SARIMA_implementation_delhi.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "id": "Goq4mAMtgfVv"
   },
   "outputs": [],
   "source": [
    "import csv\n",
    "import numpy as np \n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime\n",
    "import warnings\n",
    "import seaborn as sns\n",
    "# from plotly.subplots import make_subplots\n",
    "# import plotly.graph_objects as go\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 406
    },
    "id": "GZs_jDjygfWH",
    "outputId": "dd0f4677-71ac-4533-ff53-812ee3715fd6"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\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>City</th>\n",
       "      <th>Date</th>\n",
       "      <th>PM2.5</th>\n",
       "      <th>PM10</th>\n",
       "      <th>NO</th>\n",
       "      <th>NO2</th>\n",
       "      <th>NOx</th>\n",
       "      <th>NH3</th>\n",
       "      <th>CO</th>\n",
       "      <th>SO2</th>\n",
       "      <th>O3</th>\n",
       "      <th>Benzene</th>\n",
       "      <th>Toluene</th>\n",
       "      <th>Xylene</th>\n",
       "      <th>AQI</th>\n",
       "      <th>AQI_Bucket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>0.92</td>\n",
       "      <td>18.22</td>\n",
       "      <td>17.15</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>0.92</td>\n",
       "      <td>27.64</td>\n",
       "      <td>133.36</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>0.97</td>\n",
       "      <td>15.69</td>\n",
       "      <td>16.46</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>0.97</td>\n",
       "      <td>24.55</td>\n",
       "      <td>34.06</td>\n",
       "      <td>3.68000</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>3.770000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>17.40</td>\n",
       "      <td>19.30</td>\n",
       "      <td>29.70</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>17.40</td>\n",
       "      <td>29.07</td>\n",
       "      <td>30.70</td>\n",
       "      <td>6.80000</td>\n",
       "      <td>16.400000</td>\n",
       "      <td>2.250000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>1.70</td>\n",
       "      <td>18.48</td>\n",
       "      <td>17.97</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>1.70</td>\n",
       "      <td>18.59</td>\n",
       "      <td>36.08</td>\n",
       "      <td>4.43000</td>\n",
       "      <td>10.140000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>22.10</td>\n",
       "      <td>21.42</td>\n",
       "      <td>37.76</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>22.10</td>\n",
       "      <td>39.33</td>\n",
       "      <td>39.31</td>\n",
       "      <td>7.01000</td>\n",
       "      <td>18.890000</td>\n",
       "      <td>2.780000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29526</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-06-27</td>\n",
       "      <td>15.020000</td>\n",
       "      <td>50.940000</td>\n",
       "      <td>7.68</td>\n",
       "      <td>25.06</td>\n",
       "      <td>19.54</td>\n",
       "      <td>12.470000</td>\n",
       "      <td>0.47</td>\n",
       "      <td>8.55</td>\n",
       "      <td>23.30</td>\n",
       "      <td>2.24000</td>\n",
       "      <td>12.070000</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29527</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-06-28</td>\n",
       "      <td>24.380000</td>\n",
       "      <td>74.090000</td>\n",
       "      <td>3.42</td>\n",
       "      <td>26.06</td>\n",
       "      <td>16.53</td>\n",
       "      <td>11.990000</td>\n",
       "      <td>0.52</td>\n",
       "      <td>12.72</td>\n",
       "      <td>30.14</td>\n",
       "      <td>0.74000</td>\n",
       "      <td>2.210000</td>\n",
       "      <td>0.380000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29528</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-06-29</td>\n",
       "      <td>22.910000</td>\n",
       "      <td>65.730000</td>\n",
       "      <td>3.45</td>\n",
       "      <td>29.53</td>\n",
       "      <td>18.33</td>\n",
       "      <td>10.710000</td>\n",
       "      <td>0.48</td>\n",
       "      <td>8.42</td>\n",
       "      <td>30.96</td>\n",
       "      <td>0.01000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29529</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>16.640000</td>\n",
       "      <td>49.970000</td>\n",
       "      <td>4.05</td>\n",
       "      <td>29.26</td>\n",
       "      <td>18.80</td>\n",
       "      <td>10.030000</td>\n",
       "      <td>0.52</td>\n",
       "      <td>9.84</td>\n",
       "      <td>28.30</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29530</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>0.40</td>\n",
       "      <td>26.85</td>\n",
       "      <td>14.05</td>\n",
       "      <td>5.200000</td>\n",
       "      <td>0.59</td>\n",
       "      <td>2.10</td>\n",
       "      <td>17.05</td>\n",
       "      <td>3.28084</td>\n",
       "      <td>8.700972</td>\n",
       "      <td>3.070128</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29531 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                City        Date      PM2.5        PM10     NO    NO2    NOx  \\\n",
       "0          Ahmedabad  2015-01-01  67.450578  118.127103   0.92  18.22  17.15   \n",
       "1          Ahmedabad  2015-01-02  67.450578  118.127103   0.97  15.69  16.46   \n",
       "2          Ahmedabad  2015-01-03  67.450578  118.127103  17.40  19.30  29.70   \n",
       "3          Ahmedabad  2015-01-04  67.450578  118.127103   1.70  18.48  17.97   \n",
       "4          Ahmedabad  2015-01-05  67.450578  118.127103  22.10  21.42  37.76   \n",
       "...              ...         ...        ...         ...    ...    ...    ...   \n",
       "29526  Visakhapatnam  2020-06-27  15.020000   50.940000   7.68  25.06  19.54   \n",
       "29527  Visakhapatnam  2020-06-28  24.380000   74.090000   3.42  26.06  16.53   \n",
       "29528  Visakhapatnam  2020-06-29  22.910000   65.730000   3.45  29.53  18.33   \n",
       "29529  Visakhapatnam  2020-06-30  16.640000   49.970000   4.05  29.26  18.80   \n",
       "29530  Visakhapatnam  2020-07-01  15.000000   66.000000   0.40  26.85  14.05   \n",
       "\n",
       "             NH3     CO    SO2      O3  Benzene    Toluene    Xylene  \\\n",
       "0      23.483476   0.92  27.64  133.36  0.00000   0.020000  0.000000   \n",
       "1      23.483476   0.97  24.55   34.06  3.68000   5.500000  3.770000   \n",
       "2      23.483476  17.40  29.07   30.70  6.80000  16.400000  2.250000   \n",
       "3      23.483476   1.70  18.59   36.08  4.43000  10.140000  1.000000   \n",
