houses-in-lekki.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/bernardrr/houses-in-lekki?scriptVersionId=123918675\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown"},{"cell_type":"markdown","id":"25aa8232","metadata":{"papermill":{"duration":0.01622,"end_time":"2023-03-30T08:48:17.703875","exception":false,"start_time":"2023-03-30T08:48:17.687655","status":"completed"},"tags":[]},"source":["# **Predicting House Prices in Lekki**"]},{"cell_type":"code","execution_count":1,"id":"d14fa3ab","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.execute_input":"2023-03-30T08:48:17.736648Z","iopub.status.busy":"2023-03-30T08:48:17.736024Z","iopub.status.idle":"2023-03-30T08:48:19.677065Z","shell.execute_reply":"2023-03-30T08:48:19.675401Z"},"papermill":{"duration":1.962375,"end_time":"2023-03-30T08:48:19.681215","exception":false,"start_time":"2023-03-30T08:48:17.71884","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["/kaggle/input/nigeria-houses-and-prices-dataset/info.txt\n","/kaggle/input/nigeria-houses-and-prices-dataset/nigeria_houses_data.csv\n"]}],"source":["import numpy as np # linear algebra\n","import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import mean_absolute_error\n","from category_encoders import OneHotEncoder\n","from sklearn.pipeline import make_pipeline\n","from sklearn.linear_model import LinearRegression, Ridge\n","from ipywidgets import Dropdown, FloatSlider, IntSlider, interact\n","\n","\n","import os\n","for dirname, _, filenames in os.walk('/kaggle/input'):\n","    for filename in filenames:\n","        print(os.path.join(dirname, filename))\n"]},{"cell_type":"code","execution_count":2,"id":"2449f341","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:19.714298Z","iopub.status.busy":"2023-03-30T08:48:19.713769Z","iopub.status.idle":"2023-03-30T08:48:19.827989Z","shell.execute_reply":"2023-03-30T08:48:19.826819Z"},"papermill":{"duration":0.13302,"end_time":"2023-03-30T08:48:19.830887","exception":false,"start_time":"2023-03-30T08:48:19.697867","status":"completed"},"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>bedrooms</th>\n","      <th>bathrooms</th>\n","      <th>toilets</th>\n","      <th>parking_space</th>\n","      <th>title</th>\n","      <th>town</th>\n","      <th>state</th>\n","      <th>price</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>20602</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Block of Flats</td>\n","      <td>Ikoyi</td>\n","      <td>Lagos</td>\n","      <td>1.500000e+10</td>\n","    </tr>\n","    <tr>\n","      <th>13490</th>\n","      <td>3.0</td>\n","      <td>3.0</td>\n","      <td>3.0</td>\n","      <td>4.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Ajah</td>\n","      <td>Lagos</td>\n","      <td>4.200000e+10</td>\n","    </tr>\n","    <tr>\n","      <th>17383</th>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>3.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Ajah</td>\n","      <td>Lagos</td>\n","      <td>5.000000e+10</td>\n","    </tr>\n","    <tr>\n","      <th>15806</th>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>1.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Ifako-Ijaiye</td>\n","      <td>Lagos</td>\n","      <td>5.500000e+10</td>\n","    </tr>\n","    <tr>\n","      <th>15836</th>\n","      <td>5.0</td>\n","      <td>6.0</td>\n","      <td>7.0</td>\n","      <td>4.0</td>\n","      <td>Terraced Duplexes</td>\n","      <td>Guzape District</td>\n","      <td>Abuja</td>\n","      <td>8.500000e+10</td>\n","    </tr>\n","    <tr>\n","      <th>7098</th>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>6.0</td>\n","      <td>4.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>1.250000e+11</td>\n","    </tr>\n","    <tr>\n","      <th>4327</th>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>6.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>1.600000e+11</td>\n","    </tr>\n","    <tr>\n","      <th>15962</th>\n","      <td>9.0</td>\n","      <td>9.0</td>\n","      <td>1.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>3.500000e+11</td>\n","    </tr>\n","    <tr>\n","      <th>6632</th>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Ikoyi</td>\n","      <td>Lagos</td>\n","      <td>4.500000e+11</td>\n","    </tr>\n","    <tr>\n","      <th>4096</th>\n","      <td>7.0</td>\n","      <td>7.0</td>\n","      <td>8.0</td>\n","      <td>8.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Ikoyi</td>\n","      <td>Lagos</td>\n","      <td>1.800000e+12</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["       bedrooms  bathrooms  toilets  parking_space                 title  \\\n","20602       4.0        5.0      5.0            4.0        Block of Flats   \n","13490       3.0        3.0      3.0            4.0  Semi Detached Duplex   \n","17383       4.0        4.0      5.0            3.0       Detached Duplex   \n","15806       5.0        5.0      5.0            1.0       Detached Duplex   \n","15836       5.0        6.0      7.0            4.0     Terraced Duplexes   \n","7098        5.0        5.0      6.0            4.0  Semi Detached Duplex   \n","4327        5.0        5.0      6.0            4.0       Detached Duplex   \n","15962       9.0        9.0      1.0            4.0       Detached Duplex   \n","6632        4.0        4.0      5.0            4.0  Semi Detached Duplex   \n","4096        7.0        7.0      8.0            8.0       Detached Duplex   \n","\n","                  town  state         price  \n","20602            Ikoyi  Lagos  1.500000e+10  \n","13490             Ajah  Lagos  4.200000e+10  \n","17383             Ajah  Lagos  5.000000e+10  \n","15806     Ifako-Ijaiye  Lagos  5.500000e+10  \n","15836  Guzape District  Abuja  8.500000e+10  \n","7098             Lekki  Lagos  1.250000e+11  \n","4327             Lekki  Lagos  1.600000e+11  \n","15962            Lekki  Lagos  3.500000e+11  \n","6632             Ikoyi  Lagos  4.500000e+11  \n","4096             Ikoyi  Lagos  1.800000e+12  "]},"execution_count":2,"metadata":{},"output_type":"execute_result"}],"source":["df = pd.read_csv(\"../input/nigeria-houses-and-prices-dataset/nigeria_houses_data.csv\")\n","df.sort_values(by=\"price\").tail(10)"]},{"cell_type":"code","execution_count":3,"id":"77f47179","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:19.863486Z","iopub.status.busy":"2023-03-30T08:48:19.862012Z","iopub.status.idle":"2023-03-30T08:48:19.895685Z","shell.execute_reply":"2023-03-30T08:48:19.893858Z"},"papermill":{"duration":0.052982,"end_time":"2023-03-30T08:48:19.898725","exception":false,"start_time":"2023-03-30T08:48:19.845743","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 24326 entries, 0 to 24325\n","Data columns (total 8 columns):\n"," #   Column         Non-Null Count  Dtype  \n","---  ------         --------------  -----  \n"," 0   bedrooms       24326 non-null  float64\n"," 1   bathrooms      24326 non-null  float64\n"," 2   toilets        24326 non-null  float64\n"," 3   parking_space  24326 non-null  float64\n"," 4   title          24326 non-null  object \n"," 5   town           24326 non-null  object \n"," 6   state          24326 non-null  object \n"," 7   price          24326 non-null  float64\n","dtypes: float64(5), object(3)\n","memory usage: 1.5+ MB\n"]}],"source":["df.info()"]},{"cell_type":"markdown","id":"1b15e6cb","metadata":{"papermill":{"duration":0.015036,"end_time":"2023-03-30T08:48:19.928945","exception":false,"start_time":"2023-03-30T08:48:19.913909","status":"completed"},"tags":[]},"source":["# **Exploratory Data Analysis**\n"]},{"cell_type":"code","execution_count":4,"id":"5241cc33","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:19.960987Z","iopub.status.busy":"2023-03-30T08:48:19.960435Z","iopub.status.idle":"2023-03-30T08:48:19.973257Z","shell.execute_reply":"2023-03-30T08:48:19.971517Z"},"papermill":{"duration":0.032805,"end_time":"2023-03-30T08:48:19.97645","exception":false,"start_time":"2023-03-30T08:48:19.943645","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["There are 25 unique states in the dataset\n","There are 189 unique towns in the dataset\n"]}],"source":["# Unique number of states\n","state_no = df[\"state\"].nunique()\n","print(f\"There are {state_no} unique states in the dataset\")\n","\n","# Unique number of towns\n","towns_no = df[\"town\"].nunique()\n","print(f\"There are {towns_no} unique towns in the dataset\")"]},{"cell_type":"code","execution_count":5,"id":"569c6f49","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:20.008632Z","iopub.status.busy":"2023-03-30T08:48:20.008068Z","iopub.status.idle":"2023-03-30T08:48:20.392252Z","shell.execute_reply":"2023-03-30T08:48:20.390657Z"},"papermill":{"duration":0.403878,"end_time":"2023-03-30T08:48:20.395414","exception":false,"start_time":"2023-03-30T08:48:19.991536","status":"completed"},"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"}],"source":["(\n","    (df.groupby(\"town\")['price']\n","    .mean()/1e9)\n","    .sort_values(ascending=False)\n","    .head(20)\n","    .plot(kind=\"bar\",\n","         xlabel = 'Towns',\n","         ylabel = \"Prices [₦1B]\",\n","         title = \"Most Expensive Real Estate Towns in Nigeria\")\n",");"]},{"cell_type":"markdown","id":"ae91114d","metadata":{"papermill":{"duration":0.014958,"end_time":"2023-03-30T08:48:20.425969","exception":false,"start_time":"2023-03-30T08:48:20.411011","status":"completed"},"tags":[]},"source":["During analysis, it could intuitively be noticed that houses in *Ifako-Ijaiye* cannot be in the league of houses in *Maitama District*. There had to be outliers contributing to this. It was discovered that a house in \"Ifako-Ijaiye\" was selling for about 55 billion naira, quite absurd.\n","\n","Also, houses in *Ikoyi* are quite expensive but still, the gap was unexpected. Further investigation showed that a house was selling for about *1.8 trillion naira*. Whether the house is worth it or not is not the question; the effect was harmful to this dataset."]},{"cell_type":"code","execution_count":6,"id":"a03a174b","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:20.459879Z","iopub.status.busy":"2023-03-30T08:48:20.459357Z","iopub.status.idle":"2023-03-30T08:48:20.479177Z","shell.execute_reply":"2023-03-30T08:48:20.477964Z"},"papermill":{"duration":0.040647,"end_time":"2023-03-30T08:48:20.48266","exception":false,"start_time":"2023-03-30T08:48:20.442013","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["bedrooms                       9.0\n","bathrooms                      9.0\n","toilets                        9.0\n","parking_space                  9.0\n","title            Terraced Duplexes\n","town                         Ikoyi\n","state                        Lagos\n","price              1800000000000.0\n","dtype: object\n","bedrooms                       7.0\n","bathrooms                      8.0\n","toilets                        8.0\n","parking_space                  8.0\n","title            Terraced Bungalow\n","town                  Ifako-Ijaiye\n","state                        Lagos\n","price                55000000000.0\n","dtype: object\n"]}],"source":["# Detecting suspected outlier\n","print(df[df[\"town\"]==\"Ikoyi\"].max())\n","print(df[df[\"town\"]==\"Ifako-Ijaiye\"].max())"]},{"cell_type":"markdown","id":"59279944","metadata":{"papermill":{"duration":0.014932,"end_time":"2023-03-30T08:48:20.513465","exception":false,"start_time":"2023-03-30T08:48:20.498533","status":"completed"},"tags":[]},"source":["### Removing Outliers"]},{"cell_type":"code","execution_count":7,"id":"b5400916","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:20.547034Z","iopub.status.busy":"2023-03-30T08:48:20.546555Z","iopub.status.idle":"2023-03-30T08:48:20.580835Z","shell.execute_reply":"2023-03-30T08:48:20.579381Z"},"papermill":{"duration":0.054821,"end_time":"2023-03-30T08:48:20.58372","exception":false,"start_time":"2023-03-30T08:48:20.528899","status":"completed"},"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>bedrooms</th>\n","      <th>bathrooms</th>\n","      <th>toilets</th>\n","      <th>parking_space</th>\n","      <th>title</th>\n","      <th>town</th>\n","      <th>state</th>\n","      <th>price</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>120000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>6.