  Модернизация машин и оборудования    Нет   \n",
+       "\n",
+       "                                              BMGc27 BMGd6 BMGd7    BMGe1  \\\n",
+       "0                                                NaN   Нет   Нет   100000   \n",
+       "1  Не является приоритетом по сравнению с другими...   Нет   Нет   160000   \n",
+       "2                       Нехватка финансовых ресурсов   Нет   Нет  Не знаю   \n",
+       "3               Операционный и/ или технический риск   Нет   Нет  Не знаю   \n",
+       "4                       Нехватка финансовых ресурсов   Нет   Нет   100000   \n",
+       "\n",
+       "     BMGe2 BMGe2u  \n",
+       "0    20000  Литры  \n",
+       "1    18500  Литры  \n",
+       "2  Не знаю    NaN  \n",
+       "3  Не знаю    NaN  \n",
+       "4    10000  Литры  \n",
+       "\n",
+       "[5 rows x 48 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "url = \"ecology.xlsx\"\n",
+    "df = pd.read_excel(url)\n",
+    "\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['id', 'a4a', 'a6a', 'a2', 'a0', 'b1', 'b5', 'b7a', 'd1a1x', 'g1a',\n",
+       "       'BMj4c', 'j30_environment_pos', 'BMj5', 'n2a', 'n2e', 'n2b', 'n2f',\n",
+       "       'n2i', 'n2p', 'BMGa1', 'BMGa2', 'BMGa4', 'BMGb1', 'BMGb2', 'BMGc2',\n",
+       "       'BMGc5', 'BMGc7', 'BMGc8', 'BMGc16', 'BMGc18', 'BMGc23a', 'BMGc23b',\n",
+       "       'BMGc23c', 'BMGc23d', 'BMGc23e', 'BMGc23f', 'BMGc23g', 'BMGc23h',\n",
+       "       'BMGc23i', 'BMGc23j', 'BMGc24', 'BMGc25', 'BMGc27', 'BMGd6', 'BMGd7',\n",
+       "       'BMGe1', 'BMGe2', 'BMGe2u'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "exc = ['id', 'b5', 'g1a', 'j30_environment_pos']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " ____         _              _              _                _         \n",
+      "/ ___|   ___ | |  ___   ___ | |_   ___   __| |   ___   ___  | | ___  _ \n",
+      "\\___ \\  / _ \\| | / _ \\ / __|| __| / _ \\ / _` |  / __| / _ \\ | |/ __|(_)\n",
+      " ___) ||  __/| ||  __/| (__ | |_ |  __/| (_| | | (__ | (_) || |\\__ \\ _ \n",
+      "|____/  \\___||_| \\___| \\___| \\__| \\___| \\__,_|  \\___| \\___/ |_||___/(_)\n",
+      "                                                                       \n",
+      "\n",
+      "\n",
+      "n2a | n2e | n2b | n2f | n2i | n2p | BMGe1 | BMGe2\n",
+      "                                                                      \n",
+      "                                                                      \n",
+      "                                                                      \n",
+      "                                                                      \n",
+      " _____  _____  _____  _____  _____  _____  _____  _____  _____  _____ \n",
+      "|_____||_____||_____||_____||_____||_____||_____||_____||_____||_____|\n",
+      "\n",
+      "column: n2a => deleted: 154\n",
+      "column: n2e => deleted: 76\n",
+      "column: n2b => deleted: 72\n",
+      "column: n2f => deleted: 25\n",
+      "column: n2i => deleted: 8\n",
+      "column: n2p => deleted: 18\n",
+      "column: BMGe1 => deleted: 29\n",
+      "column: BMGe2 => deleted: 63\n",
+      "__        __    _     ____     \n",
+      "\\ \\      / /   / \\   / ___|  _ \n",
+      " \\ \\ /\\ / /   / _ \\  \\___ \\ (_)\n",
+      "  \\ V  V /   / ___ \\  ___) | _ \n",
+      "   \\_/\\_/   /_/   \\_\\|____/ (_)\n",
+      "                               \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1300 with 8 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                                                                      \n",
+      "                                                                      \n",
+      "                                                                      \n",
+      "                                                                      \n",
+      " _____  _____  _____  _____  _____  _____  _____  _____  _____  _____ \n",
+      "|_____||_____||_____||_____||_____||_____||_____||_____||_____||_____|\n",
+      "\n",
+      " ____   _____   ____     _     __  __  _____    \n",
+      "| __ ) | ____| / ___|   / \\   |  \\/  || ____| _ \n",
+      "|  _ \\ |  _|  | |      / _ \\  | |\\/| ||  _|  (_)\n",