       "4      23.483476  22.10  39.33   39.31  7.01000  18.890000  2.780000   \n",
       "...          ...    ...    ...     ...      ...        ...       ...   \n",
       "29526  12.470000   0.47   8.55   23.30  2.24000  12.070000  0.730000   \n",
       "29527  11.990000   0.52  12.72   30.14  0.74000   2.210000  0.380000   \n",
       "29528  10.710000   0.48   8.42   30.96  0.01000   0.010000  0.000000   \n",
       "29529  10.030000   0.52   9.84   28.30  0.00000   0.000000  0.000000   \n",
       "29530   5.200000   0.59   2.10   17.05  3.28084   8.700972  3.070128   \n",
       "\n",
       "              AQI    AQI_Bucket  \n",
       "0      166.463581      Moderate  \n",
       "1      166.463581      Moderate  \n",
       "2      166.463581      Moderate  \n",
       "3      166.463581      Moderate  \n",
       "4      166.463581      Moderate  \n",
       "...           ...           ...  \n",
       "29526   41.000000          Good  \n",
       "29527   70.000000  Satisfactory  \n",
       "29528   68.000000  Satisfactory  \n",
       "29529   54.000000  Satisfactory  \n",
       "29530   50.000000          Good  \n",
       "\n",
       "[29531 rows x 16 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_day = pd.read_csv('city_day.csv')\n",
    "del city_day['Unnamed: 0']\n",
    "city_day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "i726IxbQgfWK",
    "outputId": "5e392821-6296-4383-e1c1-8e7cd1148180"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City          0\n",
       "Date          0\n",
       "PM2.5         0\n",
       "PM10          0\n",
       "NO            0\n",
       "NO2           0\n",
       "NOx           0\n",
       "NH3           0\n",
       "CO            0\n",
       "SO2           0\n",
       "O3            0\n",
       "Benzene       0\n",
       "Toluene       0\n",
       "Xylene        0\n",
       "AQI           0\n",
       "AQI_Bucket    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_day.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "id": "mL5dSwyfgfWK"
   },
   "outputs": [],
   "source": [
    "from sklearn.experimental import enable_iterative_imputer\n",
    "from sklearn.impute import IterativeImputer\n",
    "city_day = city_day.copy(deep=True)\n",
    "\n",
    "mice_imputer = IterativeImputer()\n",
    "city_day['PM2.5'] = mice_imputer.fit_transform(city_day[['PM2.5']])\n",
    "city_day['PM10'] = mice_imputer.fit_transform(city_day[['PM10']])\n",
    "city_day['NO'] = mice_imputer.fit_transform(city_day[['NO']])\n",
    "city_day['NOx'] = mice_imputer.fit_transform(city_day[['NOx']])\n",
    "city_day['NH3'] = mice_imputer.fit_transform(city_day[['NH3']])\n",
    "city_day['CO'] = mice_imputer.fit_transform(city_day[['CO']])\n",
    "city_day['SO2'] = mice_imputer.fit_transform(city_day[['SO2']])\n",
    "city_day['O3'] = mice_imputer.fit_transform(city_day[['O3']])\n",
    "city_day['Benzene'] = mice_imputer.fit_transform(city_day[['Benzene']])\n",
    "city_day['Toluene'] = mice_imputer.fit_transform(city_day[['Toluene']])\n",
    "city_day['Xylene'] = mice_imputer.fit_transform(city_day[['Xylene']])\n",
    "city_day['AQI'] = mice_imputer.fit_transform(city_day[['AQI']])\n",
    "city_day['NO2'] = mice_imputer.fit_transform(city_day[['NO2']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "vAVw8BC7gfWL",
    "outputId": "39fd947a-a01f-4127-8656-a28f76540a75",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "City          0\n",
       "Date          0\n",
       "PM2.5         0\n",
       "PM10          0\n",
       "NO            0\n",
       "NO2           0\n",
       "NOx           0\n",
       "NH3           0\n",
       "CO            0\n",
       "SO2           0\n",
       "O3            0\n",
       "Benzene       0\n",
       "Toluene       0\n",
       "Xylene        0\n",
       "AQI           0\n",
       "AQI_Bucket    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_day.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 593
    },
    "id": "_Zl1cSyagfWM",
    "outputId": "6173b6f9-eaa3-495b-f2bb-a18b17c992da"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</th>\n",
       "      <th>Date</th>\n",
       "      <th>PM2.5</th>\n",
       "      <th>PM10</th>\n",
       "      <th>NO</th>\n",
       "      <th>NO2</th>\n",
       "      <th>NOx</th>\n",
       "      <th>NH3</th>\n",
       "      <th>CO</th>\n",
       "      <th>SO2</th>\n",
       "      <th>O3</th>\n",
       "      <th>Benzene</th>\n",
       "      <th>Toluene</th>\n",
       "      <th>Xylene</th>\n",
       "      <th>AQI</th>\n",
       "      <th>AQI_Bucket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>0.92</td>\n",
       "      <td>18.22</td>\n",
       "      <td>17.15</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>0.92</td>\n",
       "      <td>27.64</td>\n",
       "      <td>133.36</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>0.97</td>\n",
       "      <td>15.69</td>\n",
       "      <td>16.46</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>0.97</td>\n",
       "      <td>24.55</td>\n",
       "      <td>34.06</td>\n",
       "      <td>3.68000</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>3.770000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>17.40</td>\n",
       "      <td>19.30</td>\n",
       "      <td>29.70</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>17.40</td>\n",
       "      <td>29.07</td>\n",
       "      <td>30.70</td>\n",
       "      <td>6.80000</td>\n",
       "      <td>16.400000</td>\n",
       "      <td>2.250000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>1.70</td>\n",
       "      <td>18.48</td>\n",
       "      <td>17.97</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>1.70</td>\n",
       "      <td>18.59</td>\n",
       "      <td>36.08</td>\n",
       "      <td>4.43000</td>\n",
       "      <td>10.140000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>67.450578</td>\n",
       "      <td>118.127103</td>\n",
       "      <td>22.10</td>\n",
       "      <td>21.42</td>\n",
       "      <td>37.76</td>\n",
       "      <td>23.483476</td>\n",
       "      <td>22.10</td>\n",
       "      <td>39.33</td>\n",
       "      <td>39.31</td>\n",
       "      <td>7.01000</td>\n",
       "      <td>18.890000</td>\n",
       "      <td>2.780000</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29526</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-06-27</td>\n",
       "      <td>15.020000</td>\n",
       "      <td>50.940000</td>\n",
       "      <td>7.68</td>\n",
       "      <td>25.06</td>\n",
       "      <td>19.54</td>\n",
       "      <td>12.470000</td>\n",
       "      <td>0.47</td>\n",
       "      <td>8.55</td>\n",
       "      <td>23.30</td>\n",