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Ajah</td>\n","      <td>Lagos</td>\n","      <td>40000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>2.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>75000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>65000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>1.0</td>\n","      <td>1.0</td>\n","      <td>1.0</td>\n","      <td>1.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>200000000.0</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","    </tr>\n","    <tr>\n","      <th>24318</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>110000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>24320</th>\n","      <td>3.0</td>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>80000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>24323</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>68000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>24324</th>\n","      <td>3.0</td>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>3.0</td>\n","      <td>Block of Flats</td>\n","      <td>Victoria Island (VI)</td>\n","      <td>Lagos</td>\n","      <td>78000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>24325</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>Lagos</td>\n","      <td>65000000.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>17491 rows × 8 columns</p>\n","</div>"],"text/plain":["       bedrooms  bathrooms  toilets  parking_space                 title  \\\n","2           4.0        5.0      5.0            4.0       Detached Duplex   \n","3           4.0        4.0      5.0            6.0       Detached Duplex   \n","4           4.0        4.0      5.0            2.0  Semi Detached Duplex   \n","6           4.0        5.0      5.0            4.0       Detached Duplex   \n","8           1.0        1.0      1.0            1.0       Detached Duplex   \n","...         ...        ...      ...            ...                   ...   \n","24318       4.0        5.0      5.0            4.0  Semi Detached Duplex   \n","24320       3.0        4.0      4.0            5.0       Detached Duplex   \n","24323       4.0        5.0      5.0            4.0       Detached Duplex   \n","24324       3.0        4.0      4.0            3.0        Block of Flats   \n","24325       4.0        5.0      5.0            4.0       Detached Duplex   \n","\n","                       town  state        price  \n","2                     Lekki  Lagos  120000000.0  \n","3                      Ajah  Lagos   40000000.0  \n","4                     Lekki  Lagos   75000000.0  \n","6                     Lekki  Lagos   65000000.0  \n","8                     Lekki  Lagos  200000000.0  \n","...                     ...    ...          ...  \n","24318                 Lekki  Lagos  110000000.0  \n","24320                 Lekki  Lagos   80000000.0  \n","24323                 Lekki  Lagos   68000000.0  \n","24324  Victoria Island (VI)  Lagos   78000000.0  \n","24325                 Lekki  Lagos   65000000.0  \n","\n","[17491 rows x 8 columns]"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["trim_df = q1, q9 = df[\"price\"].quantile([0.15,0.85])\n","mask_df = df[\"price\"].between(q1,q9)\n","trimmed_df = df[mask_df]\n","trimmed_df"]},{"cell_type":"code","execution_count":8,"id":"f52b3b00","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:20.618124Z","iopub.status.busy":"2023-03-30T08:48:20.617643Z","iopub.status.idle":"2023-03-30T08:48:20.630517Z","shell.execute_reply":"2023-03-30T08:48:20.628737Z"},"papermill":{"duration":0.033592,"end_time":"2023-03-30T08:48:20.63356","exception":false,"start_time":"2023-03-30T08:48:20.599968","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Lagos        13805\n","Abuja         2462\n","Rivers         339\n","Oyo            229\n","Imo            195\n","Ogun           141\n","Enugu           96\n","Anambara        83\n","Edo             51\n","Delta           42\n","Akwa Ibom       13\n","Kaduna           8\n","Ekiti            5\n","Abia             5\n","Kogi             4\n","Nasarawa         4\n","Osun             3\n","Kwara            2\n","Borno            2\n","Bayelsa          1\n","Niger            1\n","Name: state, dtype: int64"]},"execution_count":8,"metadata":{},"output_type":"execute_result"}],"source":["few_records = trimmed_df[\"state\"].value_counts()\n","few_records"]},{"cell_type":"code","execution_count":9,"id":"fdb46f7e","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:20.66807Z","iopub.status.busy":"2023-03-30T08:48:20.667585Z","iopub.status.idle":"2023-03-30T08:48:20.679006Z","shell.execute_reply":"2023-03-30T08:48:20.677155Z"},"papermill":{"duration":0.033019,"end_time":"2023-03-30T08:48:20.682403","exception":false,"start_time":"2023-03-30T08:48:20.649384","status":"completed"},"tags":[]},"outputs":[],"source":["# Removing States with few entries to stabilize the average\n","trimmed_df = trimmed_df[~trimmed_df['state'].isin(few_records[few_records < 100].index)]"]},{"cell_type":"code","execution_count":10,"id":"e0416393","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:20.716376Z","iopub.status.busy":"2023-03-30T08:48:20.715857Z","iopub.status.idle":"2023-03-30T08:48:20.727678Z","shell.execute_reply":"2023-03-30T08:48:20.726383Z"},"papermill":{"duration":0.032693,"end_time":"2023-03-30T08:48:20.730646","exception":false,"start_time":"2023-03-30T08:48:20.697953","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Lagos     13805\n","Abuja      2462\n","Rivers      339\n","Oyo         229\n","Imo         195\n","Ogun        141\n","Name: state, dtype: int64"]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":["trimmed_df[\"state\"].value_counts()"]},{"cell_type":"markdown","id":"e1f67b7a","metadata":{"papermill":{"duration":0.015549,"end_time":"2023-03-30T08:48:20.762396","exception":false,"start_time":"2023-03-30T08:48:20.746847","status":"completed"},"tags":[]},"source":["This chart looks a lot more accurate than the previous one. *Ikoyi* is still on top which is expected but now, it is not so far away from the other expensive towns."]},{"cell_type":"code","execution_count":11,"id":"dd0d9f40","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:20.796685Z","iopub.status.busy":"2023-03-30T08:48:20.79615Z","iopub.status.idle":"2023-03-30T08:48:21.119054Z","shell.execute_reply":"2023-03-30T08:48:21.117699Z"},"papermill":{"duration":0.344019,"end_time":"2023-03-30T08:48:21.122042","exception":false,"start_time":"2023-03-30T08:48:20.778023","status":"completed"},"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"}],"source":["(\n","    (trimmed_df.groupby(\"town\")['price']\n","    .mean()/1e6)\n","    .sort_values(ascending=False)\n","    .head(20)\n","    .plot(kind=\"bar\",\n","         xlabel = 'Towns',\n","         ylabel = \"Prices [₦1M]\",\n","         title = \"Most Expensive Real Estate Towns in Nigeria\")\n",");"]},{"cell_type":"markdown","id":"4c17c5d1","metadata":{"papermill":{"duration":0.015793,"end_time":"2023-03-30T08:48:21.154007","exception":false,"start_time":"2023-03-30T08:48:21.138214","status":"completed"},"tags":[]},"source":["As communicated by the dataset, Lagos State has the most expensive houses on average. Abuja comes in as the second most expensive.\n"]},{"cell_type":"code","execution_count":12,"id":"3538c998","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:21.189136Z","iopub.status.busy":"2023-03-30T08:48:21.188668Z","iopub.status.idle":"2023-03-30T08:48:21.411488Z","shell.execute_reply":"2023-03-30T08:48:21.409822Z"},"papermill":{"duration":0.244708,"end_time":"2023-03-30T08:48:21.415132","exception":false,"start_time":"2023-03-30T08:48:21.170424","status":"completed"},"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"}],"source":["#States with the highest mean prices\n","(\n","    (trimmed_df.groupby(\"state\")[\"price\"].mean()/1e6)\n","    .sort_values(ascending=False)\n","    .plot(kind=\"bar\",\n","         xlabel = \"States\", \n","         ylabel = \"Prices [₦1M]\",\n","          title = \"Average House Price by State\"\n","        )\n",");"]},{"cell_type":"code","execution_count":13,"id":"51cc4a07","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:21.453147Z","iopub.status.busy":"2023-03-30T08:48:21.452657Z","iopub.status.idle":"2023-03-30T08:48:21.463842Z","shell.execute_reply":"2023-03-30T08:48:21.462796Z"},"papermill":{"duration":0.033571,"end_time":"2023-03-30T08:48:21.466494","exception":false,"start_time":"2023-03-30T08:48:21.432923","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Lagos     13805\n","Abuja      2462\n","Rivers      339\n","Oyo         229\n","Imo         195\n","Ogun        141\n","Name: state, dtype: int64"]},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":["trimmed_df[\"state\"].value_counts()"]},{"cell_type":"code","execution_count":14,"id":"fd6d9d3f","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:21.503015Z","iopub.status.busy":"2023-03-30T08:48:21.502474Z","iopub.status.idle":"2023-03-30T08:48:21.742332Z","shell.execute_reply":"2023-03-30T08:48:21.741112Z"},"papermill":{"duration":0.261575,"end_time":"2023-03-30T08:48:21.745016","exception":false,"start_time":"2023-03-30T08:48:21.483441","status":"completed"},"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"}],"source":["(\n","    (trimmed_df.groupby(\"title\")[\"price\"]\n","     .mean()/1e6)\n","    .plot(kind=\"barh\",\n","          xlabel= 'House Type',\n","          ylabel = \"Prices [₦1M]\",\n","          title = \"Average Price by Type of House\"\n","         )\n",");"]},{"cell_type":"markdown","id":"2a97c14b","metadata":{"papermill":{"duration":0.01704,"end_time":"2023-03-30T08:48:21.779599","exception":false,"start_time":"2023-03-30T08:48:21.762559","status":"completed"},"tags":[]},"source":[]},{"cell_type":"code","execution_count":15,"id":"ece17307","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:21.81676Z","iopub.status.busy":"2023-03-30T08:48:21.815984Z","iopub.status.idle":"2023-03-30T08:48:22.084525Z","shell.execute_reply":"2023-03-30T08:48:22.083405Z"},"papermill":{"duration":0.290458,"end_time":"2023-03-30T08:48:22.08764","exception":false,"start_time":"2023-03-30T08:48:21.797182","status":"completed"},"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"}],"source":["trimmed_df_lagos = trimmed_df[trimmed_df[\"state\"]==\"Lagos\"]\n","(\n","    (trimmed_df_lagos.groupby(\"town\")[\"price\"].mean()/1e6)\n","    .sort_values(ascending=False)\n","    .head(10).plot(kind=\"bar\",\n","                   xlabel = \"Towns\",\n","                   ylabel = \"Prices [₦1M]\",\n","                   title = \"Average Price of Houses by Towns in Lagos\"\n","                  )\n",");"]},{"cell_type":"code","execution_count":16,"id":"7ab0158d","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:22.126912Z","iopub.status.busy":"2023-03-30T08:48:22.126353Z","iopub.status.idle":"2023-03-30T08:48:22.138488Z","shell.execute_reply":"2023-03-30T08:48:22.137065Z"},"papermill":{"duration":0.035288,"end_time":"2023-03-30T08:48:22.14157","exception":false,"start_time":"2023-03-30T08:48:22.106282","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Lekki                   9134\n","Ajah                    1797\n","Ikeja                    609\n","Magodo                   360\n","Victoria Island (VI)     300\n","Ikoyi                    255\n","Ibeju Lekki              193\n","Isheri North             183\n","Isolo                    164\n","Surulere                 106\n","Alimosho                  92\n","Yaba                      75\n","Maryland                  58\n","Agege                     56\n","Ojodu                     55\n","Gbagada                   51\n","Ikorodu                   49\n","Ogudu                     43\n","Amuwo Odofin              40\n","Ilupeju                   29\n","Ipaja                     22\n","Ikotun                    21\n","Shomolu                   15\n","Ojo                       15\n","Isheri                    15\n","Ketu                      13\n","Ifako-Ijaiye              13\n","Oshodi                     9\n","Ejigbo                     7\n","Idimu                      4\n","Kosofe                     3\n","Lagos Island               3\n","Agbara-Igbesa              3\n","Apapa                      3\n","Ijaiye                     2\n","Ayobo                      2\n","Ojota                      1\n","Epe                        1\n","Mushin                     1\n","Egbe                       1\n","Badagry                    1\n","Ijesha                     1\n","Name: town, dtype: int64"]},"execution_count":16,"metadata":{},"output_type":"execute_result"}],"source":["trimmed_df_lagos[\"town\"].value_counts()"]},{"cell_type":"code","execution_count":17,"id":"006773e2","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:22.179313Z","iopub.status.busy":"2023-03-30T08:48:22.178771Z","iopub.status.idle":"2023-03-30T08:48:22.191399Z","shell.execute_reply":"2023-03-30T08:48:22.190302Z"},"papermill":{"duration":0.03544,"end_time":"2023-03-30T08:48:22.194902","exception":false,"start_time":"2023-03-30T08:48:22.159462","status":"completed"},"tags":[]},"outputs":[],"source":["df_lekki = trimmed_df_lagos[trimmed_df_lagos['town']==\"Lekki\"].reset_index()\n","df_lekki.drop(columns=[\"index\", \"state\"], inplace=True)"]},{"cell_type":"code","execution_count":18,"id":"3df8af98","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:22.233713Z","iopub.status.busy":"2023-03-30T08:48:22.232462Z","iopub.status.idle":"2023-03-30T08:48:22.264767Z","shell.execute_reply":"2023-03-30T08:48:22.263734Z"},"papermill":{"duration":0.054905,"end_time":"2023-03-30T08:48:22.267938","exception":false,"start_time":"2023-03-30T08:48:22.213033","status":"completed"},"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>bedrooms</th>\n","      <th>bathrooms</th>\n","      <th>toilets</th>\n","      <th>parking_space</th>\n","      <th>price</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>9134.000000</td>\n","      <td>9134.000000</td>\n","      <td>9134.000000</td>\n","      <td>9134.000000</td>\n","      <td>9.134000e+03</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>4.471097</td>\n","      <td>4.697613</td>\n","      <td>5.427414</td>\n","      <td>3.986643</td>\n","      <td>1.074863e+08</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>0.681831</td>\n","      <td>0.763707</td>\n","      <td>0.760587</td>\n","      <td>1.121365</td>\n","      <td>4.855801e+07</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","      <td>3.500000e+07</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>4.000000</td>\n","      <td>4.000000</td>\n","      <td>5.000000</td>\n","      <td>4.000000</td>\n","      <td>7.000000e+07</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>5.000000</td>\n","      <td>5.000000</td>\n","      <td>5.000000</td>\n","      <td>4.000000</td>\n","      <td>9.500000e+07</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>5.000000</td>\n","      <td>5.000000</td>\n","      <td>6.000000</td>\n","      <td>4.000000</td>\n","      <td>1.300000e+08</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>9.000000</td>\n","      <td>9.000000</td>\n","      <td>9.000000</td>\n","      <td>9.000000</td>\n","      <td>2.600000e+08</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["          bedrooms    bathrooms      toilets  parking_space         price\n","count  9134.000000  9134.000000  9134.000000    9134.000000  9.134000e+03\n","mean      4.471097     4.697613     5.427414       3.986643  1.074863e+08\n","std       0.681831     0.763707     0.760587       1.121365  4.855801e+07\n","min       1.000000     1.000000     1.000000       1.000000  3.500000e+07\n","25%       4.000000     4.000000     5.000000       4.000000  7.000000e+07\n","50%       5.000000     5.000000     5.000000       4.000000  9.500000e+07\n","75%       5.000000     5.000000     6.000000       4.000000  1.300000e+08\n","max       9.000000     9.000000     9.000000       9.000000  2.600000e+08"]},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":["df_lekki.describe()"]},{"cell_type":"code","execution_count":19,"id":"7e306d3f","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:22.308468Z","iopub.status.busy":"2023-03-30T08:48:22.306922Z","iopub.status.idle":"2023-03-30T08:48:22.326712Z","shell.execute_reply":"2023-03-30T08:48:22.325393Z"},"papermill":{"duration":0.042583,"end_time":"2023-03-30T08:48:22.32951","exception":false,"start_time":"2023-03-30T08:48:22.286927","status":"completed"},"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>bedrooms</th>\n","      <th>bathrooms</th>\n","      <th>toilets</th>\n","      <th>parking_space</th>\n","      <th>house_type</th>\n","      <th>town</th>\n","      <th>price</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>120000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>2.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>75000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>65000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1.0</td>\n","      <td>1.0</td>\n","      <td>1.0</td>\n","      <td>1.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>200000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>6.0</td>\n","      <td>3.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>65000000.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   bedrooms  bathrooms  toilets  parking_space            house_type   town  \\\n","0       4.0        5.0      5.0            4.0       Detached Duplex  Lekki   \n","1       4.0        4.0      5.0            2.0  Semi Detached Duplex  Lekki   \n","2       4.0        5.0      5.0            4.0       Detached Duplex  Lekki   \n","3       1.0        1.0      1.0            1.0       Detached Duplex  Lekki   \n","4       4.0        5.0      6.0            3.0  Semi Detached Duplex  Lekki   \n","\n","         price  \n","0  120000000.0  \n","1   75000000.0  \n","2   65000000.0  \n","3  200000000.0  \n","4   65000000.0  "]},"execution_count":19,"metadata":{},"output_type":"execute_result"}],"source":["# Renaming the title column house_type\n","df_lekki.rename({\"title\": \"house_type\"}, axis = 1, inplace=True)\n","df_lekki.head()"]},{"cell_type":"code","execution_count":20,"id":"d40aa0ac","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:22.368936Z","iopub.status.busy":"2023-03-30T08:48:22.36845Z","iopub.status.idle":"2023-03-30T08:48:22.613938Z","shell.execute_reply":"2023-03-30T08:48:22.612746Z"},"papermill":{"duration":0.268637,"end_time":"2023-03-30T08:48:22.616982","exception":false,"start_time":"2023-03-30T08:48:22.348345","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Detached Duplex           6259\n","Semi Detached Duplex      1376\n","Terraced Duplexes         1232\n","Block of Flats             169\n","Semi Detached Bungalow      41\n","Detached Bungalow           38\n","Terraced Bungalow           19\n","Name: house_type, dtype: int64\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfIAAAEICAYAAACkmHavAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAAwhUlEQVR4nO3debxd0/3/8ddbRhGSqtBrTKtRNQaJqaKhMTZEi6pSoSr00aJKKzqgLd+fVltKqr4UoVVDDaX0i6Ah1HQTGQShJIYIMTU1Jk18fn+sdWU7ucO5N3faN+/n43EeZ8/rs85O7mevtfY5WxGBmZmZldNKHR2AmZmZtZwTuZmZWYk5kZuZmZWYE7mZmVmJOZGbmZmVmBO5mZlZiTmRm1mrk3ShpJ+08jFPl/Sn1jymNUzSTEnD27G84ZJebMG6YZJmtW10nZsTuVkbkTRR0puSenV0LMsrJ9H/Snpb0r8l/VPSDg1tHxHHRMTP2zPG5pA0R9KIimWHS7qvo2IqkvTD/Fm/Lel9SUsK8zPbI4aI2DQiJrZkX0kh6dOtHFK9ImJSRHymPcrqrJzIzdqApIHAMCCAfdvg+N1b+5hVuCYi+gIDgPuAGySpciNJ3do9si4mIv4nIvrmz/sY4IG6+YjYtKPjs87FidysbRwGPAiMB0YDSOqVW7Ob1W0kaYCk9yStmedHSppaaPVuUdh2jqSTJU0H3pHUXdJYSc9IekvS45K+VNi+m6RfS3pN0mxJ38ktpe55fT9Jl0iaJ2mupDOqScIR8V/gcuATwMcljZf0e0l/l/QOsEtedkYhllG5Xv/J8e7Zwhh6S7om13eKpC3zcb4v6frihpLOk/TbpurTEEmfzb0q/87dzPsW1k2U9M3C/IeteSXnSJqf6zuj7pznfwO/kvS8pFfyEMTKzYip0XrmuP6fpIdz2TdJWr2w7fb539W/JU1TI13nxV6L3CNzraQr8mc/U9KQauMuHLPq+ks6Lv+bXrexdWqk231F4URu1jYOA67Mrz0krRURC4EbgIML230FuCci5kvaCrgUOBr4OPC/wM36aNf8wcAXgf4RsRh4htTy7wf8FPiTpJq87VHAXsBgYGtgv4oYxwOLgU8DWwG7A9+kCTmew4EXIuK1vPhrwJnAqqTWenH7bYErgO8D/YGdgTktjGEU8BdgdeDPwF8l9QD+BOwpqX8uszvw1Vxus+Vj/g24A1gTOBa4UlI1Xbi7k+q4Eem8fAV4Pa87Ky8fTKrzOsCpzQitmnoeBnwDqCF9tuflbdcBbgXOIH1+JwHXSxpQZdn7AleTzuHNwLhmxF2nqvpLOpX0b+zzEfFitetWWBHhl19+teIL2An4L7BGnn8SOCFPjwCeKWx7P3BYnv498POKY80i/cGClPy+0UTZU4FRefpu4OjCuhGkrv7uwFrAQmDlwvqDgX80cNzTgUXAv4H5+djb5HXjgSsqth8PnJGn/xc4p55jtiSGBwvzKwHzgGF5/v+Ao/L0SODxRj6nOcDbuT51r3eB+/L6YcDLwEqFfa4CTs/TE4FvFtYdXth3V+ApYPuK/QW8A2xYWLYDMLuJc/rhsZuqZ47rrML8Jvm8dQNOBv5YcezbgdGNfEYjCp/9nRXHfa+RmAP4dMWyRusPDAfmAr8hXQz2K2zX1LoXW/r/tSu8OmKczayrGw3cEUtbq3/Oy84B/gH0kbQd8AqpZXJj3m4DYLSkYwvH6gmsXZh/oViQpMOA7wED86K+wBp5eu2K7YvTGwA9gHlaOsy9UuXxK1wbEYc2sK6x/dYD/l7P8pbE8OG6iPggd6nWfT6XA98CLgYOBf7YyHEA9ouIO+tmJB3O0t6AtUk9Dh8Utn+O1IJsVETcLWkc8DtgA0k3kFq/vYE+wORCfUVKss3RVD2Ln99zpM94DdLnfaCkfQrre5D+TVbj5cL0u6Rhju6ReoaqMYCm698fGAMcFBELKvZvbN0KzYncrBXl8b6vAN0k1f3h6wX0l7RlREyTdC2p5fkKcEtEvJW3ewE4MyLObKSIDx9XKGkD0h/zL5BuhloiaSrpjyOk1mpxfHG9wvQLpNbwGs34Q9yYxh6j+AKwYQPLmxvDh3WQtBKpfi/lRX8Ffp/Ho0cCP6jymPV5CVhP0kqFZL4+qaUNqWXZp7D9J4o7R8R5wHlK9z5cSxpWOA14D9g0IuYuR2x/pfF6Fs/z+qTeoddIn/cfI+Ko5Sh7ebxG0/V/k3Rxcq2kL0XE/VWuW6F5jNysde0HLCF1PQ7Or88Ck0hjl5Ba6AcBh+TpOhcDx0jaLt8wtYqkL0patYGyViEl0FcBJB0BbFZYfy1wvKR18pjqyXUrImIeafz315JWk7SSpA0lfb6lFW/EJcARkr6Qy1lH0sYtjGEbSV/OY8PfJV0IPJjr9D5wHekzfTginl+OmB8itTp/IKlHvilsH9IYMaQhjC9L6qP0Nasj63aUNDSfwx6khP8+8EG+ILgYOEdLb25cR9IezQmsinoeKmkTSX2AnwHXRcQS0vj6PpL2ULoRsne+UWyZm8laSc9cRm9JvUkXmE3WP9JX3g4hfSti22rXrcicyM1a12jgsoh4PiJernuRbgw6JHdFPkT6A782abwTgIioJd2gNo7U+vgXaXy0XhHxOPBr4AFS635z0ph7nYtJiXI68Cipe3sx6UID0oVFT+DxXN51pBukWlVEPAwcQRpaWADcQ+rmbUkMN5Eugt4Evg58OdJd9HUuJ30OTXWrNxXzIlLi3ovUkryAdC/Dk3mTc0hjz6/kMq8s7L4a6bN/k9S1/Tpwdl53Mum8PijpP8CdQEu+A91YPf9IukfhZVJ3/nG5Ti+Qbhb8Ieni7wVST0Fb5YGZpBZ43esIqqx/REwg3bD3N0lbV7tuRaV8s4CZdXGS9gIujIgNmty4pCStT7q58BMR8Z+OjqetNFRPSROBP0XEHzoqNmt/bpGbdVGSVpa0t9L3zdchjdHe2NR+ZZXHzL8HXN3Fk/gKUU+rnm92M+u6RPpu+TWkrs1bad53lktD0iqkbu7ngD07OJw2s6LU05rHXetmZmYl5q51MzOzEnPXurW7NdZYIwYOHNjRYZiZlcrkyZNfi4hlflLXidza3cCBA6mtre3oMMzMSkXSc/Utd9e6mZlZiTmRm5mZlZgTuZmZWYk5kZuZmZWYE7mZmVmJOZGbmZmVmL9+Zu1uxtwFDBx7a0eHYSU356wvdnQIZp2CW+RmZmYl5kRuZmZWYk7kZmZmJeZEbmZmVmJO5K1M0hJJUyVNkzRF0o55+UBJj7XwmHMkrdHCfQ+U9ISkf1QsHyjpvRxr3aunpMMljWvimMPr6mVmZh3Ld623vvciYjCApD2A/wd8vgPjORI4KiLuq2fdM3Wx1pFUzTGHA28D/1ze4MzMbPm4Rd62VgPerFwoqbekyyTNkPSopF3y8m6SfiXpMUnTJR1bsd/Kkv5P0lH1HPPgfLzHJP0iLzsV2Am4RNLZzQ1e0j6SHsox3ilpLUkDgWOAE3Irflhu9T+WeyHubW45ZmbWcm6Rt76VJU0FegM1wK71bPNtICJic0kbA3dI2gg4AhgIDI6IxZJWL+zTF7gauCIirigeTNLawC+AbUgXDndI2i8ifiZpV+CkiKjvuaEb5lgB7o+Ib1esvw/YPiJC0jeBH0TEiZIuBN6OiF/l8mcAe0TEXEn96/tQJI0BxgB0W22Zx+mamVkLOZG3vmLX+g7AFZI2q9hmJ+B8gIh4Mj9jdiNgBHBhRCzO694o7HMT8MuIuLKeMocCEyPi1VzulcDOwF+biHWZrvUK6wLXSKoBegKzG9jufmC8pGuBG+rbICIuAi4C6FUzKJqIy8zMquSu9TYUEQ8AawCt0QS9H9hTVQ5it5LzgXERsTlwNKmXYRkRcQzwY2A9YLKkj7dfiGZmKzYn8jaUu827Aa9XrJoEHJK32QhYH5gFTACOltQ9ryt2rZ9K6jb/XT1FPQx8XtIakroBBwP3tEIV+gFz8/TowvK3gFXrZiRtGBEPRcSpwKukhG5mZu3Aibz1rVz3dS7gGmB0RCyp2OYCYKU8tnwNcHhELAT+ADwPTJc0DfhaxX7H5+P/srgwIuYBY4F/ANOAyRFxUyvU5XTgL5ImA68Vlv8N+FLdzW7A2XU32pHuZJ/WCmWbmVkVFOHhSmtfvWoGRc3oczs6DCs5PzTFVjSSJkfEkMrlbpGbmZmVmBO5mZlZifnrZ9buNl+nH7XuFjUzaxVukZuZmZWYE7mZmVmJOZGbmZmVmBO5mZlZiTmRm5mZlZgTuZmZWYk5kZuZmZWYE7mZmVmJOZGbmZmVmBO5mZlZiTmRm5mZlZgTuZmZWYk5kZuZmZWYE7mZmVmJ+TGm1u5mzF3AwLG3dnQY1sXM8aNxbQXlFrmZmVmJOZGbmZmVmBO5mZlZiTmRm5mZlViXSeSSlkiaKmmmpGmSTpTUaP0kDZT0teUoc6KkIcux/3hJBzSwfHauz5OSTmtpGS2M63RJJ7VnmWZm1jJdJpED70XE4IjYFNgN2AtoKgEOBFqcyNvY9yNiMDAYGC3pkx0bjpmZdUZdKZF/KCLmA2OA7yjpJulsSY9Imi7p6LzpWcCw3PI9IbfQJ0makl871h1T0smSZuTW/lmF4g6U9LCkpyQNy9vWW16OZZykWZLuBNasojq98/s7+RhzJK2Rp4dImpinT5d0ae4leFbScYXYf5LLvE/SVXWtbUlH5RinSbpeUp/KwiUNlvRgrseNkj4maU1Jk/P6LSWFpPXz/DP1HcfMzNpGl0zkABHxLNCNlCyPBBZExFBgKHBUbuGOBSbllvw5wHxgt4jYGjgIOA9A0l7AKGC7iNgS+GWhqO4RsS3wXZb2ADRU3peAzwCbAIcBO9KwsyVNBV4Ers4XJ03ZGNgD2BY4TVIPSUOB/YEtSb0UxaGAGyJiaK7TEznuSlcAJ0fEFsAM4LQcS29JqwHDgFrSBdEGwPyIeLfyIJLGSKqVVLvk3QVVVMXMzKqxovwgzO7AFoXx6H7AIGBRxXY9gHGSBgNLgI3y8hHAZXUJKiLeKOxzQ36fTOqqb6y8nYGrImIJ8JKkuxuJ+fsRcZ2kvsBdknaMiH82Uc9bI2IhsFDSfGAt4HPATRHxPvC+pL8Vtt9M0hlAf6AvcHvxYJL6Af0j4p686HLgL3n6n/nYOwP/A+wJCJhUX2ARcRFwEUCvmkHRRD3MzKxKXTaRS/oUKRnPJyWYYyOiMlENr9jtBOAVUut1JeD9KopamN+XsPTzbKi8vauvQRIRb+fu851IyXMxS3tSeldsvrAwXYynIeOB/SJimqTDgeHNCO1eUmt8A+Am4GQgAP9km5lZO+qSXeuSBgAXAuMiIkgtzW9J6pHXbyRpFeAtYNXCrv2AeRHxAfB1Utc8wATgiLqxX0mrNxFCQ+XdCxyUx9BrgF2qqEt3YDvgmbxoDrBNnt6/qf2B+4F9JPXOrfuRhXWrAvNynIdU7hgRC4A368b+SZ9JXet8EnAo8HT+vN4A9gbuqyImMzNrJV2pRb5yHlPuQWq1/hH4TV73B1K39xRJAl4F9gOmA0skTSO1Ti8Arpd0GHAb+QaziLgtd7fXSloE/B34YSOxNFTejcCuwOPA88ADjRzjbEk/BnoCd7G0C/+nwCWSfg5MbOwDybE/IunmXNdXSOPcdYPUPwEeyvE9xEcvauqMBi7MFzHPAkfk487Jdbs3b3cfsG5EvNlUTGZm1nqUGqzWlUnqm7vo+5AS75iImNJR8fSqGRQ1o8/tqOKti/JDU6yrkzQ5Ipb57ZKu1CK3hl0kaRPSmPrlHZnEzcysdTmRrwAiorP+6I2ZmS0nJ3Jrd5uv049ad4OambWKLnnXupmZ2YrCidzMzKzEnMjNzMxKzInczMysxJzIzczMSsyJ3MzMrMScyM3MzErMidzMzKzEnMjNzMxKzInczMysxJzIzczMSsyJ3MzMrMScyM3MzErMidzMzKzE/BhTa3cz5i5g4NhbOzoMM+b4cbrWBbhFbmZmVmJO5GZmZiXmRG5mZlZiTuRmZmYl1qUTuaSPS5qaXy9LmluY79kJ4hsu6ZYGli/IcU6XdKekNdsxroGSHmuv8szMrOW6dCKPiNcjYnBEDAYuBM6pm4+IRQ3tJ6l7Y/PtZFKOcwvgEeDbHRCDmZl1cl06kddH0jaS7pE0WdLtkmry8omSzpVUCxxfz/w+kh6S9GhuIa+V9+sr6TJJM3Lref+8fHdJD0iaIukvkvrm5XtKelLSFODLVcQrYFXgzTx/uqSTCusfyy3ogZKekHSxpJmS7pC0ct5maI5tqqSz61rbeZ9JOcYpknasp/zehfo9KmmXvPxWSVvk6UclnZqnfybpqBaeHjMza6YVLZELOB84ICK2AS4Fziys7xkRQyLi1/XM3wdsHxFbAVcDP8jb/ARYEBGb59bz3ZLWAH4MjIiIrYFa4HuSegMXA/sA2wCfaCTWYZKmAs8DI3KsTRkE/C4iNgX+Deyfl18GHJ17JpYUtp8P7JZjPAg4r55jfhuIiNgcOBi4PNdjUo6xH7AY+Fxd3MC9lQeRNEZSraTaJe8uqKIqZmZWjRXtB2F6AZsBE1JDl27AvML6ayq2L86vC1yTW/A9gdl5+Qjgq3UbRcSbkkYCmwD353J6Ag8AGwOzI+JpAEl/AsY0EOukiBiZtzsZ+CVwTBP1mx0RU/P0ZGCgpP7AqhHxQF7+Z2Bknu4BjJM0mJTgN6rnmDuRLn6IiCclPZe3mwQclz+HW4HdJPUBPhkRsyoPEhEXARcB9KoZFE3Uw8zMqrSiJXIBMyNihwbWv9PI/PnAbyLiZknDgdObKGdCRBz8kYUpYbbEzcD1eXoxH+1J6V2YXliYXgKs3MRxTwBeAbbMx3y/GTE9AgwBngUmAGsAR5EuIMzMrJ2saF3rC4EBknYAkNRD0qZV7tsPmJunRxeWT6BwI5qkjwEPAp+T9Om8bBVJGwFPklrJG+bNP5LoG7ET8EyengNsnY+7NfDJxnaMiH8Db0naLi/6amF1P2BeRHwAfJ3UQ1FpEnBILm8jYH1gVr5Z8AXgQFJvwyTgJOrpVjczs7bTZCJXcmjhZqb1JW3b9qG1iQ+AA4BfSJoGTAWWucGrAacDf5E0GXitsPwM4GP5prNpwC4R8SpwOHCVpOnkbvWIeJ/UlX5rvtltfiPlDcs3p00jJdkT8/LrgdUlzQS+AzxVRexHAhfnMfdVgLpB6guA0bmMjVm2R6Jum5UkzSANNRweEXUt/0nA/Ih4L0+vm9/NzKydKKLx4UpJvyclwF0j4rO5xXlHRAxtjwBt+UnqGxFv5+mxQE1EHN9R8fSqGRQ1o8/tqOLNPuSHpliZSJocEUMql1czRr5dRGwt6VH48GauDv8xFWuWL0o6hXS+nyP1FpiZWRdQTSL/r6RuQABIGkBqoVtJRMQ1LHtHvpmZdQHVJPLzgBuBtSSdSRpj/nGbRmVd2ubr9KPWXZpmZq2iyUQeEVfmG7y+kBftFxFPtG1YZmZmVo1qv0feh/TVpKDp7yabmZlZO6nm62enApcDq5N+9OMySe5aNzMz6wSqaZEfAmyZvwONpLNI378+ow3jMjMzsypU88tuL/HRnwHtxdJfODMzM7MOVE2LfAEwU9IE0hj5bsDDks4DiIjj2jA+MzMza0Q1ifzG/KozsW1CMTMzs+aqJpG/AdyaH6xhZmZmnUg1Y+QHAU9L+qWkjds6IDMzM6tek4k8Ig4FtiI9RnO8pAckjZG0aptHZ2ZmZo2q6nnkEfEf4DrgaqAG+BIwRdKxbRibmZmZNaHBRC7py/l9X0k3km5y6wFsGxF7AVuy9BnZZmZm1gEau9ntx8ANwP7AORFxb3FlRLwr6ci2DM7MzMwaV81DU0Y3su6u1g3HzMzMmqOxRL6xpOn1LBcQEbFFG8VkXdyMuQsYOPbWjg7DrM3N8eN6rR00lshnA/u0VyBmZmbWfI0l8kUR8Vy7RWJmZmbN1tjXz+5vtyjMzMysRRpM5BHxnfYMxMzMzJqvqh+EaQlJP5I0U9J0SVMlbddKx/1nA8uX5HJmSpom6URJjdZP0kBJX1uOWCZKGrIc+4+XdEADy2fn+jwp6bSWltHCuE6XdFJ7lmlmZi1TzUNTmk3SDsBIYOuIWChpDaBnaxw7InZsYNV7ETE4l78m8GdgNaCxJDgQ+FretrP5fkRcJ6k38LikKyJidkcHZWZmnUuTLXJJfST9RNLFeX6QpJFN7FYDvBYRCwEi4rWIeCnvv42keyRNlnS7pJq8fKKkcyTVSnpC0lBJN0h6WtIZhXjebirmiJgPjAG+o6SbpLMlPZJ7CI7Om54FDMst3xNyC32SpCn59eFFg6STJc3Irf2zCsUdKOlhSU9JGpa3rbe8HMs4SbMk3Qms2VRdgN75/Z18jDn5wghJQyRNzNOnS7o0f47PSvrwOfH5/M2SdJ+kq+pa25KOyjFOk3S9pD6VhUsaLOnBXI8bJX1M0pqSJuf1W0oKSevn+WfqO46ZmbWNarrWLwMWAjvk+bnAGQ1vDsAdwHo5uV0g6fMAknoA5wMHRMQ2wKXAmYX9FkXEEOBC4Cbg28BmwOGSPl5lnQCIiGeBbqRkeSSwICKGAkOBoyR9EhgLTIqIwRFxDjAf2C0itiY99e28HPdewChgu4jYEvhloajuEbEt8F2Wtv4bKu9LwGeATYDDgIZ6FwDOljQVeBG4Ol+cNGVjYA9gW+A0ST0kDSX9Ot+WwF5AcSjghogYmuv0RI670hXAyfl3A2YAp+VYektaDRgG1JIuiDYA5kfEu5UHUXrQTq2k2iXvLqiiKmZmVo1qutY3jIiDJB0MH/40qxrbISLelrQN6Y/8LsA1ksaS/uBvBkzIh+gGzCvsenN+nwHMjIh5AJKeBdYDXq+6Zh+1O7BFYTy6HzAIWFSxXQ9gnKTBwBJgo7x8BHBZXYKKiDcK+9yQ3yeTuuobK29n4KqIWAK8JOnuRmKu61rvC9wlaceIqPf+gIJbcy/IQknzgbWAzwE3RcT7wPuS/lbYfrPc29Ef6AvcXjyYpH5A/4i4Jy+6HPhLnv5nPvbOwP8Ae5J+LGhSfYFFxEXARQC9agZFE/UwM7MqVZPIF0laGQgASRuSWuiNyslqIjBR0gxgNCnZzYyIHRrYre64H1SU8UGVsX5I0qdIyXg+KcEcGxGViWp4xW4nAK+QWq8rAe9XUVRdnEsKMTZU3t7V1yDJF0UTgZ1IyXMxS3tSeldsXvzMivE0ZDywX0RMk3Q4MLwZod1LulDbgNR7cjLp34h/ss3MrB1V07V+GnAbqav8SuAu4AeN7SDpM5IGFRYNBp4DZgEDlG6GI3f9btqSwJsofwCpe35cRASppfmt3LWPpI0krQK8BRSfq94PmBcRHwBfJ/UYAEwAjqgb+5W0ehMhNFTevcBBeQy9htRb0VRdugPbkZ4HDzAH2CZP79/U/qTfA9hHUu/cui/e37AqMC/HeUjljhGxAHizbuyf9JnUtc4nAYcCT+fP6w1gb+C+KmIyM7NWUs1DUyZImgJsT2ppHh8RrzWxW1/gfEn9SS3IfwFjImJR7m4+L3fbdgfOBWa2vAofWjmPKffIZf4R+E1e9wdSt/eUPCzwKrAfMB1YImkaqXV6AXC9pMNIFy/vAETEbbm7vVbSIuDvwA8biaWh8m4EdgUeB54HHmjkGGdL+jHpbv+7WNqF/1PgEkk/J/V4NCoiHpF0c67rK6Rhi7pB6p8AD+X4HuKjFzV1RgMX5ouYZ4Ej8nHn5LrVPRXvPmDdiHizqZjMzKz1KDVYG9lA+hwwNSLekXQosDXwW/98a3lI6pu76PuQEu+YiJjSUfH0qhkUNaPP7ajizdqNH5pirUnS5HxD+EdU07X+e+BdSVsC3yN18V7RyvFZ27oo91ZMAa7vyCRuZmatq5obyBZHREgaBfwuIi6RVN/XlKyTiogW/3qdmZl1btUk8rcknUK6sWlnpZ897dG2YVlXtvk6/ah1l6OZWauopmv9INLXmo6MiJeBdYGz2zQqMzMzq0o1d62/zNK7v4mI5/EYuZmZWafQZCKX9Bb5x2BIX4XqAbwdEf3aMjAzMzNrWjUt8g+/W5y/NzyK9J1yMzMz62DNeh55JH8lPZjDzMzMOlg1XetfLsyuRHp6VjW/QW5mZmZtrJqvn+1TmF5M+q3vUW0SjZmZmTVLNWPkR7RHIGZmZtZ8TY6RS1pX0o2S5ufX9ZLWbY/gzMzMrHHV3Ox2GXAzsHZ+/S0vMzMzsw5WTSIfEBGXRcTi/BoPDGjjuMzMzKwK1STy1yUdKqlbfh0KvN7WgZmZmVnTqknk3wC+ArwMzAMOAHwDnJmZWSdQzV3rzwH7tkMsZmZm1kwNJnJJ57P0N9aXERHHtUlE1uXNmLuAgWNv7egwzDqNOX6sry2HxlrktYXpnwKntXEsZmZm1kwNJvKIuLxuWtJ3i/NmZmbWOVT70JQGu9jNzMys4zTr6WdmZmbWuTSYyCW9Jek/kv4DbFE3Xbe8HWNsFZI+Lmlqfr0saW5hvmcniG+4pFsaWL5A0qOSZkm6V9LI5SxrjqQ1lucYZmbWOTQ2Rr5qewbS1iLidWAwgKTTgbcj4ldN7Sepe0Qsbmi+nUyKiJG5/MHAXyW9FxF3tXMcZmbWyazQXeuStpF0j6TJkm6XVJOXT5R0rqRa4Ph65veR9FBuJd8paa28X19Jl0maIWm6pP3z8t0lPSBpiqS/SOqbl+8p6UlJU4AvNxDmR0TEVOBnwHfyMcZLOqBQp7fz+/Dcer81t+QvlLTM+c6/2vdw7pn43/zrfUNz/L0lrSJppqTN8vSleftHJY3Kx9i0cIzpkga19JyYmVnzrMiJXMD5wAERsQ1wKXBmYX3PiBgSEb+uZ/4+YPuI2Aq4GvhB3uYnwIKI2DwitgDuzl3YPwZGRMTWpK/1fU9Sb+Bi0vPetwE+0YzYpwAbV7HdtsCxwCbAhlRcLEj6LHAQ8LmIGAwsAQ6JiEdID8o5A/gl8KeIeAz4EXB3RGwL7AKcLWkV4Bjgt/kYQ4AXKwORNEZSraTaJe8uaEZVzcysMU3+slsX1gvYDJggCaAb6Sdo61xTsX1xfl3gmtyC7wnMzstHAF+t2ygi3szj2ZsA9+dyegIPkBLx7Ih4GkDSn4AxVcauKrd7OCKezce/CtgJuK6w/guki4hHcmwrA/Pzup8BjwDvA3U//rM7sK+kk/J8b2D9XJ8f5cfb3lBXp6KIuAi4CKBXzSB/C8LMrJWsyIlcwMyI2KGB9e80Mn8+8JuIuFnScOD0JsqZEBEHf2RhGutuqa2AJ/L0YnLPSu46L964V5kwK+cFXB4Rp9RTxseBvkAPUsJ+J2+/f0TMqtj2CUkPAV8E/i7p6Ii4u3lVMjOzlliRu9YXAgMk7QAgqYekTavctx8wN0+PLiyfAHy7bkbSx4AHgc9J+nRetoqkjYAngYGSNsybfyTRN0TSFqQu/N/lRXNIrWpIv4nfo7D5tpI+mRP8QaQhgaK7gAMkrZmPvbqkDfK6/83lXAn8Ii+7HThWufkuaav8/ing2Yg4D7gJ2KKaupiZ2fJbkRP5B6Qnuf1C0jRgKrBjlfueDvxF0mTgtcLyM4CPSXosH3OXiHgVOBy4StJ0crd6RLxP6kq/Nd/sNp+GDav7+hkpgR9XuGP9YuDzubwd+GjPwSPAOFLrfTZwY/GgEfE4afz+jhzbBKBG0mHAfyPiz8BZwFBJuwI/J10oTJc0M89DejreY5KmkoYrrmj84zMzs9aiCA9XdkW5y/+kuq+tdSa9agZFzehzOzoMs07DD02xakiaHBFDKpevyC1yMzOz0luRb3br0iJiIjCxg8MwM7M25kRu7W7zdfpR665EM7NW4a51MzOzEnMiNzMzKzEncjMzsxJzIjczMysxJ3IzM7MScyI3MzMrMSdyMzOzEnMiNzMzKzEncjMzsxJzIjczMysxJ3IzM7MScyI3MzMrMSdyMzOzEnMiNzMzKzE/xtTa3Yy5Cxg49taODsOsS5jjRwKv8NwiNzMzKzEncjMzsxJzIjczMysxJ3IzM7MS63SJXNKPJM2UNF3SVEnbtdJx/9nA8iW5nJmSpkk6UVKjn4ukgZK+thyxTJQ0ZDn2Hy/pgAaWz871eErSFZLWXY5yhku6paX7m5lZ2+tUiVzSDsBIYOuI2AIYAbzQGseOiB0bWPVeRAyOiE2B3YC9gNOaONxAoMWJvI19PyK2BD4DPArcLalnB8dkZmZtpFMlcqAGeC0iFgJExGsR8RKApG0k3SNpsqTbJdXk5RMlnSOpVtITkoZKukHS05LOqDuwpLebKjwi5gNjgO8o6SbpbEmP5B6Co/OmZwHDckv+hNxCnyRpSn59eNEg6WRJM3Ir+axCcQdKeji3nIflbestL8cyTtIsSXcCa1ZRl4iIc4CXSRcnH/kMJB0gaXyeHi/pwvwZPiVpZOXxJK0i6dIc86OSRuXlv5V0ap7eQ9K9TfVomJlZ6+ls3yO/AzhV0lPAncA1EXGPpB7A+cCoiHhV0kHAmcA38n6LImKIpOOBm4BtgDeAZySdExGvVxtARDwrqRspWY4CFkTEUEm9gPsl3QGMBU6KiJEAkvoAu0XE+5IGAVcBQyTtlY+xXUS8K2n1QlHdI2JbSXuTegBGAEc2UN5WpBb2JsBawOPApVVWaQqwcf5cGjMQ2BbYEPiHpE9XrP8RcHdEfENSf+DhfFFxCvCIpEnAecDeEfFB5cEljSFdJNFttQFVhm5mZk3pVIk8It6WtA0wDNgFuEbSWKAW2AyYIAmgGzCvsOvN+X0GMDMi5gFIehZYD6g6kVfYHdiiMB7dDxgELKrYrgcwTtJgYAmwUV4+ArgsIt7N9XujsM8N+X0yKYk2Vt7OwFURsQR4SdLdzaiDqtzu2pyAn86f28YV63cH9pV0Up7vDawfEU9IOgq4FzghIp6p7+ARcRFwEUCvmkHRjPjNzKwRnSqRA+RkNRGYKGkGMJqU7GZGxA4N7LYwv39QmK6bb1YdJX2KlIznk5LgsRFxe8U2wyt2OwF4BdiSNFzxfhVF1cW5pBBjQ+XtXX0NlrEVcFeeLibQ3hXbVSbXynkB+0fErHrK2Jx0sbR2S4M0M7OW6VRjmZI+k7um6wwGngNmAQPyzXBI6iFp0zYofwBwITAuIgK4HfhW7tpH0kaSVgHeAlYt7NoPmJdbtF8n9RgATACOyF3vVHSt16eh8u4FDspj6DWk3oqm6iJJx5HuO7gtL35F0mfzGPaXKnY5UNJKkjYEPkX6zCtjO1a5S0TSVvl9A+BE0gXDXmqlbxmYmVl1OluLvC9wfh6DXQz8CxgTEYtyd/N5kvqR4j4XmNkKZa4saSqpe3wx8EfgN3ndH0jd3lNyAnsV2A+YDiyRNA0YD1wAXC/pMFLSfAcgIm7L3e21khYBfwd+2EgsDZV3I7AraWz8eeCBRo5xtqSfAH2AB4FdIqJuKGAscEs+bi3p867zPPAwsBpwTB7vLx7356TPfHq+EJgtaR/gEtL9Ai9JOhIYL2loRFTTK2FmZstJqeFpK7J89/otEXFde5TXq2ZQ1Iw+tz2KMuvy/NCUFYekyRGxzG+QdKqudTMzM2uezta1bh0gIg7v6BjMzKxlnMit3W2+Tj9q3R1oZtYq3LVuZmZWYk7kZmZmJeZEbmZmVmJO5GZmZiXmRG5mZlZiTuRmZmYl5kRuZmZWYk7kZmZmJeZEbmZmVmJO5GZmZiXmRG5mZlZiTuRmZmYl5kRuZmZWYk7kZmZmJeZEbmZmVmJ+Hrm1uxlzFzBw7K0dHYaZWbuac9YX2+S4bpGbmZmVmBO5mZlZiTmRm5mZldgKn8glLZE0VdJMSdMknSip0c9F0kBJX1uOMidKGrIc+4+XdEADy2fnejwl6QpJ6y5HOcMl3dLS/c3MrO2t8IkceC8iBkfEpsBuwF7AaU3sMxBocSJvY9+PiC2BzwCPAndL6tnBMZmZWRtxIi+IiPnAGOA7SrpJOlvSI5KmSzo6b3oWMCy35E/ILfRJkqbk1451x5R0sqQZuZV8VqG4AyU9nFvOw/K29ZaXYxknaZakO4E1q6hLRMQ5wMukixMkvV2I6wBJ4/P0eEkXSqrN8YysPJ6kVSRdmmN+VNKovPy3kk7N03tIurepHg0zM2s9/vpZhYh4VlI3UrIcBSyIiKGSegH3S7oDGAucFBEjAST1AXaLiPclDQKuAoZI2isfY7uIeFfS6oWiukfEtpL2JvUAjACObKC8rUgt7E2AtYDHgUurrNIUYGPgpia2GwhsC2wI/EPSpyvW/wi4OyK+Iak/8HC+qDgFeETSJOA8YO+I+KDy4JLGkC6S6LbagCpDNzOzpjiRN253YIvCeHQ/YBCwqGK7HsA4SYOBJcBGefkI4LKIeBcgIt4o7HNDfp9MSqKNlbczcFVELAFeknR3M+qgKre7NifgpyU9S0r+RbsD+0o6Kc/3BtaPiCckHQXcC5wQEc/Ud/CIuAi4CKBXzaBoRvxmZtYIJ/IKkj5FSsbzSUnw2Ii4vWKb4RW7nQC8AmxJGq54v4qiFub3JSw9Dw2Vt3f1NVjGVsBdebqYQHtXbFeZXCvnBewfEbPqKWNz4HVg7ZYGaWZmLeOxzAJJA4ALgXEREcDtwLck9cjrN5K0CvAWsGph137AvNyi/TrQLS+fAByRu96p6FqvT0Pl3QsclMfQa4BdqqiLJB0H1AC35cWvSPpsHsP+UsUuB0paSdKGwKeAyoR9O3CsJOXjb5XfNwBOJF0w7CVpu6ZiMzOz1uMWOawsaSqpe3wx8EfgN3ndH0jd3lNyAnsV2A+YDiyRNA0YD1wAXC/pMFLSfAcgIm7L3e21khYBfwd+2EgsDZV3I7AraWz8eeCBRo5xtqSfAH2AB4FdIqJuKGAscEs+bi3Qt7Df88DDwGrAMXm8v3jcnwPnAtPzhcBsSfsAl5DuF3hJ0pHAeElDI6KaXgkzM1tOSg1PW5Hlu9dviYjr2qO8XjWDomb0ue1RlJlZp7G8v7UuaXJELPMbJO5aNzMzKzF3rRsRcXhHx2BmZi3jRG7tbvN1+lHbRo/zMzNb0bhr3czMrMScyM3MzErMidzMzKzEnMjNzMxKzInczMysxJzIzczMSsyJ3MzMrMT8E63W7iS9xbIPZSmzNYDXOjqIVtTV6gNdr05drT7Q9erUFvXZICIGVC70D8JYR5hV3+8Fl5WkWtenc+tqdepq9YGuV6f2rI+71s3MzErMidzMzKzEnMitI1zU0QG0Mten8+tqdepq9YGuV6d2q49vdjMzMysxt8jNzMxKzInczMysxJzIrd1I2lPSLEn/kjS2o+NpCUnrSfqHpMclzZR0fF6+uqQJkp7O7x/r6FibQ1I3SY9KuiXPf1LSQ/lcXSOpZ0fHWC1J/SVdJ+lJSU9I2qELnJ8T8r+3xyRdJal3mc6RpEslzZf0WGFZvedEyXm5XtMlbd1xkTesgTqdnf/dTZd0o6T+hXWn5DrNkrRHa8biRG7tQlI34HfAXsAmwMGSNunYqFpkMXBiRGwCbA98O9djLHBXRAwC7srzZXI88ERh/hfAORHxaeBN4MgOiaplfgvcFhEbA1uS6lXa8yNpHeA4YEhEbAZ0A75Kuc7ReGDPimUNnZO9gEH5NQb4fTvF2FzjWbZOE4DNImIL4CngFID8N+KrwKZ5nwvy38RW4URu7WVb4F8R8WxELAKuBkZ1cEzNFhHzImJKnn6LlCTWIdXl8rzZ5cB+HRJgC0haF/gi8Ic8L2BX4Lq8SWnqI6kfsDNwCUBELIqIf1Pi85N1B1aW1B3oA8yjROcoIu4F3qhY3NA5GQVcEcmDQH9JNe0SaDPUV6eIuCMiFufZB4F18/Qo4OqIWBgRs4F/kf4mtgoncmsv6wAvFOZfzMtKS9JAYCvgIWCtiJiXV70MrNVRcbXAucAPgA/y/MeBfxf+IJXpXH0SeBW4LA8V/EHSKpT4/ETEXOBXwPOkBL4AmEx5z1Gdhs5JV/lb8Q3g//J0m9bJidysBST1Ba4HvhsR/ymui/SdzlJ8r1PSSGB+REzu6FhaSXdga+D3EbEV8A4V3ehlOj8Aeex4FOkiZW1gFZbt0i21sp2Tpkj6EWkY7sr2KM+J3NrLXGC9wvy6eVnpSOpBSuJXRsQNefErdd1/+X1+R8XXTJ8D9pU0hzTcsStpjLl/7saFcp2rF4EXI+KhPH8dKbGX9fwAjABmR8SrEfFf4AbSeSvrOarT0Dkp9d8KSYcDI4FDYukPtbRpnZzIrb08AgzKd9r2JN34cXMHx9Rsefz4EuCJiPhNYdXNwOg8PRq4qb1ja4mIOCUi1o2IgaRzcndEHAL8Azggb1am+rwMvCDpM3nRF4DHKen5yZ4HtpfUJ//7q6tTKc9RQUPn5GbgsHz3+vbAgkIXfKcmaU/SMNW+EfFuYdXNwFcl9ZL0SdKNfA+3Wrn+ZTdrL5L2Jo3HdgMujYgzOzai5pO0EzAJmMHSMeUfksbJrwXWB54DvhIRlTf3dGqShgMnRcRISZ8itdBXBx4FDo2IhR0YXtUkDSbduNcTeBY4gtRoKe35kfRT4CBSd+2jwDdJY6ylOEeSrgKGkx7t+QpwGvBX6jkn+WJlHGn44F3giIio7YCwG9VAnU4BegGv580ejIhj8vY/Io2bLyYNyf1f5TFbHIsTuZmZWXm5a93MzKzEnMjNzMxKzInczMysxJzIzczMSsyJ3MzMrMScyM3MzErMidzMzKzE/j+l63eTDT3uewAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["print(df_lekki[\"house_type\"].value_counts())\n","(\n","    (df_lekki.groupby(\"house_type\")[\"price\"].mean()/1e6)\n","    .sort_values(ascending=False).\n","    plot(kind=\"barh\",\n","         xlabel = \"House Type\",\n","         ylabel = \"Prices [₦1M]\",\n","         title = \"Average Price by House Type in Lekki\"\n","        )\n",");"]},{"cell_type":"code","execution_count":21,"id":"4ca55ee2","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:22.656823Z","iopub.status.busy":"2023-03-30T08:48:22.655864Z","iopub.status.idle":"2023-03-30T08:48:22.6676Z","shell.execute_reply":"2023-03-30T08:48:22.666589Z"},"papermill":{"duration":0.034792,"end_time":"2023-03-30T08:48:22.670407","exception":false,"start_time":"2023-03-30T08:48:22.635615","status":"completed"},"tags":[]},"outputs":[],"source":["df_lekki[\"total_rooms\"] = df[\"bedrooms\"] + df[\"bathrooms\"] + df[\"toilets\"] + df[\"parking_space\"]\n","# Swap the positions of the price and total_rooms columns\n","cols = list(df_lekki.columns)\n","cols[-1], cols[-2] = cols[-2], cols[-1]\n","df_lekki = df_lekki[cols]"]},{"cell_type":"code","execution_count":22,"id":"4629d3ba","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:22.711454Z","iopub.status.busy":"2023-03-30T08:48:22.710941Z","iopub.status.idle":"2023-03-30T08:48:22.737505Z","shell.execute_reply":"2023-03-30T08:48:22.736137Z"},"papermill":{"duration":0.051379,"end_time":"2023-03-30T08:48:22.740505","exception":false,"start_time":"2023-03-30T08:48:22.689126","status":"completed"},"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>bedrooms</th>\n","      <th>bathrooms</th>\n","      <th>toilets</th>\n","      <th>parking_space</th>\n","      <th>house_type</th>\n","      <th>town</th>\n","      <th>total_rooms</th>\n","      <th>price</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>20.0</td>\n","      <td>120000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>2.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>18.0</td>\n","      <td>75000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>18.0</td>\n","      <td>65000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1.0</td>\n","      <td>1.0</td>\n","      <td>1.0</td>\n","      <td>1.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>19.0</td>\n","      <td>200000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>6.0</td>\n","      <td>3.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>15.0</td>\n","      <td>65000000.0</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","    </tr>\n","    <tr>\n","      <th>9129</th>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>3.0</td>\n","      <td>Terraced Duplexes</td>\n","      <td>Lekki</td>\n","      <td>26.0</td>\n","      <td>75000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>9130</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Semi Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>9.0</td>\n","      <td>110000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>9131</th>\n","      <td>3.0</td>\n","      <td>4.0</td>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>17.0</td>\n","      <td>80000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>9132</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>21.0</td>\n","      <td>68000000.0</td>\n","    </tr>\n","    <tr>\n","      <th>9133</th>\n","      <td>4.0</td>\n","      <td>5.0</td>\n","      <td>5.0</td>\n","      <td>4.0</td>\n","      <td>Detached Duplex</td>\n","      <td>Lekki</td>\n","      <td>13.0</td>\n","      <td>65000000.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>9134 rows × 8 columns</p>\n","</div>"],"text/plain":["      bedrooms  bathrooms  toilets  parking_space            house_type  \\\n","0          4.0        5.0      5.0            4.0       Detached Duplex   \n","1          4.0        4.0      5.0            2.0  Semi Detached Duplex   \n","2          4.0        5.0      5.0            4.0       Detached Duplex   \n","3          1.0        1.0      1.0            1.0       Detached Duplex   \n","4          4.0        5.0      6.0            3.0  Semi Detached Duplex   \n","...        ...        ...      ...            ...                   ...   \n","9129       4.0        4.0      5.0            3.0     Terraced Duplexes   \n","9130       4.0        5.0      5.0            4.0  Semi Detached Duplex   \n","9131       3.0        4.0      4.0            5.0       Detached Duplex   \n","9132       4.0        5.0      5.0            4.0       Detached Duplex   \n","9133       4.0        5.0      5.0            4.0       Detached Duplex   \n","\n","       town  total_rooms        price  \n","0     Lekki         20.0  120000000.0  \n","1     Lekki         18.0   75000000.0  \n","2     Lekki         18.0   65000000.0  \n","3     Lekki         19.0  200000000.0  \n","4     Lekki         15.0   65000000.0  \n","...     ...          ...          ...  \n","9129  Lekki         26.0   75000000.0  \n","9130  Lekki          9.0  110000000.0  \n","9131  Lekki         17.0   80000000.0  \n","9132  Lekki         21.0   68000000.0  \n","9133  Lekki         13.0   65000000.0  \n","\n","[9134 rows x 8 columns]"]},"execution_count":22,"metadata":{},"output_type":"execute_result"}],"source":["df_lekki"]},{"cell_type":"markdown","id":"8a42c97b","metadata":{"papermill":{"duration":0.018137,"end_time":"2023-03-30T08:48:22.777446","exception":false,"start_time":"2023-03-30T08:48:22.759309","status":"completed"},"tags":[]},"source":["The new feature created had a very poor correlation with the target variable."]},{"cell_type":"code","execution_count":23,"id":"e17d674e","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:22.816985Z","iopub.status.busy":"2023-03-30T08:48:22.816512Z","iopub.status.idle":"2023-03-30T08:48:23.065313Z","shell.execute_reply":"2023-03-30T08:48:23.063935Z"},"papermill":{"duration":0.27203,"end_time":"2023-03-30T08:48:23.067966","exception":false,"start_time":"2023-03-30T08:48:22.795936","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["-0.0020368542501899875"]},"execution_count":23,"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"}],"source":["plt.scatter(\n","    x = df_lekki[\"price\"],\n","    y = df_lekki[\"total_rooms\"]\n",")\n","df_lekki[\"price\"].corr(df_lekki[\"total_rooms\"])"]},{"cell_type":"markdown","id":"2d0558a5","metadata":{"papermill":{"duration":0.020204,"end_time":"2023-03-30T08:48:23.109002","exception":false,"start_time":"2023-03-30T08:48:23.088798","status":"completed"},"tags":[]},"source":["### **Checking for Multi-Collinearity**"]},{"cell_type":"code","execution_count":24,"id":"f698886a","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:23.152159Z","iopub.status.busy":"2023-03-30T08:48:23.151672Z","iopub.status.idle":"2023-03-30T08:48:23.480866Z","shell.execute_reply":"2023-03-30T08:48:23.47936Z"},"papermill":{"duration":0.355237,"end_time":"2023-03-30T08:48:23.483632","exception":false,"start_time":"2023-03-30T08:48:23.128395","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["               bedrooms  bathrooms   toilets  parking_space  total_rooms  \\\n","bedrooms       1.000000   0.750079  0.768076       0.315122     0.010758   \n","bathrooms      0.750079   1.000000  0.762202       0.306990    -0.006481   \n","toilets        0.768076   0.762202  1.000000       0.299910     0.011514   \n","parking_space  0.315122   0.306990  0.299910       1.000000     0.007555   \n","total_rooms    0.010758  -0.006481  0.011514       0.007555     1.000000   \n","price          0.525320   0.405033  0.411606       0.274123    -0.002037   \n","\n","                  price  \n","bedrooms       0.525320  \n","bathrooms      0.405033  \n","toilets        0.411606  \n","parking_space  0.274123  \n","total_rooms   -0.002037  \n","price          1.000000  \n"]},{"data":{"text/plain":["<AxesSubplot:>"]},"execution_count":24,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAZsAAAE6CAYAAADA2P+zAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAAoyklEQVR4nO3deZwdVZ338c83HTDsoOAMEEMAEYEAMYRtREFEBTdcgqyDKI8ZZdGBQR9mUIbFGVFnXEBBA0QQUREQJwoMIIjEKJgQQkICmQcjSpBlAIHIIunu3/NHnYabm9t3SW51Vd1837zq1VXn1j33102lf31OnTpHEYGZmVmeRhUdgJmZ9T4nGzMzy52TjZmZ5c7JxszMcudkY2ZmuXOyMTOz3DnZmJnZCiRNl/SYpHuGeV2SzpV0v6T5kia1qtPJxszM6l0CHNjk9YOA7dI2FbigVYVONmZmtoKIuA14sskpBwPfjcztwMaSNm9W5+huBmgvW/74kspNzbD84rOLDqFzY15RdAQdOeery4oOoWNfemRm0SF0bO6WOxcdQkd2/N21Wt06Ovmds/Zm2/4DWYtkyLSImNbBx20JPFhzvDSVPTzcG5xszMx6weBA26emxNJJclltTjZmZr0gBkfy0x4CXlNzPDaVDcv3bMzMesHgYPvb6psBHJ1Gpe0FPB0Rw3ahgVs2ZmY9IQb6u1aXpB8A+wGbSloK/CuwFkBEfAu4DngncD/wHPCRVnU62ZiZ9YIudqNFxOEtXg/g+E7qdLIxM+sFHQwQKIKTjZlZLxjZAQIdc7IxM+sF3bnxnxsnGzOzHhBu2ZiZWe66OBotD042Zma9wAMEzMwsd+5GMzOz3JV8gECh09VIGj/c4jx5vtfMrOfEYPtbAXquZSNpdESU+06ZmVm3lbxlU4ZkM1rS5cAkYCFwNLAD8BVgfeBx4JiIeFjSbsD09L4bhyqQdAzwgXR+n6T3p/O2IZu3Z2pEzJf0ymHKzwC2TuXjgJOAvchWo3sIeE9ELJd0DvBeoB+4MSJOyedHYmbWmRhcXnQITZVh1uftgfMjYgfgGbL5ds4DpkTEUHL5t3Tud4ATI2LXBvVMSu/ZFzgTuCsidgH+BfhuOme4coBtgf3Jksn3gF9ExM7A88C7JL0KeD+wU3r/57vy3ZuZdcPIzvrcsTIkmwcjYlba/x7wDmACcJOkecBngbGSNgY2TsuVAlxWV89NETG0jOk+Q69HxC3AqyRt2KQc4PqIWA4sAPqA/07lC4DxwNPAC8DFkj5A1jJagaSpkuZImnPRd3+wKj8LM7NV43s2LdUvZboMWBgRe9cWpmTTzLOrGcdfASJiUNLyNKspwCAwOiL6Je0BvBWYApxA1hJ6Se3qd1VcFtrMKqzkz9mUoWUzTtJQYjkCuB3YbKhM0lqSdoqIp4CnJO2Tzj2ySZ0zh16XtB/weEQ806S8JUnrAxtFxHVk93QadeWZmRXDLZuWFgPHS5oOLCK7X3MDcK6kjchi/BrZ4IGPANMlBTUDBBo4I503n6y768MtytuxAfBfksYAAk7u4L1mZvnydDXDi4gHgNc3eGke8OYG59/Jii2Kz6TyS4BLas57Enhfg/cPV35G3fH6w7y2R4NYzcyK56HPZmaWOycbMzPLW0S5Bwg42ZiZ9QK3bMzMLHee9dnMzHLn0WhmZpY7d6OZmVnu3I1mZma5c8vGzMxy52RjZma5czeamZnlzqPRzMwsd+5GMzOz3Lkbbc20/OKziw6hY2sd+7miQ+jY8u9+oegQOjKw0lqB5ddf8kW5Grnr+U2KDqEjO3ajErdszMwsd042ZmaWu4Fyt0CdbMzMekHJWzajig7AzMy6IAbb31qQdKCkxZLul3Rqg9fHSfqFpLskzZf0zlZ1OtmYmfWCwcH2tyYk9QHfBA4iG7twuKT6MQyfBX4UEW8ADgPObxWek42ZWS+IaH9rbg/g/ohYEhEvAj8EDq7/NGDDtL8R8KdWlfqejZlZL+jgno2kqcDUmqJpETEt7W8JPFjz2lJgz7oqzgBulHQisB5wQKvPdLIxM+sFHUxXkxLLtJYnDu9w4JKI+E9JewOXSZoQMfwNIScbM7MeEINde2D4IeA1NcdjU1mtY4EDASLiN5LGAJsCjw1Xqe/ZmJn1gi4NEABmA9tJ2lrS2mQDAGbUnfNH4K0AknYAxgD/26xSt2zMzHpBl+ZGi4h+SScANwB9wPSIWCjpLGBORMwA/gm4UNJJZIMFjoloPvLAycbMrBd0rxuNiLgOuK6u7PSa/UXAGzup08nGzKwX9Hs9GzMzy1vr52cKNaIDBCSNl3RPB+cfI2mLmuMHJG2aT3RmZhXWvQECuSj7aLRjgC1anVRLkltrZrbmGYz2twIUkWxGS7pc0r2SrpK0rqTTJc2WdI+kacpMASYDl0uaJ2md9P4TJc2VtEDS6wEknSHpMkmzyB4uGi/pljRB3M2SxqXzhiu/RNIFkm6XtETSfpKmpxgvSef0pfPuSZ990oj/5MzMhtPFiTjzUESy2R44PyJ2AJ4BjgO+ERG7R8QEYB3g3RFxFTAHODIiJkbE8+n9j0fEJOAC4JSaencEDoiIw4HzgEsjYhfgcuDcdM5w5QCbAHsDJ5GNKf8qsBOws6SJwERgy4iYEBE7A9/p2k/EzGx1uWWzkgcjYlba/x6wD/AWSXdIWgDsT/ZLfjg/Tl/vBMbXlM+oSUh7A99P+5elz2hWDvDTNE58AfBoRCxIUy8sTJ+zBNhG0nmSDiRLlCuQNFXSHElzpt+xuMm3YGbWXdE/0PZWhCKSTX1aDbLpqaekFsOFZE+jDuev6esAK46me3Y14xqqd7Bmf+h4dET8GdgVuBX4OHBRfQURMS0iJkfE5I/uuf1qhmNm1gF3o61kXJq4DeAI4Fdp/3FJ6wNTas5dBmywCp/xa7IpFgCOBGa2KG8pjYIbFRFXk63lMGkV4jIzy0fJu9GKGLm1GDhe0nRgEdm9l02Ae4BHyOblGXIJ8C1Jz5N1gbXrROA7kj5NNl/PR1qUt2PL9N6hBP3PHbzXzCxfJV8WekSTTUQ8ALy+wUufTVv9+VcDV9cUja95bQ6wX9o/o+59fyC791Nf33Dlx9TFOKHRa7g1Y2ZlVVCLpV1+JsXMrBcUdC+mXU42ZmY9oKhRZu1ysjEz6wXuRjMzs9w52ZiZWe58z8bMzHLnlo2ZmeUt+t2yMTOzvPmhTjMzy5270czMLHdONmZmlrdshZTycrIxM+sFbtmYmVnePBptTTXmFUVH0LHl3/1C0SF0bK2jq7XSQ/+5pxUdQsdGj+orOoSOjS55l1Iu3LIxM7Pclbth42RjZtYLwi0bMzPLnZONmZnlzt1oZmaWt+h3y8bMzHLmezZmZpY/d6OZmVneSr52mpONmVlPcLIxM7O8RX/RETQ3qugAzMxs9cVg+1srkg6UtFjS/ZJOHeacD0laJGmhpO+3qtMtGzOzHtCtezaS+oBvAm8DlgKzJc2IiEU152wH/DPwxoj4s6RXt6rXLRszsx7QxZbNHsD9EbEkIl4EfggcXHfOx4BvRsSfASLisVaV9kSykbSxpONanLOFpKvS/n6Sftbi/ImS3tnNOM3MchNqe5M0VdKcmm1qTU1bAg/WHC9NZbVeB7xO0ixJt0s6sFV4vdKNtjFwHHD+cCdExJ+AKR3UORGYDFy3OoGZmY2ETrrRImIaMG01Pm40sB2wHzAWuE3SzhHxVLM39IJzgG0lzQNuSmUHAQF8PiKukDQe+FlETKh9o6T1gPOACcBawBnA9cBZwDqS9gG+ADwCfD29LYA3R8SyHL8nM7O2DfarW1U9BLym5nhsKqu1FLgjIpYDv5f0P2TJZ/ZwlfZENxpwKvC7iJgI3E7WKtkVOAD4sqTNm7z3NOCWiNgDeAvwZbKkczpwRURMjIgrgFOA49NnvAl4Pp9vxcyscxFqe2thNrCdpK0lrQ0cBsyoO+cnZK0aJG1K1q22pFmlvZJsau0D/CAiBiLiUeCXwO5Nzn87cGpqFd0KjAHGNThvFvAVSZ8ENo5YeVR7bT/o9F8vWrkGM7OcdGuAQPrddgJwA3Av8KOIWCjpLEnvTafdADwhaRHwC+DTEfFEs3p7pRttdQj4YEQsXqFQ2rP2OCLOkXQt8E5glqR3RMR9dee81A/63Nc/Xu5Z8cysp8Rg17rRiIjrqLtfHRGn1+wHcHLa2tIrLZtlwAZpfyZwqKQ+SZsBbwZ+2+S9NwAnShKApDc0qBNJ20bEgoj4Ilkz8/Vd/h7MzFZZRPtbEXoi2aTm2yxJ9wB7A/OBu4FbgM9ExCNN3n422T2a+ZIWpmPImoY7Spon6VDgHyXdI2k+sJxsEIGZWSnEoNreitAz3WgRcURd0afrXn+AbMQZEXEr2f0ZIuJ54B8a1PckK97ruaJrwZqZddngQDFJpF09k2zMzNZkRbVY2uVkY2bWA9oY0lwoJxszsx7gxdPMzCx3g27ZmJlZ3gYHyj242MnGzKwHFPX8TLucbMzMeoBHo5mZWe58z8bMzHLnoc9mZpY737MxM7PcDQx6NJqZmeXMLRszM8udBwisoc756rKiQ+jYACX/06iB/nNPKzqEjnx+zr8VHULHvjZ236JD6NisV6y0kG6pHdqFOjxAwMzMcueWjZmZ5a7s/RJONmZmPcCj0czMLHclX2HAycbMrBcEvmdjZmY5Gyz5TRsnGzOzHjDolo2ZmeVtwMnGzMzy5ns2ZmaWO49GMzOz3DnZmJlZ7tyNZmZmuRssd64h9/kNJF0iaUqD8osk7Zj355uZrQkGUNtbEXJt2Ugatv6I+D95fraZ2Zqk7PdsWrZsJI2XdJ+kyyXdK+kqSetKOl3SbEn3SJomSen8WyV9TdIc4FN1dZ2dWjp96bzJqfwvkv5N0t2Sbpf0N6l823S8QNLnJf2lSZybS7pN0rwU05tq6v6qpIWSbpa0WSr/WIr/bklXS1o3lf+NpGtS+d2S/i6VHyXpt6n+b0vqW6WfuJlZDgaltrcitNuNtj1wfkTsADwDHAd8IyJ2j4gJwDrAu2vOXzsiJkfEfw4VSPoysBnwkYgYqKt/PeD2iNgVuA34WCr/OvD1iNgZWNoixiOAGyJiIrArMK+m7jkRsRPwS+BfU/mPU/y7AvcCx6byc4FfpvJJwEJJO5Ctb/TGVP8AcGSLeMzMRkx0sBWh3WTzYETMSvvfA/YB3iLpDkkLgP2BnWrOv6Lu/Z8DNoqIj0c0XCn7ReBnaf9OYHza3xu4Mu1/v0WMs4GPSDoD2DkihpbKHKyJZyh2gAmSZqb4j6yJf3/gAoCIGIiIp4G3ArsBsyXNS8fb1AcgaaqkOZLmzF12f4twzcy6Z7CDrRVJB0paLOl+Sac2Oe+DkmKol6qZdpNNfYII4HxgSmp1XAiMqXn92brzZwO7SXrlMPUvr0lCA6zCvaSIuA14M/AQcImko4c7NX29BDghxX8mK8ZfT8ClETExbdtHxBkNYpiWWnSTJ23w2k6/BTOzVdYvtb01k24RfBM4CNgROLzRYC5JG5DdKrmjnfjaTTbjJO2d9o8AfpX2H5e0PrDSaLM6/w2cA1ybAmzX7cAH0/5hzU6UtBXwaERcCFxE1gUG2fc4FF9t7BsAD0taixW7xG4GPpHq7JO0USqbIunVqfyV6fPMzEqhi91oewD3R8SSiHgR+CFwcIPzzga+CLzQTnztJpvFwPGS7gU2IetmuhC4B7iBrOXSVERcmd4zQ9I6bX7uPwInS5oPvBZ4usm5+wF3S7qL7P7K11P5s8Aeku4h6yI7K5V/jiwjzwLuq6nnU2RdhAvIuvR2jIhFwGeBG1MsNwGbt/k9mJnlblDtb7Vd/mmbWlPVlsCDNcdLU9lLJE0CXhMR17YbX7vdVf0RcVRd2WfTtoKI2K/u+Jia/enA9HS4X035+jX7VwFXpcOHgL0iIiQdRjZQoaGIuBS4dJjXTm5QdgHp3kxd+aM0yOIRcQUr34syMyuFToY+R8Q0YNqqfI6kUcBXgGM6eV/ZZxDYDfhGGlb9FPDRYsMxMyunLo4yewh4Tc3x2FQ2ZANgAnBreuLlb8l6rN4bEXOGq7RlsomIB1LFIy4iZpINY36JpJ2By+pO/WtE7DlMHes3Kjcz6yVdnK5mNrCdpK3JksxhZPe7AUgjdDcdOpZ0K3BKs0QD5W/ZrCQiFgATi47DzKxM+rtUT0T0SzqB7H58HzA9IhZKOovsmcUZq1Jv5ZKNmZmtLLo4MUBEXAdcV1d2+jDn7tdOnU42ZmY9oOxzoznZmJn1ACcbMzPLXVFznrXLycbMrAeUffE0Jxszsx7QrdFoeXGyMTPrAe5GMzOz3LkbzczMcufRaGZmljt3o62hvvTIzKJD6Fj/YP1q3eU3elRf0SF05Gtj9y06hI79Zekviw6hY+tu8aaiQ+jIuV2oo7/k6cbJxsysB5Q71TjZmJn1BN+zMTOz3Hk0mpmZ5W6w5B1pTjZmZj2g3KnGycbMrCd4NJqZmeWu3KnGycbMrCd4NJqZmeXOAwTMzCx35U41TjZmZj3B3WhmZpa7gZK3bZxszMx6gO/ZmJlZ7sqdamBUHpVK2ljScS3OGS/piDbqGi/pnu5FZ2bWewaJtrci5JJsgI2BpskGGA+0TDadkOSWmpmtkQY72IqQ1y/nc4BtJc0DbkplB5G19D4fEVekc3ZI51wKXANcBqyXzj8hIn7d6oMkHQN8AFgf6JP0fmA6sA3wHDA1IuZLeuUw5WcAW6fyccBJwF4p3oeA90TEcknnAO8F+oEbI+KUVfvRmJl135o6QOBUYEJETJT0QeDjwK7ApsBsSbelc06JiHcDSFoXeFtEvCBpO+AHwOQ2P28SsEtEPCnpPOCuiHifpP2B7wITgTOHKQfYFngLsCPwG+CDEfEZSdcA75I0E3g/8PqICEkbNwpC0lRgKsDo0ZvQ17d+m+Gbma2eKHmyyasbrdY+wA8iYiAiHgV+Ceze4Ly1gAslLQCuJPvF366bIuLJms+7DCAibgFeJWnDJuUA10fEcmAB0Af8dypfQNbd9zTwAnCxpA+QtYxWEhHTImJyREx2ojGzkVT2brSRSDbtOgl4lKwFNBlYu4P3Pruan/1XgIgYBJZHxNCfCIPA6IjoB/YArgLezcvJyMysFAYj2t6KkFeyWQZskPZnAodK6pO0GfBm4Ld15wBsBDycfuH/PVkLY1XMBI4EkLQf8HhEPNOkvCVJ6wMbRcR1ZElx11WMzcwsF9HBVoRc7tlExBOSZqUhy9cD84G7yb7Pz0TEI5KeAAYk3Q1cApwPXC3paLKWw6q2Vs4ApkuaT9bd9eEW5e3YAPgvSWMAASevYmxmZrko+0OdioKaVL1uzJhxlfvB9g8OFB1Cx0aPWtUGcDHKfhO3kb8s/WXRIXRs3S3eVHQIHVn+4kNa3ToO3ep9bV9cV/zhJ6v9eZ3ycylmZj2g7C2bMg0QaErSOyTNq9uuKTouM7MyiA7+a0XSgZIWS7pf0qkNXj9Z0iJJ8yXdLGmrVnVWpmUTETcANxQdh5lZGXVrSLOkPuCbwNuApWTPRs6IiEU1p90FTI6I5yR9AvgScGizeivTsjEzs+FFRNtbC3sA90fEkoh4EfghcHDdZ/0iIoaeN7wdGNuqUicbM7Me0MlEnJKmSppTs02tqWpL4MGa46WpbDjHko06bqoy3WhmZja8TuZGi4hpwLTV/UxJR5E9hL9vq3OdbMzMekAXR6M9BLym5nhsKluBpAOA04B9I+KvrSp1sjEz6wFdfGZyNrCdpK3Jksxh1C0HI+kNwLeBAyPisXYqdbIxM+sB3RqNFhH9kk4gG/3bB0yPiIWSzgLmRMQM4Mtky7pcKQngjxHx3mb1OtmYmfWAbs5OkeaBvK6u7PSa/QM6rdPJxsysBwxEUYsHtMfJxsysB5R9uhonm5zM3XLnokPo2F3Pb1J0CB0bXbGJZGe9or/oEDpWtUktAZ7708yiQxhxZZ/k1cnGzKwHFLUoWrucbMzMekC5U42TjZlZT/A9GzMzy51Ho5mZWe7csjEzs9x5NJqZmeWui3Oj5cLJxsysB7gbzczMcucBAmZmljvfszEzs9x5BgEzM8udWzZmZpY7t2zMzCx3ZW/ZjCo6gDKQdJakjleeMzMri4EYbHsrwhrfspHUV7vcqZlZFZW9G62nWzaSxku6T9Llku6VdJWkdSU9IOmLkuYCh0i6RNKU9J7dJf1a0t2SfitpA0l9kr4sabak+ZL+oeBvzcxsBdHBf0VYE1o22wPHRsQsSdOB41L5ExExCUDSgenr2sAVwKERMVvShsDzwLHA0xGxu6RXALMk3RgRvx/x78bMrIEo+UOdPd2ySR6MiFlp/3vAPmn/igbnbg88HBGzASLimYjoB94OHC1pHnAH8Cpgu/o3S5oqaY6kOT965o9d/jbMzIY3SLS9FWFNaNnU/2SHjp/toA4BJ0bEDU0/KGIaMA1g0bbvKncHqpn1lLJPxLkmtGzGSdo77R8B/KrJuYuBzSXtDpDu14wGbgA+IWmtVP46SevlGbSZWSfKPhptTUg2i4HjJd0LbAJcMNyJEfEicChwnqS7gZuAMcBFwCJgrqR7gG+zZrQKzawiBiPa3oqwJvzC7I+Io+rKxtceRMQxNfuzgb0a1PMvaTMzK52yP9S5JiQbM7OeV/Z7Nj2dbCLiAWBC0XGYmeXNi6eZmVnuBgbL/ZyNk42ZWQ9wN5qZmeXO3WhmZpY7t2zMzCx3ZZ/12cnGzKwHlP05mzVhBgEzs543MDjY9taKpAMlLZZ0v6RTG7z+CklXpNfvkDS+VZ1ONmZmPaBb69lI6gO+CRwE7AgcLmnHutOOBf4cEa8Fvgp8sVV8TjZmZj0gItreWtgDuD8ilqT5In8IHFx3zsHApWn/KuCtktSsUicbM7Me0EmyqV17K21Ta6raEniw5nhpKqPROWnNr6fJ1vkalgcImJn1gE6GB9SuvTVSnGxysuPvrm3apFwdkqami6Wr6jtluyWvePOUV8yHdrvCGnnFfG63K0x8XXRX/4sPdet3zkPAa2qOx6ayRucsTWt+bQQ80axSd6NV09TWp5RK1eIFxzwSqhYvVDPmTs0GtpO0taS1gcOAGXXnzAA+nPanALdEi5tBbtmYmdlLIqJf0glkKxT3AdMjYqGks4A5ETEDuBi4TNL9wJNkCakpJxszM1tBRFwHXFdXdnrN/gvAIZ3U6W60aipln3ETVYsXHPNIqFq8UM2YS0Fln7zNzMyqzy0bMzPLnZONmZnlzsnGzMxy52RjZma5c7KpCElfkrShpLUk3SzpfyUdVXRcw5H0qRSvJF0saa6ktxcd13AkrSdpVNp/naT3Slqr6LhaST/foySdno7HSdqj6LiGU7XreIikrSQdkPbXkbRB0TFVjZNNdbw9Ip4B3g08ALwW+HShETX30RTv24FNgL8Hzik2pKZuA8ZI2hK4kSzeSwqNqD3nA3sDh6fjZWTTw5dV1a5jJH2MbGbjb6eiscBPCguoopxsqmPoAdx3AVdGxNNFBtOGoXma3glcFhELa8rKSBHxHPAB4PyIOATYqeCY2rFnRBwPvAAQEX8G1i42pKaqdh0DHA+8EXgGICL+H/DqQiOqICeb6viZpPuA3YCbJW1G+gVTUndKupEs2dyQuh1aLxFYHEnaGzgSuDaV9RUYT7uWp8WuAiBdF2X+OVftOgb4a1rXBYA08aQfUOyQH+qsEEmvBJ6OiAFJ6wIbRsQjRcfVSLr/MRFYEhFPSXoVsGVEzC82ssYkvRk4BZgVEV+UtA3wjxHxyYJDa0rSkWSTSU8iW8xqCvDZiLiy0MCaqNJ1DNl9JuAp4GjgROA4YFFEnFZkXFXjZFMR6a/XdwHjqZnTLiK+UlRMrUjahZXj/XFhATUh6ZD6X9CNyspI0uuBt5J1U94cEfcWHNKwKnodjyJbBvntZD/jG4CLWs1ybCtysqkISdeRdTcsoKabJCLOLCyoJiRNB3YBFvJyvBERHy0uquFJmhsRk1qVlY2kvYCFEbEsHW8I7BARdxQbWWNVu44hG6kIvBARA+m4D3hFusdnbfKsz9UxNiJ2KTqIDuwVEXmtx9Y1kg4iu6+0paTadcI2BPqLiaojF5B1oQ35S4OyMqnadQxwM3AA2c8WYB2yEYt/V1hEFeQBAtVxfZmfU2ngN5JKn2yAPwFzyP7avrNmmwG8o8C42qXa7pyIGKTcf0RW7ToGGBMRQ4mGtL9ugfFUUpkvSlvR7cA1qf94OVnfcUTEhsWGNazvkiWcR4C/8nK8pfqrNiLuBu6W9H2yfw/jImJxwWF1YomkT5K1ZiC7eb2kwHhaqdp1DPCspEkRMRdA0m7A8wXHVDm+Z1MRkn4PHAwsqMKNybSC38ms3Df/h8KCakLSe4D/ANaOiK0lTQTOioj3FhtZc5JeDZwL7E82HPdmslF0jxUa2DCqdh0DSNod+CFZK1jA3wKHRsSdhQZWMU42FSHpNmC/1E1SepJ+ExF7Fx1HuyTdSfYL+9aIeEMqWxAROxcbWW+p2nU8JE1dtH06XBwRy4uMp4rcjVYdS4BbJV1P1i0FlHrI6F2pa+qnrBhvKYc+A8sj4mlphUkOSv+XmKQxZMNydwLGDJWXddQfFbqOJe0fEbdI+kDdS6+TVOZruZScbKrj92lbm3JPRzJkHbJfJrU3gwMo6z/QhZKOAPokbQd8Evh1wTG14zLgPrLBDGeRzYBQ2udsqNZ1vC9wC/CeBq+V+VouJXejVYyk9eGlETHWJelJ9tNY8cG9syOi1FOpSLorIt4gaX5E7JK6e2ZGxF5Fx9ZMVa7jNJBhSkT8qOhYqs5DnytC0gRJd5E9JLlQ0p2SSjtRpKSxkq6R9FjarpY0tui4hhMRz0XEaRGxe0RMTvulTjTJ0L2DpyRNADaixJNEVu06TveWPlN0HL3A3WjVMQ04OSJ+ASBpP+BCyvtg2XeA7wOHpOOjUtnbCouoAUk/pcm9mbKPRgOmSdoE+BzZs0Hrp/2yqtp1DPBzSacAVwDPDhVGxJPFhVQ97karCEl3R8SurcrKQtK8iJjYqqxokvZt9npE/HKkYlkTVO06hpeGa6/0izIitikgnMpyy6Y6lkj6HNkNYchaCmV+eO+JtALjD9Lx4cATBcbTUNWTSZpN+wyy9VYCmEl2r6l0P+ukatcxwI5kD8vuw8s/428VGlEFuWVTEamr5EyyCx6yC/6MtFhW6UjaCjiPbBVJgFnAJyPij8VFtTJJP4qID0lawIp/vZZyxoN6km4iW2X0e6noSLLnWA4oLqrhVe06huwaIVs47fJUdASwUUR8qLioqsfJpmLSImRR9lE8VSFp84h4OCXHlZR1xoMhku6JiAl1ZaV/GLVK17GkRfWTyjYqs+Y8Gq0iJO2cRvHcw8ujeCa0el9RqjIaLSIeTl//QDYZ585pe77siSa5UdJhkkal7UNkw7ZLqWrXcTI3LeUAgKQ9ySZvtQ64ZVMRkn4NnFY3iuffI6KUo3hS9873WbFv/siIKNVotCHpl/SXgVvJutDeBHw6Iq4qMq5WJC0D1gMGyOIexcsjpko3wWXVrmMASfeSTVUz1AU8DlhMtgRF6btay8LJpiKqNoqnKqPRhki6G3jb0ASWkjYDfl7Wn29VVe06hpfuPw6rIi3gwnk0WnVUbRRPJUaj1RhVN1PyE1Sgm1nSG4F5EfFs+nlPAr5WtoEYNap2HTuZdEnp/zHZSz4KbEY2H9PVwKaprKw+CnwIeAR4GJgCfKTQiJq7XtINko6RdAxwLXBdwTG14wLgOUm7Av8E/I6Xf5GXUdWuY+sSt2wqQNma5z+OiLcUHUs7Urz/XoGn72sF8G1eHpI7DSj1/GJJf0SEpIOBb0TExZKOLTqoRqp2HVt3uWVTARExAAxK2qjoWNqR4t1KUtln9a31toj4cUScnLZrgIOKDqoNyyT9M1l31LVp4si1Co6poapdx9ZdbtlUx1+ABWmUV+38TJ8sLqSmlgCzJM1gxXhLtW6JpE+QPR2+jaT5NS9tQPYgatkdSvaQ4bER8YikcWSj6sqqatexdYlHo1WEpA83Ko+IS0c6lnZI+tdG5RFx5kjH0kz6K3sT4AvAqTUvLeuFiRZVshVTq3YdW/c42Zj1sKH1boqOo12Sro6IDxYdh3Wfu9FKrsGcXSso6wNlkl4HnAKMp+Y6i4j9i4ppDVW1vyY9k3KPcrIpv3enr8enr7XPJ5T5F8mVZDPjXkT2dLtZO8p8TdtqcDdaRTTqDpE0NyImFRVTM5LujIjdio5jTVfBbrTSXtO2ejz0uTqUnhYfOvg7Svj/T9IrJb0S+Kmk4yRtPlSWym1k/X3RAXRIRQdg+XDLpiIk7QZMJ1tjHuAp4KMRMbewoBqoWdWw0S+N8OqG3ZUm4qz/R/w02azE/xQRpZ4Kpp6kt0fEjUXHYd3nZFMxQw/ERcTTRcfSjKQxEfFCqzJbPZLOBpaSzbAt4DBgW2Au8ImI2K+46F7WZKBLJRaps9XnZFMRkv4G+Hdgi4g4SNKOwN4RcXHBoTXUqO/d/fHdN8wsyvMiYmKZZlP2zMnm0WjVcQnwHeC0dPw/wBVAqZKNpL8FtgTWkfQGXu5O2xBYt7DAetdzaS2eoXV3ppAtAgclGtnlZGJONtWxaUT8KM2DRUT0SyrjkOJ3AMcAY4HaqWmWAf9SREA97kjg68D5ZMnlduAoSesAJxQZWCNpxcvzgB2AtYE+4NmyLfJm3edkUx3PSnoV6a/V9I+2dPdt0rQjl0r6YERcXXQ8vS4NAHjPMC//aiRjadM3yO4rXQlMBo4GXldoRDYifM+mIiRNIvuLcCdgIdmaIFMiYn7TNxZI0rvI4h0zVBYRZxUXUe9JK4p+jJVnaijlGjGS5kTEZEnzhwYFVO1ZIFs1btlUxyLgGuA5si6pn5DdtyklSd8iu0fzFrJZBKYAvy00qN70X8BM4OdUY6aG59LSE/MkfYlsYb3SPS9m3eeWTUVI+hHwDHB5KjoC2DgiDikuquEN/eVa83V94PqIeFPRsfWSoZFnRcfRrjQq7VGy+zUnkT039s2I+F2hgVnu3LKpjgkRsWPN8S8kLSosmtaeT1+fk7QF8ASweYHx9KqfSXpnRFRhCWuA90XE18lGzJ0JIOlTZIMcrIe5+Vodc9OgAAAk7Un2lHhZ/UzSxsCXgDuBB4AfFBlQj/oU2c/6eUnPSFom6Zmig2qi0Xo2x4x0EDby3I1WcjVPXq8FbA/8MR1vBdxX19opjTT09hPAm8jinQlc4BkE1kySDifr+t2H7FoYsiEwEBFvLSQwGzFONiVX1Sev0z2mZcD3UtERwEYR8aHiouodkl4fEfelUYorKeGceVsBW9NgRVRgfkT0FxKYjRgnG8uFpEX1ra5GZbZqJE2LiKmSftHg5SjzInVp6qXd0+FvI+KxIuOxkeEBApaXuZL2iojboRL3mColIqam3bdGxGDta5LGNHhLKUg6BPgP4FayqYzOk/TpiLiq6Rut8tyysa6q6j2mqpI0vfYBTknrATPKeg9E0t3A24ZaM+mh1J+XZcJQy49bNtZt7259inXRQ5LOj4jjJG0CXAtcWHRQTYyq6zZ7Ao+KXSO4ZWNWcelJ/A2B3YBzyjwnXYp1V14eBn8o2QCB/1tcVDYS/BeFWQVJ+sDQBtwB7AXcBUQqK6sAvg3skrZpxYZjI8UtG7MKkvSdJi9HiSfibLSo3kuTclrvcrIxqyhJfcAnI+KrRcfSiqRPAMcB2wC186BtAMyKiKMKCcxGjJONWYVJ+m1E7FF0HK1I2gjYhAYPdUbEk8VEZSPJycaswiR9lWyY+RXAs0PlZZtBwMzJxqzCqjiDgK2ZnGzMzCx3fqjTrOK8/LZVgZ+zMauwtPz2ocCJZHONHUI2NZBZqbgbzazCvPy2VYVbNmbVVr/89nK8/LaVkO/ZmFVb/fLbABcVF45ZY+5GM6swL79tVeFkY1ZhXn7bqsLJxqzCvPy2VYUHCJhV21xJew0dePltKyu3bMwqTNK9vLz8NsA4YDHQTzZtjafut1JwsjGrMElNH+CMiD+MVCxmzTjZmJlZ7nzPxszMcudkY2ZmuXOyMTOz3DnZmJlZ7v4/lv6cKvxphbEAAAAASUVORK5CYII=\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["corr = df_lekki.corr()\n","print(corr)\n","sns.heatmap(corr)"]},{"cell_type":"code","execution_count":25,"id":"c088c65d","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:23.525516Z","iopub.status.busy":"2023-03-30T08:48:23.524976Z","iopub.status.idle":"2023-03-30T08:48:23.532667Z","shell.execute_reply":"2023-03-30T08:48:23.531416Z"},"papermill":{"duration":0.03189,"end_time":"2023-03-30T08:48:23.535319","exception":false,"start_time":"2023-03-30T08:48:23.503429","status":"completed"},"tags":[]},"outputs":[],"source":["# Drop multi-collinearity and low-cardinality features and feature not correlating with target\n","df_lekki.drop(columns=[\"bathrooms\", \"toilets\", \"town\", \"total_rooms\"], inplace=True)"]},{"cell_type":"markdown","id":"6414cd9d","metadata":{"papermill":{"duration":0.019748,"end_time":"2023-03-30T08:48:23.575063","exception":false,"start_time":"2023-03-30T08:48:23.555315","status":"completed"},"tags":[]},"source":["### **Removing Outliers**"]},{"cell_type":"code","execution_count":26,"id":"70056568","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:23.618274Z","iopub.status.busy":"2023-03-30T08:48:23.617711Z","iopub.status.idle":"2023-03-30T08:48:23.629307Z","shell.execute_reply":"2023-03-30T08:48:23.627625Z"},"papermill":{"duration":0.038207,"end_time":"2023-03-30T08:48:23.632766","exception":false,"start_time":"2023-03-30T08:48:23.594559","status":"completed"},"tags":[]},"outputs":[],"source":["trim = q1, q9 = df_lekki[\"price\"].quantile([0.1,0.9])\n","mask = df_lekki[\"price\"].between(q1,q9)\n","trimmed_df_lekki = df_lekki[mask]"]},{"cell_type":"code","execution_count":27,"id":"79effc63","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:23.67456Z","iopub.status.busy":"2023-03-30T08:48:23.673789Z","iopub.status.idle":"2023-03-30T08:48:23.684696Z","shell.execute_reply":"2023-03-30T08:48:23.68339Z"},"papermill":{"duration":0.034698,"end_time":"2023-03-30T08:48:23.687245","exception":false,"start_time":"2023-03-30T08:48:23.652547","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["7397    55000000.0\n","6960    55000000.0\n","644     55000000.0\n","6936    55000000.0\n","3619    55000000.0\n","Name: price, dtype: float64"]},"execution_count":27,"metadata":{},"output_type":"execute_result"}],"source":["trimmed_df_lekki[\"price\"].sort_values().head()"]},{"cell_type":"code","execution_count":28,"id":"a1f47fbe","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:23.729338Z","iopub.status.busy":"2023-03-30T08:48:23.728575Z","iopub.status.idle":"2023-03-30T08:48:23.745628Z","shell.execute_reply":"2023-03-30T08:48:23.743713Z"},"papermill":{"duration":0.041677,"end_time":"2023-03-30T08:48:23.748592","exception":false,"start_time":"2023-03-30T08:48:23.706915","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["   bedrooms  parking_space            house_type        price\n","0       4.0            4.0       Detached Duplex  120000000.0\n","1       4.0            2.0  Semi Detached Duplex   75000000.0\n","2       4.0            4.0       Detached Duplex   65000000.0\n","4       4.0            3.0  Semi Detached Duplex   65000000.0\n","5       4.0            4.0  Semi Detached Duplex   70000000.0\n","7526\n"]},{"data":{"text/plain":["bedrooms                       8.0\n","parking_space                  9.0\n","house_type       Terraced Duplexes\n","price                  170000000.0\n","dtype: object"]},"execution_count":28,"metadata":{},"output_type":"execute_result"}],"source":["print(trimmed_df_lekki.head())\n","print(len(trimmed_df_lekki))\n","trimmed_df_lekki.max()"]},{"cell_type":"markdown","id":"5cb7cb0c","metadata":{"papermill":{"duration":0.019642,"end_time":"2023-03-30T08:48:23.788222","exception":false,"start_time":"2023-03-30T08:48:23.76858","status":"completed"},"tags":[]},"source":["# **Split Data**"]},{"cell_type":"code","execution_count":29,"id":"81b6b964","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:23.831518Z","iopub.status.busy":"2023-03-30T08:48:23.831046Z","iopub.status.idle":"2023-03-30T08:48:23.846204Z","shell.execute_reply":"2023-03-30T08:48:23.845205Z"},"papermill":{"duration":0.040791,"end_time":"2023-03-30T08:48:23.850051","exception":false,"start_time":"2023-03-30T08:48:23.80926","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["      bedrooms  parking_space            house_type\n","0          4.0            4.0       Detached Duplex\n","1          4.0            2.0  Semi Detached Duplex\n","2          4.0            4.0       Detached Duplex\n","4          4.0            3.0  Semi Detached Duplex\n","5          4.0            4.0  Semi Detached Duplex\n","...        ...            ...                   ...\n","9129       4.0            3.0     Terraced Duplexes\n","9130       4.0            4.0  Semi Detached Duplex\n","9131       3.0            5.0       Detached Duplex\n","9132       4.0            4.0       Detached Duplex\n","9133       4.0            4.0       Detached Duplex\n","\n","[7526 rows x 3 columns]\n","0       120000000.0\n","1        75000000.0\n","2        65000000.0\n","4        65000000.0\n","5        70000000.0\n","           ...     \n","9129     75000000.0\n","9130    110000000.0\n","9131     80000000.0\n","9132     68000000.0\n","9133     65000000.0\n","Name: price, Length: 7526, dtype: float64\n"]}],"source":["target =  \"price\"\n","features = (trimmed_df_lekki.drop(columns = target)).columns\n","y = trimmed_df_lekki[target]\n","X = trimmed_df_lekki[features]\n","print(X)\n","print(y)"]},{"cell_type":"markdown","id":"f63ed251","metadata":{"papermill":{"duration":0.019886,"end_time":"2023-03-30T08:48:23.891521","exception":false,"start_time":"2023-03-30T08:48:23.871635","status":"completed"},"tags":[]},"source":["## **Train-Test-Split**"]},{"cell_type":"code","execution_count":30,"id":"aa87787e","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:23.935462Z","iopub.status.busy":"2023-03-30T08:48:23.934672Z","iopub.status.idle":"2023-03-30T08:48:23.9431Z","shell.execute_reply":"2023-03-30T08:48:23.94163Z"},"papermill":{"duration":0.034297,"end_time":"2023-03-30T08:48:23.946492","exception":false,"start_time":"2023-03-30T08:48:23.912195","status":"completed"},"tags":[]},"outputs":[],"source":["X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 42)"]},{"cell_type":"markdown","id":"38cc3e71","metadata":{"papermill":{"duration":0.020006,"end_time":"2023-03-30T08:48:23.988475","exception":false,"start_time":"2023-03-30T08:48:23.968469","status":"completed"},"tags":[]},"source":["### Train-Test-Split (Validation)"]},{"cell_type":"code","execution_count":31,"id":"ebbaa9de","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:24.030903Z","iopub.status.busy":"2023-03-30T08:48:24.030414Z","iopub.status.idle":"2023-03-30T08:48:24.037871Z","shell.execute_reply":"2023-03-30T08:48:24.03585Z"},"papermill":{"duration":0.03171,"end_time":"2023-03-30T08:48:24.040419","exception":false,"start_time":"2023-03-30T08:48:24.008709","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["1506\n","1505\n"]}],"source":["print(len(X_test))\n","print(round(len(X)*0.2))\n"]},{"cell_type":"markdown","id":"4e154d19","metadata":{"papermill":{"duration":0.020328,"end_time":"2023-03-30T08:48:24.082197","exception":false,"start_time":"2023-03-30T08:48:24.061869","status":"completed"},"tags":[]},"source":["# **Build Model**"]},{"cell_type":"markdown","id":"476050c2","metadata":{"papermill":{"duration":0.019898,"end_time":"2023-03-30T08:48:24.123777","exception":false,"start_time":"2023-03-30T08:48:24.103879","status":"completed"},"tags":[]},"source":["### **Model Baseline**\n"]},{"cell_type":"code","execution_count":32,"id":"e94d43ca","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:24.167633Z","iopub.status.busy":"2023-03-30T08:48:24.16636Z","iopub.status.idle":"2023-03-30T08:48:24.17668Z","shell.execute_reply":"2023-03-30T08:48:24.175183Z"},"papermill":{"duration":0.035457,"end_time":"2023-03-30T08:48:24.179544","exception":false,"start_time":"2023-03-30T08:48:24.144087","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Mean price: 101915054.8179402\n","Baseline MAE: 28144187.62008587\n"]}],"source":["y_mean = y_train.mean()\n","y_pred_baseline = [y_mean]*len(y_train)\n","print(\"Mean price:\", y_mean)\n","print(\"Baseline MAE:\", mean_absolute_error(y_train, y_pred_baseline))"]},{"cell_type":"markdown","id":"381ee068","metadata":{"papermill":{"duration":0.020406,"end_time":"2023-03-30T08:48:24.221438","exception":false,"start_time":"2023-03-30T08:48:24.201032","status":"completed"},"tags":[]},"source":["## **Model**"]},{"cell_type":"code","execution_count":33,"id":"e6a2b538","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:24.265229Z","iopub.status.busy":"2023-03-30T08:48:24.264733Z","iopub.status.idle":"2023-03-30T08:48:24.342887Z","shell.execute_reply":"2023-03-30T08:48:24.340274Z"},"papermill":{"duration":0.107291,"end_time":"2023-03-30T08:48:24.349871","exception":false,"start_time":"2023-03-30T08:48:24.24258","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Pipeline(steps=[('onehotencoder',\n","                 OneHotEncoder(cols=['house_type'], use_cat_names=True)),\n","                ('ridge', Ridge())])"]},"execution_count":33,"metadata":{},"output_type":"execute_result"}],"source":["model = make_pipeline(OneHotEncoder(use_cat_names=True),Ridge())\n","model.fit(X_train, y_train)"]},{"cell_type":"code","execution_count":34,"id":"c8274e19","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:24.440745Z","iopub.status.busy":"2023-03-30T08:48:24.439823Z","iopub.status.idle":"2023-03-30T08:48:24.463928Z","shell.execute_reply":"2023-03-30T08:48:24.461706Z"},"papermill":{"duration":0.068402,"end_time":"2023-03-30T08:48:24.471214","exception":false,"start_time":"2023-03-30T08:48:24.402812","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Training MAE: 21817560.71552872\n"]}],"source":["y_pred_training = model.predict(X_train)\n","print(\"Training