+      "| |_) || |___ | |___  / ___ \\ | |  | || |___  _ \n",
+      "|____/ |_____| \\____|/_/   \\_\\|_|  |_||_____|(_)\n",
+      "                                                \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1300 with 8 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "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>id</th>\n",
+       "      <th>a4a</th>\n",
+       "      <th>a6a</th>\n",
+       "      <th>a2</th>\n",
+       "      <th>a0</th>\n",
+       "      <th>b1</th>\n",
+       "      <th>b5</th>\n",
+       "      <th>b7a</th>\n",
+       "      <th>d1a1x</th>\n",
+       "      <th>g1a</th>\n",
+       "      <th>...</th>\n",
+       "      <th>BMGc23i</th>\n",
+       "      <th>BMGc23j</th>\n",
+       "      <th>BMGc24</th>\n",
+       "      <th>BMGc25</th>\n",
+       "      <th>BMGc27</th>\n",
+       "      <th>BMGd6</th>\n",
+       "      <th>BMGd7</th>\n",
+       "      <th>BMGe1</th>\n",
+       "      <th>BMGe2</th>\n",
+       "      <th>BMGe2u</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>50</td>\n",
+       "      <td>Готовые Металлические Изделия</td>\n",
+       "      <td>Малый</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Другие услуги</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Строительство жилых и нежилых зданий</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Операционный и/ или технический риск</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>90</td>\n",
+       "      <td>Другие Услуги</td>\n",
+       "      <td>Средний</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Другие услуги</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>1999</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Оптовая Торговля Промышленным Электрооборудова...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>126</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Малый</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Розничная Торговля Запасными Частями и Комплек...</td>\n",
+       "      <td>Не применимо</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Минимизация отходов, вторичная переработка и у...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>7800</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>145</td>\n",
+       "      <td>Готовые Металлические Изделия</td>\n",
+       "      <td>Средний</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Производство</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2000</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Изготовление Вертикальных Стальных Резервуаров...</td>\n",
+       "      <td>Не применимо</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>176</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Малый</td>\n",
+       "      <td>Центральный Федеральный округ</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2002</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Розничная торговля Продуктами питания И Товара...</td>\n",
+       "      <td>Не применимо</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не применимо</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нехватка финансовых ресурсов</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>2000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</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>1315</th>\n",
+       "      <td>699488</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Крупный</td>\n",
+       "      <td>Северо-Западный федеральный округ</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Розничная Торговля Настольными Играми</td>\n",
+       "      <td>Не применимо</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не является приоритетом по сравнению с другими...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1316</th>\n",
+       "      <td>699522</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Крупный</td>\n",
+       "      <td>Южный федеральный округ и Северо-Кавказский фе...</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2000</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Розничная Торговля Алкогольными напитками</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Неопределенность в отношении будущих цен</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1320</th>\n",