       "      <td>2.24000</td>\n",
       "      <td>12.070000</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29527</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-06-28</td>\n",
       "      <td>24.380000</td>\n",
       "      <td>74.090000</td>\n",
       "      <td>3.42</td>\n",
       "      <td>26.06</td>\n",
       "      <td>16.53</td>\n",
       "      <td>11.990000</td>\n",
       "      <td>0.52</td>\n",
       "      <td>12.72</td>\n",
       "      <td>30.14</td>\n",
       "      <td>0.74000</td>\n",
       "      <td>2.210000</td>\n",
       "      <td>0.380000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29528</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-06-29</td>\n",
       "      <td>22.910000</td>\n",
       "      <td>65.730000</td>\n",
       "      <td>3.45</td>\n",
       "      <td>29.53</td>\n",
       "      <td>18.33</td>\n",
       "      <td>10.710000</td>\n",
       "      <td>0.48</td>\n",
       "      <td>8.42</td>\n",
       "      <td>30.96</td>\n",
       "      <td>0.01000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29529</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>16.640000</td>\n",
       "      <td>49.970000</td>\n",
       "      <td>4.05</td>\n",
       "      <td>29.26</td>\n",
       "      <td>18.80</td>\n",
       "      <td>10.030000</td>\n",
       "      <td>0.52</td>\n",
       "      <td>9.84</td>\n",
       "      <td>28.30</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29530</th>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>0.40</td>\n",
       "      <td>26.85</td>\n",
       "      <td>14.05</td>\n",
       "      <td>5.200000</td>\n",
       "      <td>0.59</td>\n",
       "      <td>2.10</td>\n",
       "      <td>17.05</td>\n",
       "      <td>3.28084</td>\n",
       "      <td>8.700972</td>\n",
       "      <td>3.070128</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29531 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                City        Date      PM2.5        PM10     NO    NO2    NOx  \\\n",
       "0          Ahmedabad  2015-01-01  67.450578  118.127103   0.92  18.22  17.15   \n",
       "1          Ahmedabad  2015-01-02  67.450578  118.127103   0.97  15.69  16.46   \n",
       "2          Ahmedabad  2015-01-03  67.450578  118.127103  17.40  19.30  29.70   \n",
       "3          Ahmedabad  2015-01-04  67.450578  118.127103   1.70  18.48  17.97   \n",
       "4          Ahmedabad  2015-01-05  67.450578  118.127103  22.10  21.42  37.76   \n",
       "...              ...         ...        ...         ...    ...    ...    ...   \n",
       "29526  Visakhapatnam  2020-06-27  15.020000   50.940000   7.68  25.06  19.54   \n",
       "29527  Visakhapatnam  2020-06-28  24.380000   74.090000   3.42  26.06  16.53   \n",
       "29528  Visakhapatnam  2020-06-29  22.910000   65.730000   3.45  29.53  18.33   \n",
       "29529  Visakhapatnam  2020-06-30  16.640000   49.970000   4.05  29.26  18.80   \n",
       "29530  Visakhapatnam  2020-07-01  15.000000   66.000000   0.40  26.85  14.05   \n",
       "\n",
       "             NH3     CO    SO2      O3  Benzene    Toluene    Xylene  \\\n",
       "0      23.483476   0.92  27.64  133.36  0.00000   0.020000  0.000000   \n",
       "1      23.483476   0.97  24.55   34.06  3.68000   5.500000  3.770000   \n",
       "2      23.483476  17.40  29.07   30.70  6.80000  16.400000  2.250000   \n",
       "3      23.483476   1.70  18.59   36.08  4.43000  10.140000  1.000000   \n",
       "4      23.483476  22.10  39.33   39.31  7.01000  18.890000  2.780000   \n",
       "...          ...    ...    ...     ...      ...        ...       ...   \n",
       "29526  12.470000   0.47   8.55   23.30  2.24000  12.070000  0.730000   \n",
       "29527  11.990000   0.52  12.72   30.14  0.74000   2.210000  0.380000   \n",
       "29528  10.710000   0.48   8.42   30.96  0.01000   0.010000  0.000000   \n",
       "29529  10.030000   0.52   9.84   28.30  0.00000   0.000000  0.000000   \n",
       "29530   5.200000   0.59   2.10   17.05  3.28084   8.700972  3.070128   \n",
       "\n",
       "              AQI    AQI_Bucket  \n",
       "0      166.463581      Moderate  \n",
       "1      166.463581      Moderate  \n",
       "2      166.463581      Moderate  \n",
       "3      166.463581      Moderate  \n",
       "4      166.463581      Moderate  \n",
       "...           ...           ...  \n",
       "29526   41.000000          Good  \n",
       "29527   70.000000  Satisfactory  \n",
       "29528   68.000000  Satisfactory  \n",
       "29529   54.000000  Satisfactory  \n",
       "29530   50.000000          Good  \n",
       "\n",
       "[29531 rows x 16 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_day['AQI_Bucket'] = np.where(\n",
    "   (city_day['AQI'] <=50) & (city_day['AQI'] >=0) ,'Good' , city_day['AQI_Bucket']\n",
    "   )\n",
    "city_day['AQI_Bucket'] = np.where(\n",
    "   (city_day['AQI'] <=100) & (city_day['AQI'] >=51) ,'Satisfactory' , city_day['AQI_Bucket']\n",
    "   )\n",
    "city_day['AQI_Bucket'] = np.where(\n",
    "   (city_day['AQI'] <=200) & (city_day['AQI'] >=101) ,'Moderate' , city_day['AQI_Bucket']\n",
    "   )\n",
    "city_day['AQI_Bucket'] = np.where(\n",
    "   (city_day['AQI'] <=300) & (city_day['AQI'] >=201) ,'Poor' , city_day['AQI_Bucket']\n",
    "   )\n",
    "city_day['AQI_Bucket'] = np.where(\n",
    "   (city_day['AQI'] <=400) & (city_day['AQI'] >=301) ,'Very Poor' , city_day['AQI_Bucket']\n",
    "   )\n",
    "city_day['AQI_Bucket'] = np.where(\n",
    "   (city_day['AQI'] <=500) & (city_day['AQI'] >=401) ,'Severe' , city_day['AQI_Bucket']\n",
    "   )\n",
    "city_day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "id": "tOc4lL08gfWN"
   },
   "outputs": [],
   "source": [
    "city_day.to_csv('city_day.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 406
    },
    "id": "wBlBFQyAgfWN",
    "outputId": "cbfa673a-0e51-4247-b894-10f73898f548"
   },
   "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>Date</th>\n",
       "      <th>City</th>\n",
       "      <th>AQI</th>\n",
       "      <th>AQI_Bucket</th>\n",
       "      <th>Particulate_Matter</th>\n",
       "      <th>NO2</th>\n",
       "      <th>CO</th>\n",
       "      <th>SO2</th>\n",
       "      <th>O3</th>\n",
       "      <th>BTX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>18.22</td>\n",
       "      <td>0.92</td>\n",
       "      <td>27.64</td>\n",
       "      <td>133.36</td>\n",
       "      <td>0.02000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>15.69</td>\n",
       "      <td>0.97</td>\n",
       "      <td>24.55</td>\n",
       "      <td>34.06</td>\n",