MAE:\", mean_absolute_error(y_pred_training, y_train))"]},{"cell_type":"code","execution_count":35,"id":"7796a1ed","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:24.57897Z","iopub.status.busy":"2023-03-30T08:48:24.578453Z","iopub.status.idle":"2023-03-30T08:48:25.071461Z","shell.execute_reply":"2023-03-30T08:48:25.069973Z"},"papermill":{"duration":0.549403,"end_time":"2023-03-30T08:48:25.074475","exception":false,"start_time":"2023-03-30T08:48:24.525072","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<AxesSubplot:>"]},"execution_count":35,"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"}],"source":["prediction_data = model.predict(X_test)\n","model_result = pd.DataFrame({'test_price': y_test, \"prediction_price\": prediction_data})\n","model_result.tail(20).plot(kind=\"bar\")"]},{"cell_type":"code","execution_count":36,"id":"f0cc1c7a","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:25.119356Z","iopub.status.busy":"2023-03-30T08:48:25.118835Z","iopub.status.idle":"2023-03-30T08:48:25.12705Z","shell.execute_reply":"2023-03-30T08:48:25.125281Z"},"papermill":{"duration":0.034924,"end_time":"2023-03-30T08:48:25.130823","exception":false,"start_time":"2023-03-30T08:48:25.095899","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Test MAE: 21140344.333580773\n"]}],"source":["print(\"Test MAE:\", mean_absolute_error(prediction_data, y_test))"]},{"cell_type":"code","execution_count":37,"id":"c4ab7815","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:25.176264Z","iopub.status.busy":"2023-03-30T08:48:25.175785Z","iopub.status.idle":"2023-03-30T08:48:25.184942Z","shell.execute_reply":"2023-03-30T08:48:25.183747Z"},"papermill":{"duration":0.034672,"end_time":"2023-03-30T08:48:25.187219","exception":false,"start_time":"2023-03-30T08:48:25.152547","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["bedrooms                     5.0\n","parking_space                6.0\n","house_type       Detached Duplex\n","price                140000000.0\n","Name: 5935, dtype: object"]},"execution_count":37,"metadata":{},"output_type":"execute_result"}],"source":["trimmed_df_lekki.iloc[4902]"]},{"cell_type":"markdown","id":"7577f02d","metadata":{"papermill":{"duration":0.020531,"end_time":"2023-03-30T08:48:25.228652","exception":false,"start_time":"2023-03-30T08:48:25.208121","status":"completed"},"tags":[]},"source":["# **Result Communication**"]},{"cell_type":"code","execution_count":38,"id":"236248e7","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:25.273068Z","iopub.status.busy":"2023-03-30T08:48:25.272424Z","iopub.status.idle":"2023-03-30T08:48:25.280513Z","shell.execute_reply":"2023-03-30T08:48:25.27942Z"},"papermill":{"duration":0.03359,"end_time":"2023-03-30T08:48:25.283175","exception":false,"start_time":"2023-03-30T08:48:25.249585","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["intercept: -9954261.556066543\n","coefficients len: 9\n","[ 22472085.53066787   2643343.40835888   2686222.10223658\n"," -12671873.2847402     559975.20924007]\n"]}],"source":["intercept = model.named_steps[\"ridge\"].intercept_\n","coefficients = model.named_steps[\"ridge\"].coef_\n","print(\"intercept:\", intercept)\n","print(\"coefficients len:\", len(coefficients))\n","print(coefficients[:5])  # First five coefficients"]},{"cell_type":"code","execution_count":39,"id":"66aa59bb","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:25.327573Z","iopub.status.busy":"2023-03-30T08:48:25.327067Z","iopub.status.idle":"2023-03-30T08:48:25.333901Z","shell.execute_reply":"2023-03-30T08:48:25.332477Z"},"papermill":{"duration":0.032563,"end_time":"2023-03-30T08:48:25.336773","exception":false,"start_time":"2023-03-30T08:48:25.30421","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["features len: 9\n","['bedrooms', 'parking_space', 'house_type_Detached Duplex', 'house_type_Semi Detached Duplex', 'house_type_Terraced Duplexes', 'house_type_Detached Bungalow', 'house_type_Block of Flats', 'house_type_Terraced Bungalow', 'house_type_Semi Detached Bungalow']\n"]}],"source":["feature_names = model.named_steps[\"onehotencoder\"].get_feature_names()\n","print(\"features len:\", len(feature_names))\n","print(feature_names)"]},{"cell_type":"code","execution_count":40,"id":"b0b48aa4","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:25.382822Z","iopub.status.busy":"2023-03-30T08:48:25.382333Z","iopub.status.idle":"2023-03-30T08:48:25.39286Z","shell.execute_reply":"2023-03-30T08:48:25.39137Z"},"papermill":{"duration":0.036317,"end_time":"2023-03-30T08:48:25.395673","exception":false,"start_time":"2023-03-30T08:48:25.359356","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["bedrooms                             2.247209e+07\n","parking_space                        2.643343e+06\n","house_type_Detached Duplex           2.686222e+06\n","house_type_Semi Detached Duplex     -1.267187e+07\n","house_type_Terraced Duplexes         5.599752e+05\n","house_type_Detached Bungalow        -1.792535e+06\n","house_type_Block of Flats            2.074404e+07\n","house_type_Terraced Bungalow         8.472496e+06\n","house_type_Semi Detached Bungalow   -1.799832e+07\n","dtype: float64"]},"execution_count":40,"metadata":{},"output_type":"execute_result"}],"source":["feat_imp = pd.Series(coefficients, index=feature_names)\n","feat_imp"]},{"cell_type":"markdown","id":"3ebd17dd","metadata":{"papermill":{"duration":0.021463,"end_time":"2023-03-30T08:48:25.438787","exception":false,"start_time":"2023-03-30T08:48:25.417324","status":"completed"},"tags":[]},"source":["The barplot below shows that the number of bedrooms affect the price the most. Also notice that, if the house is a Semi Detached Bungalow, the price of the house depreciates by about 18 million naira."]},{"cell_type":"code","execution_count":41,"id":"c4dec53f","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:25.484496Z","iopub.status.busy":"2023-03-30T08:48:25.483985Z","iopub.status.idle":"2023-03-30T08:48:25.76345Z","shell.execute_reply":"2023-03-30T08:48:25.762087Z"},"papermill":{"duration":0.305617,"end_time":"2023-03-30T08:48:25.766439","exception":false,"start_time":"2023-03-30T08:48:25.460822","status":"completed"},"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"}],"source":["feat_imp.sort_values(key=abs).plot(kind=\"barh\")\n","plt.xlabel(\"Importance [₦10M]\")\n","plt.ylabel(\"Feature\")\n","plt.title(\"Importance [₦10M] vs Features\");"]},{"cell_type":"code","execution_count":42,"id":"00d206a0","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:25.813607Z","iopub.status.busy":"2023-03-30T08:48:25.813061Z","iopub.status.idle":"2023-03-30T08:48:25.819967Z","shell.execute_reply":"2023-03-30T08:48:25.818838Z"},"papermill":{"duration":0.033625,"end_time":"2023-03-30T08:48:25.822672","exception":false,"start_time":"2023-03-30T08:48:25.789047","status":"completed"},"tags":[]},"outputs":[],"source":["def make_prediction(bedrooms, parking_space, house_type):\n","    data = {\"bedrooms\":bedrooms,\n","            \"parking_space\":parking_space,\n","            \"house_type\":house_type\n","    }\n","    df = pd.DataFrame(data, index=[0])\n","    prediction = model.predict(df).round(2)[0]\n","    return f\"Predicted apartment price: ₦{prediction}\""]},{"cell_type":"markdown","id":"1f0ac268","metadata":{"papermill":{"duration":0.021351,"end_time":"2023-03-30T08:48:25.865909","exception":false,"start_time":"2023-03-30T08:48:25.844558","status":"completed"},"tags":[]},"source":["### **Testing the Function**"]},{"cell_type":"code","execution_count":43,"id":"c7b7a157","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:25.911462Z","iopub.status.busy":"2023-03-30T08:48:25.910534Z","iopub.status.idle":"2023-03-30T08:48:25.929705Z","shell.execute_reply":"2023-03-30T08:48:25.928744Z"},"papermill":{"duration":0.044722,"end_time":"2023-03-30T08:48:25.932323","exception":false,"start_time":"2023-03-30T08:48:25.887601","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["'Predicted apartment price: ₦105964805.01'"]},"execution_count":43,"metadata":{},"output_type":"execute_result"}],"source":["make_prediction(4, 2, \"Block of Flats\")"]},{"cell_type":"code","execution_count":44,"id":"48f53445","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:25.978952Z","iopub.status.busy":"2023-03-30T08:48:25.978116Z","iopub.status.idle":"2023-03-30T08:48:26.286417Z","shell.execute_reply":"2023-03-30T08:48:26.285406Z"},"papermill":{"duration":0.334723,"end_time":"2023-03-30T08:48:26.289232","exception":false,"start_time":"2023-03-30T08:48:25.954509","status":"completed"},"tags":[]},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"c22bbf5cd60442259b8e085816d1025e","version_major":2,"version_minor":0},"text/plain":["interactive(children=(IntSlider(value=4, description='bedrooms', max=8, min=1), IntSlider(value=3, description…"]},"metadata":{},"output_type":"display_data"}],"source":["interact(\n","    make_prediction,\n","    bedrooms=IntSlider(\n","        min=X_train[\"bedrooms\"].min(),\n","        max=X_train[\"bedrooms\"].max(),\n","        value=X_train[\"bedrooms\"].mean(),\n","    ),\n","    parking_space=IntSlider(\n","        min=X_train[\"parking_space\"].min(),\n","        max=X_train[\"parking_space\"].max(),\n","        step=1,\n","        value=X_train[\"parking_space\"].mean(),\n","    ),\n","    house_type=Dropdown(options=sorted(X_train[\"house_type\"].unique())),\n",");"]},{"cell_type":"markdown","id":"89888f53","metadata":{"papermill":{"duration":0.021617,"end_time":"2023-03-30T08:48:26.33322","exception":false,"start_time":"2023-03-30T08:48:26.311603","status":"completed"},"tags":[]},"source":["# **Conclusions**"]},{"cell_type":"markdown","id":"fe35717b","metadata":{"papermill":{"duration":0.023062,"end_time":"2023-03-30T08:48:26.378368","exception":false,"start_time":"2023-03-30T08:48:26.355306","status":"completed"},"tags":[]},"source":["* Excluding Banana Island in Lagos, Ikoyi has the most expensive houses in Nigeria, second to Maitama District in Abuja.\n","* The number of bedrooms in a house in Lekki is key in predicting the price of the house. Infact, one room should cost about 21 million naira on average. The number of rooms times 21 million naira will get you closer to the overall price of the house.\n","* Surprisingly, an apartment in a Block of Flats will cost about 17 million naira more than a Detached Duplex on average.\n","* If the house is a Semi-detached Bungalow, the price should depreciate by about 18 million naira. My hypothesis is that the style does not appeal to what the inhabitants of the town view as luxury.\n","* Some features are highly correlated. For example, the more the bedrooms, the more the bathrooms so the number of bathrooms is not needed for the model to predict the price of a house.\n","* The number of parking spaces in a house contributes to the overall price of the house with one parking space contributing about 3 million naira to the overall price of the house.\n"]},{"cell_type":"code","execution_count":45,"id":"5acef9b0","metadata":{"execution":{"iopub.execute_input":"2023-03-30T08:48:26.426273Z","iopub.status.busy":"2023-03-30T08:48:26.425746Z","iopub.status.idle":"2023-03-30T08:48:26.432729Z","shell.execute_reply":"2023-03-30T08:48:26.431161Z"},"papermill":{"duration":0.034908,"end_time":"2023-03-30T08:48:26.435682","exception":false,"start_time":"2023-03-30T08:48:26.400774","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Hope you found this useful\n"]}],"source":["print(\"Hope you found this useful\")"]}],"metadata":{"kernelspec":{"display_name":"Python 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