+       "      <td>699770</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Крупный</td>\n",
+       "      <td>Дальневосточный федеральный округ</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2005</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Розничная Продажа Бытовых Электроприборов</td>\n",
+       "      <td>Не применимо</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не выгодно</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1321</th>\n",
+       "      <td>699775</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Крупный</td>\n",
+       "      <td>Сибирский федеральный округ</td>\n",
+       "      <td>Другие услуги</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>2002</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Розничная Продажа Моторного топлива В Специали...</td>\n",
+       "      <td>Не применимо</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1322</th>\n",
+       "      <td>699777</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Крупный</td>\n",
+       "      <td>Уральский федеральный округ</td>\n",
+       "      <td>Розничная торговля</td>\n",
+       "      <td>Акционерная компания с неторгуемыми акциями ил...</td>\n",
+       "      <td>1999</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Розничная Продажа Продуктов Питания И Напитков</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Усовершенствования системы освещения</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Нет</td>\n",
+       "      <td>Да</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>Не знаю</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>878 rows × 48 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          id                            a4a      a6a  \\\n",
+       "3         50  Готовые Металлические Изделия    Малый   \n",
+       "5         90                  Другие Услуги  Средний   \n",
+       "7        126             Розничная торговля    Малый   \n",
+       "13       145  Готовые Металлические Изделия  Средний   \n",
+       "16       176             Розничная торговля    Малый   \n",
+       "...      ...                            ...      ...   \n",
+       "1315  699488             Розничная торговля  Крупный   \n",
+       "1316  699522             Розничная торговля  Крупный   \n",
+       "1320  699770             Розничная торговля  Крупный   \n",
+       "1321  699775             Розничная торговля  Крупный   \n",
+       "1322  699777             Розничная торговля  Крупный   \n",
+       "\n",
+       "                                                     a2                  a0  \\\n",
+       "3                         Центральный Федеральный округ       Другие услуги   \n",
+       "5                         Центральный Федеральный округ       Другие услуги   \n",
+       "7                         Центральный Федеральный округ  Розничная торговля   \n",
+       "13                        Центральный Федеральный округ        Производство   \n",
+       "16                        Центральный Федеральный округ  Розничная торговля   \n",
+       "...                                                 ...                 ...   \n",
+       "1315                  Северо-Западный федеральный округ  Розничная торговля   \n",
+       "1316  Южный федеральный округ и Северо-Кавказский фе...  Розничная торговля   \n",
+       "1320                  Дальневосточный федеральный округ  Розничная торговля   \n",
+       "1321                        Сибирский федеральный округ       Другие услуги   \n",
+       "1322                        Уральский федеральный округ  Розничная торговля   \n",
+       "\n",
+       "                                                     b1    b5  b7a  \\\n",
+       "3     Акционерная компания с неторгуемыми акциями ил...  2015  Нет   \n",
+       "5     Акционерная компания с неторгуемыми акциями ил...  1999   Да   \n",
+       "7     Акционерная компания с неторгуемыми акциями ил...  1994  Нет   \n",
+       "13    Акционерная компания с неторгуемыми акциями ил...  2000   Да   \n",
+       "16    Акционерная компания с неторгуемыми акциями ил...  2002   Да   \n",
+       "...                                                 ...   ...  ...   \n",
+       "1315  Акционерная компания с неторгуемыми акциями ил...  2011  Нет   \n",