       "      <td>12.95000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>19.30</td>\n",
       "      <td>17.40</td>\n",
       "      <td>29.07</td>\n",
       "      <td>30.70</td>\n",
       "      <td>25.45000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>18.48</td>\n",
       "      <td>1.70</td>\n",
       "      <td>18.59</td>\n",
       "      <td>36.08</td>\n",
       "      <td>15.57000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>21.42</td>\n",
       "      <td>22.10</td>\n",
       "      <td>39.33</td>\n",
       "      <td>39.31</td>\n",
       "      <td>28.68000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29526</th>\n",
       "      <td>2020-06-27</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>Good</td>\n",
       "      <td>65.960000</td>\n",
       "      <td>25.06</td>\n",
       "      <td>0.47</td>\n",
       "      <td>8.55</td>\n",
       "      <td>23.30</td>\n",
       "      <td>15.04000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29527</th>\n",
       "      <td>2020-06-28</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "      <td>98.470000</td>\n",
       "      <td>26.06</td>\n",
       "      <td>0.52</td>\n",
       "      <td>12.72</td>\n",
       "      <td>30.14</td>\n",
       "      <td>3.33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29528</th>\n",
       "      <td>2020-06-29</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "      <td>88.640000</td>\n",
       "      <td>29.53</td>\n",
       "      <td>0.48</td>\n",
       "      <td>8.42</td>\n",
       "      <td>30.96</td>\n",
       "      <td>0.02000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29529</th>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "      <td>66.610000</td>\n",
       "      <td>29.26</td>\n",
       "      <td>0.52</td>\n",
       "      <td>9.84</td>\n",
       "      <td>28.30</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29530</th>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>Good</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>26.85</td>\n",
       "      <td>0.59</td>\n",
       "      <td>2.10</td>\n",
       "      <td>17.05</td>\n",
       "      <td>15.05194</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29531 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date           City         AQI    AQI_Bucket  Particulate_Matter  \\\n",
       "0     2015-01-01      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "1     2015-01-02      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "2     2015-01-03      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "3     2015-01-04      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "4     2015-01-05      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "...          ...            ...         ...           ...                 ...   \n",
       "29526 2020-06-27  Visakhapatnam   41.000000          Good           65.960000   \n",
       "29527 2020-06-28  Visakhapatnam   70.000000  Satisfactory           98.470000   \n",
       "29528 2020-06-29  Visakhapatnam   68.000000  Satisfactory           88.640000   \n",
       "29529 2020-06-30  Visakhapatnam   54.000000  Satisfactory           66.610000   \n",
       "29530 2020-07-01  Visakhapatnam   50.000000          Good           81.000000   \n",
       "\n",
       "         NO2     CO    SO2      O3       BTX  \n",
       "0      18.22   0.92  27.64  133.36   0.02000  \n",
       "1      15.69   0.97  24.55   34.06  12.95000  \n",
       "2      19.30  17.40  29.07   30.70  25.45000  \n",
       "3      18.48   1.70  18.59   36.08  15.57000  \n",
       "4      21.42  22.10  39.33   39.31  28.68000  \n",
       "...      ...    ...    ...     ...       ...  \n",
       "29526  25.06   0.47   8.55   23.30  15.04000  \n",
       "29527  26.06   0.52  12.72   30.14   3.33000  \n",
       "29528  29.53   0.48   8.42   30.96   0.02000  \n",
       "29529  29.26   0.52   9.84   28.30   0.00000  \n",
       "29530  26.85   0.59   2.10   17.05  15.05194  \n",
       "\n",
       "[29531 rows x 10 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def mergeColumns(data):\n",
    "    data['Date'] = pd.to_datetime(data['Date'])\n",
    "    data['BTX'] = data['Benzene'] + data['Toluene'] + data['Xylene']\n",
    "    data.drop(['Benzene','Toluene','Xylene'], axis=1)\n",
    "    data['Particulate_Matter'] = data['PM2.5'] + data['PM10']\n",
    "    return data\n",
    "\n",
    "def subsetColumns(data):\n",
    "    pollutants = ['Particulate_Matter', 'NO2', 'CO','SO2', 'O3', 'BTX']\n",
    "    columns =  ['Date', 'City', 'AQI', 'AQI_Bucket'] + pollutants\n",
    "    data = data[columns]\n",
    "    return data, pollutants\n",
    "def handleMissingValues(data):\n",
    "   # missing_values = getMissingValues(data)\n",
    "    newCityData = mergeColumns(data)\n",
    "    newCityData, pollutants = subsetColumns(newCityData)\n",
    "    return newCityData, pollutants\n",
    "\n",
    "newCityData, newColumns = handleMissingValues(city_day)\n",
    "newCityData\n",
    "#print(newColumns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "EeMgUuGpgfWO",
    "outputId": "2678a3bb-5f2f-439c-8753-ac67282d7371"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date                  0\n",
       "City                  0\n",
       "AQI                   0\n",
       "AQI_Bucket            0\n",
       "Particulate_Matter    0\n",
       "NO2                   0\n",
       "CO                    0\n",
       "SO2                   0\n",
       "O3                    0\n",
       "BTX                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newCityData.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 593
    },
    "id": "EuOPKmAYgfWP",
    "outputId": "b6672b0f-5c77-47ff-d3db-e95bc6fe5f69"
   },
   "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>Date</th>\n",
       "      <th>City</th>\n",
       "      <th>AQI</th>\n",
       "      <th>AQI_Bucket</th>\n",
       "      <th>Particulate_Matter</th>\n",
       "      <th>NO2</th>\n",
       "      <th>CO</th>\n",
       "      <th>SO2</th>\n",
       "      <th>O3</th>\n",
       "      <th>BTX</th>\n",
       "      <th>Particulate_Matter_new</th>\n",
       "      <th>NO2_new</th>\n",
       "      <th>CO_new</th>\n",
       "      <th>SO2_new</th>\n",
       "      <th>O3_new</th>\n",
       "      <th>BTX_new</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>18.22</td>\n",
       "      <td>0.92</td>\n",
       "      <td>27.64</td>\n",
       "      <td>133.36</td>\n",
       "      <td>0.02000</td>\n",
       "      <td>0.096167</td>\n",
       "      <td>0.050276</td>\n",
       "      <td>0.005233</td>\n",
       "      <td>0.142533</td>\n",
       "      <td>0.517422</td>\n",