+       "1316  Акционерная компания с неторгуемыми акциями ил...  2000  Нет   \n",
+       "1320  Акционерная компания с неторгуемыми акциями ил...  2005  Нет   \n",
+       "1321  Акционерная компания с неторгуемыми акциями ил...  2002  Нет   \n",
+       "1322  Акционерная компания с неторгуемыми акциями ил...  1999   Да   \n",
+       "\n",
+       "                                                  d1a1x           g1a  ...  \\\n",
+       "3                  Строительство жилых и нежилых зданий             0  ...   \n",
+       "5     Оптовая Торговля Промышленным Электрооборудова...             0  ...   \n",
+       "7     Розничная Торговля Запасными Частями и Комплек...  Не применимо  ...   \n",
+       "13    Изготовление Вертикальных Стальных Резервуаров...  Не применимо  ...   \n",
+       "16    Розничная торговля Продуктами питания И Товара...  Не применимо  ...   \n",
+       "...                                                 ...           ...  ...   \n",
+       "1315              Розничная Торговля Настольными Играми  Не применимо  ...   \n",
+       "1316          Розничная Торговля Алкогольными напитками       Не знаю  ...   \n",
+       "1320          Розничная Продажа Бытовых Электроприборов  Не применимо  ...   \n",
+       "1321  Розничная Продажа Моторного топлива В Специали...  Не применимо  ...   \n",
+       "1322     Розничная Продажа Продуктов Питания И Напитков             0  ...   \n",
+       "\n",
+       "     BMGc23i       BMGc23j                                             BMGc24  \\\n",
+       "3        Нет           Нет                                                NaN   \n",
+       "5        Нет           Нет                                                NaN   \n",
+       "7         Да           Нет  Минимизация отходов, вторичная переработка и у...   \n",
+       "13       Нет           Нет                                                NaN   \n",
+       "16       Нет  Не применимо                                            Не знаю   \n",
+       "...      ...           ...                                                ...   \n",
+       "1315     Нет           Нет                                                NaN   \n",
+       "1316     Нет           Нет                                                NaN   \n",
+       "1320     Нет           Нет                                                NaN   \n",
+       "1321      Да           Нет                                            Не знаю   \n",
+       "1322      Да           Нет               Усовершенствования системы освещения   \n",
+       "\n",
+       "     BMGc25                                             BMGc27 BMGd6    BMGd7  \\\n",
+       "3       Нет               Операционный и/ или технический риск   Нет      Нет   \n",
+       "5        Да                                                NaN   Нет      Нет   \n",
+       "7       Нет                                            Не знаю   Нет      Нет   \n",
+       "13      Нет                                            Не знаю   Нет      Нет   \n",
+       "16      Нет                       Нехватка финансовых ресурсов   Нет      Нет   \n",
+       "...     ...                                                ...   ...      ...   \n",
+       "1315    Нет  Не является приоритетом по сравнению с другими...   Нет      Нет   \n",
+       "1316    Нет           Неопределенность в отношении будущих цен   Нет      Нет   \n",
+       "1320    Нет                                         Не выгодно   Нет      Нет   \n",
+       "1321     Да                                                NaN   Нет  Не знаю   \n",
+       "1322     Да                                                NaN   Нет       Да   \n",
+       "\n",
+       "        BMGe1    BMGe2 BMGe2u  \n",
+       "3     Не знаю  Не знаю    NaN  \n",
+       "5     Не знаю  Не знаю    NaN  \n",
+       "7        7800  Не знаю    NaN  \n",
+       "13    Не знаю  Не знаю    NaN  \n",
+       "16       2000        0    NaN  \n",
+       "...       ...      ...    ...  \n",
+       "1315  Не знаю  Не знаю    NaN  \n",
+       "1316  Не знаю  Не знаю    NaN  \n",
+       "1320  Не знаю        0    NaN  \n",
+       "1321  Не знаю  Не знаю    NaN  \n",