       "      <td>0.000022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>15.69</td>\n",
       "      <td>0.97</td>\n",
       "      <td>24.55</td>\n",
       "      <td>34.06</td>\n",
       "      <td>12.95000</td>\n",
       "      <td>0.096167</td>\n",
       "      <td>0.043291</td>\n",
       "      <td>0.005517</td>\n",
       "      <td>0.126593</td>\n",
       "      <td>0.132120</td>\n",
       "      <td>0.014188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>19.30</td>\n",
       "      <td>17.40</td>\n",
       "      <td>29.07</td>\n",
       "      <td>30.70</td>\n",
       "      <td>25.45000</td>\n",
       "      <td>0.096167</td>\n",
       "      <td>0.053258</td>\n",
       "      <td>0.098970</td>\n",
       "      <td>0.149910</td>\n",
       "      <td>0.119083</td>\n",
       "      <td>0.027882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>18.48</td>\n",
       "      <td>1.70</td>\n",
       "      <td>18.59</td>\n",
       "      <td>36.08</td>\n",
       "      <td>15.57000</td>\n",
       "      <td>0.096167</td>\n",
       "      <td>0.050994</td>\n",
       "      <td>0.009670</td>\n",
       "      <td>0.095847</td>\n",
       "      <td>0.139958</td>\n",
       "      <td>0.017058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>166.463581</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>185.577681</td>\n",
       "      <td>21.42</td>\n",
       "      <td>22.10</td>\n",
       "      <td>39.33</td>\n",
       "      <td>39.31</td>\n",
       "      <td>28.68000</td>\n",
       "      <td>0.096167</td>\n",
       "      <td>0.059111</td>\n",
       "      <td>0.125704</td>\n",
       "      <td>0.202837</td>\n",
       "      <td>0.152491</td>\n",
       "      <td>0.031421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29526</th>\n",
       "      <td>2020-06-27</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>Good</td>\n",
       "      <td>65.960000</td>\n",
       "      <td>25.06</td>\n",
       "      <td>0.47</td>\n",
       "      <td>8.55</td>\n",
       "      <td>23.30</td>\n",
       "      <td>15.04000</td>\n",
       "      <td>0.033713</td>\n",
       "      <td>0.069161</td>\n",
       "      <td>0.002673</td>\n",
       "      <td>0.044055</td>\n",
       "      <td>0.090369</td>\n",
       "      <td>0.016477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29527</th>\n",
       "      <td>2020-06-28</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "      <td>98.470000</td>\n",
       "      <td>26.06</td>\n",
       "      <td>0.52</td>\n",
       "      <td>12.72</td>\n",
       "      <td>30.14</td>\n",
       "      <td>3.33000</td>\n",
       "      <td>0.050687</td>\n",
       "      <td>0.071922</td>\n",
       "      <td>0.002958</td>\n",
       "      <td>0.065566</td>\n",
       "      <td>0.116910</td>\n",
       "      <td>0.003648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29528</th>\n",
       "      <td>2020-06-29</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "      <td>88.640000</td>\n",
       "      <td>29.53</td>\n",
       "      <td>0.48</td>\n",
       "      <td>8.42</td>\n",
       "      <td>30.96</td>\n",
       "      <td>0.02000</td>\n",
       "      <td>0.045555</td>\n",
       "      <td>0.081502</td>\n",
       "      <td>0.002730</td>\n",
       "      <td>0.043384</td>\n",
       "      <td>0.120092</td>\n",
       "      <td>0.000022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29529</th>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>Satisfactory</td>\n",
       "      <td>66.610000</td>\n",
       "      <td>29.26</td>\n",
       "      <td>0.52</td>\n",
       "      <td>9.84</td>\n",
       "      <td>28.30</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.034052</td>\n",
       "      <td>0.080756</td>\n",
       "      <td>0.002958</td>\n",
       "      <td>0.050709</td>\n",
       "      <td>0.109770</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29530</th>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>Good</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>26.85</td>\n",
       "      <td>0.59</td>\n",
       "      <td>2.10</td>\n",
       "      <td>17.05</td>\n",
       "      <td>15.05194</td>\n",
       "      <td>0.041566</td>\n",
       "      <td>0.074103</td>\n",
       "      <td>0.003356</td>\n",
       "      <td>0.010782</td>\n",
       "      <td>0.066118</td>\n",
       "      <td>0.016490</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29531 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date           City         AQI    AQI_Bucket  Particulate_Matter  \\\n",
       "0     2015-01-01      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "1     2015-01-02      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "2     2015-01-03      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "3     2015-01-04      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "4     2015-01-05      Ahmedabad  166.463581      Moderate          185.577681   \n",
       "...          ...            ...         ...           ...                 ...   \n",
       "29526 2020-06-27  Visakhapatnam   41.000000          Good           65.960000   \n",
       "29527 2020-06-28  Visakhapatnam   70.000000  Satisfactory           98.470000   \n",
       "29528 2020-06-29  Visakhapatnam   68.000000  Satisfactory           88.640000   \n",
       "29529 2020-06-30  Visakhapatnam   54.000000  Satisfactory           66.610000   \n",
       "29530 2020-07-01  Visakhapatnam   50.000000          Good           81.000000   \n",
       "\n",
       "         NO2     CO    SO2      O3       BTX  Particulate_Matter_new  \\\n",
       "0      18.22   0.92  27.64  133.36   0.02000                0.096167   \n",
       "1      15.69   0.97  24.55   34.06  12.95000                0.096167   \n",
       "2      19.30  17.40  29.07   30.70  25.45000                0.096167   \n",
       "3      18.48   1.70  18.59   36.08  15.57000                0.096167   \n",
       "4      21.42  22.10  39.33   39.31  28.68000                0.096167   \n",
       "...      ...    ...    ...     ...       ...                     ...   \n",
       "29526  25.06   0.47   8.55   23.30  15.04000                0.033713   \n",
       "29527  26.06   0.52  12.72   30.14   3.33000                0.050687   \n",
       "29528  29.53   0.48   8.42   30.96   0.02000                0.045555   \n",
       "29529  29.26   0.52   9.84   28.30   0.00000                0.034052   \n",
       "29530  26.85   0.59   2.10   17.05  15.05194                0.041566   \n",
       "\n",
       "        NO2_new    CO_new   SO2_new    O3_new   BTX_new  \n",