+       "1322  Не знаю  Не знаю    NaN  \n",
+       "\n",
+       "[878 rows x 48 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "clear_df, deleted = data_preprocessing(df, exclude=exc)\n",
+    "clear_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'n2a': {'count': 154,\n",
+       "  'deleted': {1: '150000000',\n",
+       "   14: '150000000',\n",
+       "   37: '160000000',\n",
+       "   47: '270000000',\n",
+       "   67: '240000000',\n",
+       "   75: '150000000',\n",
+       "   89: '200400000',\n",
+       "   90: '400000000',\n",
+       "   108: '900000000',\n",
+       "   124: '3000000000',\n",
+       "   143: '180000000',\n",
+       "   159: '200000000',\n",
+       "   184: '950000000',\n",
+       "   188: '155000000',\n",
+       "   225: '185000000',\n",
+       "   258: '200000000',\n",
+       "   345: '270000000',\n",
+       "   363: '190000000',\n",
+       "   378: '240600000',\n",
+       "   394: '190000000',\n",
+       "   398: '460000000',\n",
+       "   399: '1000000000',\n",
+       "   485: '188000000',\n",
+       "   505: '760000000',\n",
+       "   508: '480000000',\n",
+       "   568: '396000000',\n",
+       "   582: '250000000',\n",
+       "   791: '4213205000',\n",
+       "   863: '2000000000',\n",
+       "   961: '155000000',\n",
+       "   964: '164000000',\n",
+       "   976: '150000000',\n",
+       "   978: '480000000',\n",
+       "   981: '170000000',\n",
+       "   982: '248000000',\n",
+       "   989: '395000000',\n",
+       "   991: '700000000',\n",
+       "   992: '200000000',\n",
+       "   993: '200000000',\n",
+       "   995: '150000000',\n",
+       "   1002: '185000000',\n",
+       "   1004: '480000000',\n",
+       "   1005: '185000000',\n",
+       "   1006: '714000000',\n",
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+       "   1010: '412000000',\n",
+       "   1014: '400000000',\n",
+       "   1016: '200000000',\n",
+       "   1018: '250000000',\n",
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+       "   1073: '150000000',\n",
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+       "   1146: '250000000',\n",
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+       "   1157: '360700000',\n",
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+       "   1163: '500000000',\n",
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+       "   1212: '400000000',\n",
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+       "   1216: '300000000',\n",
+       "   1218: '1000000000',\n",
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+       "   1226: '50000000000',\n",
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+       "   1246: '2200000000',\n",
+       "   1249: '173840802',\n",
+       "   1254: '320000000',\n",
+       "   1317: '392400000'}},\n",
+       " 'n2e': {'count': 76,\n",
+       "  'deleted': {2: '78000000',\n",
+       "   8: '120000000',\n",
+       "   9: '300000000',\n",
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+       "   30: '190000000',\n",
+       "   34: '84000000',\n",
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+       "   56: '100000000',\n",
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+       "   135: '115000000',\n",
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+       "   605: '680000000',\n",
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+       "   763: '100000000',\n",
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+       "   797: '95000000',\n",
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+       "   826: '80000000',\n",
+       "   833: '113000000',\n",
+       "   834: '150000000',\n",
+       "   844: '100000000',\n",
+       "   854: '240000000',\n",
+       "   857: '150000000',\n",
+       "   864: '90000000',\n",
+       "   865: '119000000',\n",
+       "   872: '150000000',\n",
+       "   873: '108000000',\n",
+       "   880: '180000000',\n",
+       "   882: '400000000',\n",
+       "   884: '153128001',\n",
+       "   919: '160000000',\n",
+       "   921: '200000000',\n",
+       "   928: '330000000',\n",
+       "   945: '650000000',\n",
+       "   947: '275000000',\n",
+       "   949: '350000000',\n",
+       "   956: '400000000',\n",
+       "   967: '120000000',\n",