       "0      0.050276  0.005233  0.142533  0.517422  0.000022  \n",
       "1      0.043291  0.005517  0.126593  0.132120  0.014188  \n",
       "2      0.053258  0.098970  0.149910  0.119083  0.027882  \n",
       "3      0.050994  0.009670  0.095847  0.139958  0.017058  \n",
       "4      0.059111  0.125704  0.202837  0.152491  0.031421  \n",
       "...         ...       ...       ...       ...       ...  \n",
       "29526  0.069161  0.002673  0.044055  0.090369  0.016477  \n",
       "29527  0.071922  0.002958  0.065566  0.116910  0.003648  \n",
       "29528  0.081502  0.002730  0.043384  0.120092  0.000022  \n",
       "29529  0.080756  0.002958  0.050709  0.109770  0.000000  \n",
       "29530  0.074103  0.003356  0.010782  0.066118  0.016490  \n",
       "\n",
       "[29531 rows x 16 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min_Particulate_Matter = newCityData['Particulate_Matter'].min()\n",
    "max_Particulate_Matter = newCityData['Particulate_Matter'].max()\n",
    "newCityData['Particulate_Matter_new'] = [(x-min_Particulate_Matter)/(max_Particulate_Matter-min_Particulate_Matter) \n",
    "                                         for x in newCityData['Particulate_Matter']]\n",
    "\n",
    "min_NO2\t= newCityData['NO2'].min()\n",
    "max_NO2 = newCityData['NO2'].max()\n",
    "newCityData['NO2_new'] = [(x-min_NO2)/(max_NO2-min_NO2) for x in newCityData['NO2']]\n",
    "\n",
    "min_CO= newCityData['CO'].min()\n",
    "max_CO = newCityData['CO'].max()\n",
    "newCityData['CO_new'] = [(x-min_CO)/(max_CO-min_CO) for x in newCityData['CO']]\n",
    "\n",
    "min_SO2= newCityData['SO2'].min()\n",
    "max_SO2 = newCityData['SO2'].max()\n",
    "newCityData['SO2_new'] = [(x-min_SO2)/(max_SO2-min_SO2) for x in newCityData['SO2']]\n",
    "\n",
    "min_O3= newCityData['O3'].min()\n",
    "max_O3 = newCityData['O3'].max()\n",
    "newCityData['O3_new'] = [(x-min_O3)/(max_O3-min_O3) for x in newCityData['O3']]\n",
    "\n",
    "min_BTX = newCityData['BTX'].min()\n",
    "max_BTX = newCityData['BTX'].max()\n",
    "newCityData['BTX_new'] = [(x-min_BTX)/(max_BTX-min_BTX) for x in newCityData['BTX']]\n",
    "newCityData"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "id": "zTn4eiIdgfWQ"
   },
   "outputs": [],
   "source": [
    "newCityData= newCityData[['City','Date','AQI','AQI_Bucket', 'Particulate_Matter_new','NO2_new','CO_new','SO2_new','O3_new',\n",
    "                          'BTX_new']]\n",
    "newCityData.to_csv('newCityData.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "id": "OddjFa08gfWQ"
   },
   "outputs": [],
   "source": [
    "pollutant = ['Particulate_Matter_new','NO2_new','CO_new','SO2_new','O3_new','BTX_new']\n",
    "column =  ['Date', 'City', 'AQI', 'AQI_Bucket'] + pollutant\n",
    "nCityData = newCityData[column]\n",
    "nCityData.to_csv('nCityData.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 807
    },
    "id": "T-RR8T7qgfWR",
    "outputId": "0d2bc52c-fa43-414d-c03b-2ff9a6f9429c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1080 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def visualisepollutants(udata, column):\n",
    "    data = udata.copy()\n",
    "    data.set_index('Date',inplace=True)\n",
    "            \n",
    "    axes = data[column].plot(marker='.', alpha=10, linestyle='None', figsize=(16, 15), subplots=True)\n",
    "    for ax in axes:\n",
    "        ax.set_xlabel('Years')\n",
    "        ax.set_ylabel('ug/m3')\n",
    "visualisepollutants(nCityData, pollutant)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 518
    },
    "id": "i5cSEiMZgfWS",
    "outputId": "0fa82762-398d-4f94-b453-b811750f1906"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x240 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x240 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def trend_plot(nCityData, value):\n",
    "    data = nCityData.copy()\n",
    "    data['Year'] = [d.year for d in data.Date]\n",
    "    data['Month'] = [d.strftime('%b') for d in data.Date]\n",
    "    years = data['Year'].unique()\n",
    "    fig, axes = plt.subplots(1, 2, figsize=(12,3), dpi= 80)\n",
    "    sns.boxplot(x='Year', y=value, data=data, ax=axes[0])\n",
    "    sns.lineplot(x='Month', y=value, data=data.loc[~data.Year.isin([2015, 2020]), :])\n",
    "    \n",
    "    axes[0].set_title('Year-wise Plot i.e. the trend', fontsize=18); \n",
    "    axes[1].set_title('Month-wise Plot i.e. the seasonality', fontsize=18)\n",
    "    plt.show()\n",
    "value='Particulate_Matter_new'\n",
    "trend_plot(nCityData,value)\n",
    "value='NO2_new'\n",
    "trend_plot(nCityData,value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 220
    },
    "id": "MxlH8Rw_gfWT",
    "outputId": "23b3d135-5594-48c2-f12d-d363416b3fbb"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def visualiseAQI(udata, column):\n",
    "    data = udata.copy()\n",
    "    data.set_index('Date',inplace=True)\n",
    "            \n",
    "    axes = data[column].plot(marker='.', alpha=0.5, linestyle='None', figsize=(16, 3), subplots=True)\n",
    "    for ax in axes:\n",
    "        ax.set_xlabel('Years')\n",
    "        ax.set_ylabel('AQI')\n",
    "visualiseAQI(nCityData, ['AQI'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "id": "r-NxwKCqgfWU"
   },
   "outputs": [],
   "source": [
    "from pandas import DataFrame\n",
    "from pandas import concat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "id": "-iBZeg79gfWU"
   },
   "outputs": [],
   "source": [
    "def series_to_supervised(data, n_in=1, n_out=1, dropnan=True):\n",
    "    n_vars = 1 if type(data) is list else data.shape[1]\n",
    "    df = DataFrame(data)\n",
    "    cols, names = list(), list()\n",
    "    # input sequence (t-n, ... t-1)\n",
    "    for i in range(n_in, 0, -1):\n",
    "        cols.append(df.shift(i))\n",
    "        names += [('var%d(t-%d)' % (j+1, i)) for j in range(n_vars)]\n",
    "    # forecast sequence (t, t+1, ... t+n)\n",
    "    for i in range(0, n_out):\n",
    "        cols.append(df.shift(-i))\n",
    "        if i == 0:\n",
    "            names += [('var%d(t)' % (j+1)) for j in range(n_vars)]\n",
    "        else:\n",
    "            names += [('var%d(t+%d)' % (j+1, i)) for j in range(n_vars)]\n",
    "    # put it all together\n",
    "    agg = concat(cols, axis=1)\n",
    "    agg.columns = names\n",
    "    # drop rows with NaN values\n",
    "    if dropnan:\n",
    "        agg.dropna(inplace=True)\n",
    "    return agg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "id": "eBmocxQqgfWV"
   },
   "outputs": [],
   "source": [
    "newCityData = pd.read_csv('newCityData.csv', header=0, index_col=0)\n",
    "values = newCityData.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "W4BPWSokgfWV",
    "outputId": "2408a5c5-adba-4509-e1ab-722a17c7dbb1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([['Ahmedabad', '2015-01-01', 166.4635814889336, ...,\n",
       "        0.14253288625225688, 0.5174220083811889, 2.191132179981615e-05],\n",
       "       ['Ahmedabad', '2015-01-02', 166.4635814889336, ...,\n",
       "        0.12659272633479493, 0.13212013037404935, 0.01418758086538096],\n",
       "       ['Ahmedabad', '2015-01-03', 166.4635814889336, ...,\n",
       "        0.1499097240134124, 0.11908272543846032, 0.02788215699026605],\n",
       "       ...,\n",
       "       ['Visakhapatnam', '2020-06-29', 68.0, ..., 0.04338405984008253,\n",
       "        0.12009157224895235, 2.191132179981615e-05],\n",
       "       ['Visakhapatnam', '2020-06-30', 54.0, ..., 0.050709311323188025,\n",
       "        0.10977029334161104, 0.0],\n",
       "       ['Visakhapatnam', '2020-07-01', 50.0, ..., 0.010781532112458086,\n",
       "        0.06611826788762998, 0.016490395280493782]], dtype=object)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values[:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "id": "jPmZRUsTgfWV"
   },
   "outputs": [],
   "source": [
    "cities = ['Mumbai','Shillong','Lucknow','Delhi','Visakhapatnam','Patna','Bhopal']\n",
    "somecityday = newCityData[newCityData['Date'] >= '2015-01-01']\n",
    "AQI = somecityday[somecityday.City.isin(cities)][['Date','City','AQI','AQI_Bucket']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "id": "9qryW5YfgfWW"
   },
   "outputs": [],
   "source": [
    "AQI_pivot = AQI.pivot(index='Date', columns='City', values='AQI')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "cARzRAQrgfWW",
    "outputId": "962441e3-36a4-4687-c379-866708685061",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'AQI')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1296 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def getColorBar(city):\n",
    "    col = []\n",
    "    for val in AQI_pivot[city]:\n",
    "        if val < 50:\n",
    "            col.append('royalblue')\n",
    "        elif val > 50 and val < 101:\n",
    "            col.append('lightskyblue') #cornflowerblue\n",
    "        elif val > 100 and val < 201:\n",
    "            col.append('lightsteelblue')\n",
    "        elif val > 200 and val < 301:\n",
    "            col.append('peachpuff')\n",
    "        elif val > 300 and val < 401:\n",
    "            col.append('lightcoral')\n",
    "        elif val> 400:\n",
    "            col.append('firebrick')\n",
    "        else:\n",
    "            col.append('white')\n",
    "    return col\n",
    "\n",
    "\n",
    "ah = getColorBar('Mumbai')\n",
    "de = getColorBar('Shillong')\n",
    "mu = getColorBar('Lucknow')\n",
    "ko = getColorBar('Delhi')\n",
    "hy = getColorBar('Visakhapatnam')\n",
    "ch = getColorBar('Patna')\n",
    "bp=getColorBar('Bhopal')\n",
    "\n",
    "\n",
    "colors = {'Good':'royalblue', 'Satisfactory':'lightskyblue', 'Moderate':'lightsteelblue', 'Poor':'peachpuff', 'Very Poor':'lightcoral', 'Severe':'firebrick'}         \n",
    "labels = list(colors.keys())\n",
    "handles = [plt.Rectangle((0,0),1,1, color=colors[label]) for label in labels]\n",
    "        \n",
    "f, ((ax1, ax2, ax3, ax4, ax5, ax6, ax7)) = plt.subplots(7, 1, sharex='col', sharey='row', figsize=(15,18))\n",
    "ax1.bar(AQI_pivot.index, AQI_pivot['Mumbai'], color = ah, width = 0.75)\n",
    "ax2.bar(AQI_pivot.index, AQI_pivot['Shillong'], color = de, width = 0.75)\n",
    "ax3.bar(AQI_pivot.index, AQI_pivot['Lucknow'], color = mu, width = 0.75)\n",
    "ax4.bar(AQI_pivot.index, AQI_pivot['Delhi'], color = ko, width = 0.75)\n",
    "ax5.bar(AQI_pivot.index, AQI_pivot['Visakhapatnam'], color = hy, width = 0.75)\n",
    "ax6.bar(AQI_pivot.index, AQI_pivot['Patna'], color = ch, width = 0.75)\n",
    "ax7.bar(AQI_pivot.index, AQI_pivot['Bhopal'], color = bp, width = 0.75)\n",
    "\n",
    "ax1.legend(handles, labels, loc='upper left')\n",
    "ax2.legend(handles, labels, loc='upper left')\n",
    "ax3.legend(handles, labels, loc='upper left')\n",
    "ax4.legend(handles, labels, loc='upper left')\n",
    "ax5.legend(handles, labels, loc='upper left')\n",
    "ax6.legend(handles, labels, loc='upper left')\n",
    "ax7.legend(handles, labels, loc='upper left')\n",
    "\n",
    "ax1.title.set_text('Mumbai')\n",
    "ax2.title.set_text('Shillong')\n",
    "ax3.title.set_text('Lucknow')\n",
    "ax4.title.set_text('Delhi')\n",
    "ax5.title.set_text('Visakhapatnam')\n",
    "ax6.title.set_text('Patna')\n",
    "ax7.title.set_text('Bhopal')\n",
    "\n",
    "\n",
    "ax1.set_ylabel('AQI')\n",
    "ax2.set_ylabel('AQI')\n",
    "ax3.set_ylabel('AQI')\n",
    "ax4.set_ylabel('AQI')\n",
    "ax5.set_ylabel('AQI')\n",
    "ax6.set_ylabel('AQI')\n",
    "ax7.set_ylabel('AQI')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 643
    },
    "id": "RQHnHpQegfWX",
    "outputId": "b80e8344-6fea-4da9-e1c2-aa92a5f34b54"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1944x108 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1944x108 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1944x108 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1944x108 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1944x108 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1944x108 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1944x108 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "AQI_beforeLockdown = AQI_pivot['2015-01-01':'2020-03-25']\n",
    "AQI_afterLockdown = AQI_pivot['2020-03-26':'2020-07-01']\n",
    "limits = [50, 100, 200, 300, 400, 510]\n",
    "#palette = sns.light_palette(\"Spectral\", len(limits), reverse = True)\n",
    "palette = sns.color_palette(\"coolwarm\", len(limits))\n",
    "for city in cities:\n",
    "    aqi_before = AQI_beforeLockdown[city].mean()\n",
    "    aqi_after = AQI_afterLockdown[city].mean()\n",
    "    fig, (ax1, ax2) = plt.subplots(1,2,figsize=(27, 1.5))\n",
    "    ax1.set_yticks([1])\n",
    "    ax1.set_yticklabels([city])\n",
    "    ax1.spines['bottom'].set_visible(False)\n",
    "    ax1.spines['top'].set_visible(False)\n",
    "    ax1.spines['right'].set_visible(False)\n",
    "    ax1.spines['left'].set_visible(False)\n",
    "\n",
    "    prev_limit = 0\n",
    "    for idx, lim in enumerate(limits):\n",
    "        ax1.barh([1], lim-prev_limit, left=prev_limit, height=15, color=palette[idx])\n",
    "        prev_limit = lim\n",
    "\n",
    "    ax1.barh([1], aqi_before, color='black', height=5)\n",
    "    \n",
    "    # after lockdown\n",
    "    ax2.set_yticks([1])\n",
    "    ax2.set_yticklabels([city])\n",
    "    ax2.spines['bottom'].set_visible(False)\n",