+       "   970: '250000000',\n",
+       "   971: '300000000',\n",
+       "   975: '700000000',\n",
+       "   983: '600000000',\n",
+       "   987: '690000000',\n",
+       "   988: '90000000',\n",
+       "   994: '700000000',\n",
+       "   997: '580000000',\n",
+       "   1000: '260000000',\n",
+       "   1021: '200000000',\n",
+       "   1039: '700000000',\n",
+       "   1040: '900000000',\n",
+       "   1063: '900000000',\n",
+       "   1065: '100000000',\n",
+       "   1070: '314500000',\n",
+       "   1080: '500000000',\n",
+       "   1081: '950000000',\n",
+       "   1088: '670000000',\n",
+       "   1108: '130000000',\n",
+       "   1131: '373000000',\n",
+       "   1135: '270000000',\n",
+       "   1144: '1200000000',\n",
+       "   1145: '150000000',\n",
+       "   1147: '250000000',\n",
+       "   1178: '1500000000',\n",
+       "   1197: '157800000',\n",
+       "   1202: '120000000',\n",
+       "   1204: '140000000',\n",
+       "   1222: '480000000',\n",
+       "   1247: '120000000'}},\n",
+       " 'n2b': {'count': 72,\n",
+       "  'deleted': {12: '2600000',\n",
+       "   20: '1800000',\n",
+       "   32: '2000000',\n",
+       "   48: '1500000',\n",
+       "   54: '2000000',\n",
+       "   60: '1500000',\n",
+       "   80: '3000000',\n",
+       "   102: '1500000',\n",
+       "   104: '100000000',\n",
+       "   105: '2000000',\n",
+       "   111: '1500000',\n",
+       "   113: '1500000',\n",
+       "   126: '1500000',\n",
+       "   127: '1500000',\n",
+       "   132: '1600000',\n",
+       "   133: '4600000',\n",
+       "   134: '1500000',\n",
+       "   149: '2000000',\n",
+       "   247: '3600000',\n",
+       "   334: '2300000',\n",
+       "   336: '3500000',\n",
+       "   346: '2700000',\n",
+       "   348: '2400000',\n",
+       "   349: '1500000',\n",
+       "   358: '1700000',\n",
+       "   392: '1500000',\n",
+       "   400: '2500000',\n",
+       "   416: '1500000',\n",
+       "   461: '1500000',\n",
+       "   478: '3630000',\n",
+       "   482: '7265000',\n",
+       "   484: '6000000',\n",
+       "   486: '12000000',\n",
+       "   499: '8000000',\n",
+       "   511: '8000000',\n",
+       "   552: '30000000',\n",
+       "   565: '2000000',\n",
+       "   580: '2600000',\n",
+       "   599: '1500000',\n",
+       "   662: '2400000',\n",
+       "   688: '2300000',\n",
+       "   697: '8900000',\n",
+       "   702: '2100000',\n",
+       "   737: '4000000',\n",
+       "   738: '3000000',\n",
+       "   741: '3000000',\n",
+       "   756: '3800000',\n",
+       "   796: '2500000',\n",
+       "   804: '1500000',\n",
+       "   810: '1800000',\n",
+       "   871: '3000000',\n",
+       "   958: '1500000',\n",
+       "   959: '3600000',\n",
+       "   966: '2000000',\n",
+       "   973: '3200000',\n",
+       "   999: '3000000',\n",
+       "   1003: '1500000',\n",
+       "   1007: '5500000',\n",
+       "   1011: '4000000',\n",
+       "   1019: '1600000',\n",
+       "   1091: '12108000',\n",
+       "   1092: '1800000',\n",
+       "   1185: '4500000',\n",
+       "   1227: '8000000',\n",
+       "   1232: '2000000',\n",
+       "   1250: '1500000',\n",
+       "   1253: '1700000',\n",
+       "   1278: '1800000',\n",
+       "   1288: '2000000',\n",
+       "   1314: '2700000',\n",
+       "   1318: '5500000',\n",
+       "   1319: '4000000'}},\n",
+       " 'n2f': {'count': 25,\n",
+       "  'deleted': {19: '2000000',\n",
+       "   63: '3600000',\n",
+       "   77: '110000000',\n",
+       "   93: '11000000',\n",
+       "   98: '2160000',\n",
+       "   122: '1800000',\n",
+       "   138: '1700000',\n",
+       "   142: '1600000',\n",
+       "   164: '2100000',\n",
+       "   170: '1650000',\n",
+       "   405: '6000000',\n",
+       "   451: '1800000',\n",
+       "   481: '6180168',\n",
+       "   491: '10000000',\n",
+       "   493: '7949004',\n",
+       "   549: '1700000',\n",
+       "   550: '10000000',\n",
+       "   564: '4000000',\n",
+       "   588: '2900000',\n",
+       "   699: '18000000',\n",
+       "   727: '5000000',\n",
+       "   879: '8000000',\n",
+       "   946: '3000000',\n",
+       "   962: '9800000',\n",
+       "   1052: '3000000'}},\n",
+       " 'n2i': {'count': 8,\n",
+       "  'deleted': {11: '200000000',\n",
+       "   125: '58800000',\n",
+       "   129: '380000000',\n",
+       "   136: '140000000',\n",
+       "   248: '45000000',\n",
+       "   329: '140000000',\n",
+       "   1283: '145000000',\n",
+       "   1285: '68000000'}},\n",
+       " 'n2p': {'count': 18,\n",
+       "  'deleted': {183: '78000000',\n",
+       "   320: '79100000',\n",
+       "   376: '80000000',\n",
+       "   384: '156000000',\n",
+       "   434: '86000000',\n",
+       "   802: '91000000',\n",
+       "   827: '113000000',\n",
+       "   835: '181020000',\n",
+       "   878: '105000000',\n",
+       "   881: '80000000',\n",
+       "   931: '82000000',\n",
+       "   938: '118030000',\n",
+       "   951: '78000000',\n",
+       "   955: '171560000',\n",
+       "   965: '78760000',\n",
+       "   998: '100000000',\n",
+       "   1015: '150000000',\n",
+       "   1210: '81000000'}},\n",
+       " 'BMGe1': {'count': 29,\n",
+       "  'deleted': {10: '170000',\n",
+       "   24: '180000',\n",
+       "   26: '120000',\n",
+       "   35: '166000',\n",
+       "   53: '150000',\n",
+       "   79: '150000',\n",
+       "   84: '150000',\n",
+       "   87: '175000',\n",
+       "   99: '250000',\n",
+       "   103: '300000',\n",
+       "   106: '130000',\n",
+       "   115: '150000',\n",
+       "   117: '150000',\n",
+       "   123: '150000',\n",
+       "   415: '250000',\n",
+       "   419: '250000',\n",
+       "   651: '400000',\n",
+       "   698: '166000',\n",
+       "   703: '142000',\n",
+       "   724: '140000',\n",
+       "   747: '166000',\n",
+       "   867: '190000',\n",
+       "   895: '250000',\n",
+       "   911: '2000000',\n",
+       "   927: '314000',\n",
+       "   942: '160000',\n",
+       "   1023: '500000',\n",
+       "   1047: '250000',\n",
+       "   1199: '1000000'}},\n",
+       " 'BMGe2': {'count': 63,\n",
+       "  'deleted': {0: '20000',\n",
+       "   4: '10000',\n",
+       "   6: '5500',\n",
+       "   25: '36000',\n",
+       "   29: '13000',\n",
+       "   33: '17000',\n",
+       "   36: '18000',\n",
+       "   39: '6000',\n",
+       "   50: '12000',\n",
+       "   57: '13000',\n",
+       "   58: '150000',\n",
+       "   59: '200',\n",
+       "   61: '50000',\n",
+       "   69: '2000',\n",
+       "   72: '3600',\n",
+       "   76: '30000',\n",
+       "   91: '16000',\n",
+       "   92: '25000',\n",
+       "   94: '2000',\n",
+       "   96: '5500',\n",
+       "   97: '9000',\n",
+       "   109: '150000',\n",
+       "   112: '7200',\n",
+       "   114: '11000',\n",
+       "   116: '7400',\n",
+       "   119: '16000',\n",
+       "   128: '15000',\n",
+       "   171: '700',\n",
+       "   333: '60',\n",
+       "   337: '410',\n",
+       "   397: '2000',\n",
+       "   402: '500',\n",
+       "   410: '30',\n",
+       "   438: '20',\n",
+       "   480: '14000',\n",
+       "   483: '46000',\n",
+       "   487: '10080',\n",
+       "   496: '17000',\n",
+       "   534: '18000',\n",
+       "   535: '250000',\n",
+       "   540: '600',\n",
+       "   545: '2500',\n",
+       "   548: '2000',\n",
+       "   589: '15',\n",
+       "   590: '20000',\n",
+       "   639: '500',\n",
+       "   683: '2300',\n",
+       "   689: '600',\n",
+       "   718: '10000',\n",
+       "   730: '3000',\n",
+       "   735: '5000',\n",
+       "   751: '6000',\n",
+       "   753: '552',\n",
+       "   759: '2500',\n",
+       "   787: '18000',\n",
+       "   832: '120009',\n",
+       "   850: '20000',\n",
+       "   892: '76',\n",
+       "   916: '15000',\n",
+       "   980: '4800',\n",
+       "   1119: '15000',\n",
+       "   1171: '20000',\n",
+       "   1277: '3000'}}}"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "deleted"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/test.py b/test.py
new file mode 100644
index 0000000..b99b67c
--- /dev/null
+++ b/test.py
@@ -0,0 +1,10 @@
+import pandas as pd
+
+# import matplotlib.pyplot as plt
+# import seaborn as sns
+# import numpy as np
+# from spandas.preprocessing import *
+
+df = pd.read_excel("C:\\Users\\Vex\\ProgaMain\\Selling Pandas\\spandas\\ecology.xlsx")
+
+exc = ["id", "b5", "g1a", "j30_environment_pos"]