    "    ax2.spines['top'].set_visible(False)\n",
    "    ax2.spines['right'].set_visible(False)\n",
    "    ax2.spines['left'].set_visible(False)\n",
    "\n",
    "    prev_limit = 0\n",
    "    for idx, lim in enumerate(limits):\n",
    "        ax2.barh([1], lim-prev_limit, left=prev_limit, height=15, color=palette[idx])\n",
    "        prev_limit = lim\n",
    "\n",
    "    ax2.barh([1], aqi_after, color='black', height=5)\n",
    "    \n",
    "    ax1.set_title('Before Lockdown')\n",
    "    ax2.set_title('After Lockdown')\n",
    "    \n",
    "    rects = ax1.patches\n",
    "    labels=[\"Good\", \"Satisfactory\", \"Moderate\", \"Poor\", 'Very Poor', 'Severe']\n",
    "    \n",
    "    for rect, label in zip(rects, labels):\n",
    "        height = rect.get_height()\n",
    "        ax1.text(\n",
    "            rect.get_x() + rect.get_width() / 2,\n",
    "            -height * .4,\n",
    "            label,\n",
    "            ha='center',\n",
    "            va='bottom',\n",
    "            color='black')\n",
    "        ax2.text(\n",
    "            rect.get_x() + rect.get_width() / 2,\n",
    "            -height * .4,\n",
    "            label,\n",
    "            ha='center',\n",
    "            va='bottom',\n",
    "            color='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "id": "zsGWjnqkgfWY"
   },
   "outputs": [],
   "source": [
    "Delhi_data = newCityData[newCityData['City']=='Delhi']\n",
    "Delhi_data.set_index('Date',inplace=True, drop = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 436
    },
    "id": "s563-RMCgfWY",
    "outputId": "89e7e5c1-041f-4d86-d48a-e65956ebec34"
   },
   "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>City</th>\n",
       "      <th>Date</th>\n",
       "      <th>AQI</th>\n",
       "      <th>AQI_Bucket</th>\n",
       "      <th>Particulate_Matter_new</th>\n",
       "      <th>NO2_new</th>\n",
       "      <th>CO_new</th>\n",
       "      <th>SO2_new</th>\n",
       "      <th>O3_new</th>\n",
       "      <th>BTX_new</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-01-01</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>472.0</td>\n",
       "      <td>Severe</td>\n",
       "      <td>0.480248</td>\n",
       "      <td>0.100442</td>\n",
       "      <td>0.086457</td>\n",
       "      <td>0.047666</td>\n",
       "      <td>0.161687</td>\n",
       "      <td>0.053748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-02</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>454.0</td>\n",
       "      <td>Severe</td>\n",
       "      <td>0.237219</td>\n",
       "      <td>0.090723</td>\n",
       "      <td>0.054263</td>\n",
       "      <td>0.034253</td>\n",
       "      <td>0.116250</td>\n",
       "      <td>0.038268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-03</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>143.0</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>0.113660</td>\n",
       "      <td>0.083655</td>\n",
       "      <td>0.060349</td>\n",
       "      <td>0.013619</td>\n",
       "      <td>0.076440</td>\n",
       "      <td>0.017671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-04</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>319.0</td>\n",
       "      <td>Very Poor</td>\n",
       "      <td>0.204821</td>\n",
       "      <td>0.101877</td>\n",
       "      <td>0.065639</td>\n",
       "      <td>0.023833</td>\n",
       "      <td>0.098363</td>\n",
       "      <td>0.018964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-05</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>325.0</td>\n",
       "      <td>Very Poor</td>\n",
       "      <td>0.190228</td>\n",
       "      <td>0.096383</td>\n",
       "      <td>0.052329</td>\n",
       "      <td>0.017127</td>\n",
       "      <td>0.089981</td>\n",
       "      <td>0.013114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-27</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2020-06-27</td>\n",
       "      <td>112.0</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>0.101473</td>\n",
       "      <td>0.059221</td>\n",
       "      <td>0.004949</td>\n",
       "      <td>0.053495</td>\n",
       "      <td>0.073219</td>\n",
       "      <td>0.024223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-28</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2020-06-28</td>\n",
       "      <td>196.0</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>0.191502</td>\n",
       "      <td>0.059608</td>\n",
       "      <td>0.005347</td>\n",
       "      <td>0.055146</td>\n",
       "      <td>0.069998</td>\n",
       "      <td>0.031311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-29</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2020-06-29</td>\n",
       "      <td>233.0</td>\n",
       "      <td>Poor</td>\n",
       "      <td>0.118829</td>\n",
       "      <td>0.059525</td>\n",
       "      <td>0.005005</td>\n",
       "      <td>0.059685</td>\n",
       "      <td>0.103213</td>\n",
       "      <td>0.029646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>114.0</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>0.068079</td>\n",
       "      <td>0.049558</td>\n",
       "      <td>0.004778</td>\n",
       "      <td>0.054166</td>\n",
       "      <td>0.144653</td>\n",
       "      <td>0.020191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-01</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>101.0</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>0.094649</td>\n",
       "      <td>0.058089</td>\n",
       "      <td>0.005517</td>\n",
       "      <td>0.057467</td>\n",
       "      <td>0.115319</td>\n",
       "      <td>0.028759</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2009 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             City        Date    AQI AQI_Bucket  Particulate_Matter_new  \\\n",
       "Date                                                                      \n",
       "2015-01-01  Delhi  2015-01-01  472.0     Severe                0.480248   \n",
       "2015-01-02  Delhi  2015-01-02  454.0     Severe                0.237219   \n",
       "2015-01-03  Delhi  2015-01-03  143.0   Moderate                0.113660   \n",
       "2015-01-04  Delhi  2015-01-04  319.0  Very Poor                0.204821   \n",
       "2015-01-05  Delhi  2015-01-05  325.0  Very Poor                0.190228   \n",
       "...           ...         ...    ...        ...                     ...   \n",
       "2020-06-27  Delhi  2020-06-27  112.0   Moderate                0.101473   \n",
       "2020-06-28  Delhi  2020-06-28  196.0   Moderate                0.191502   \n",
       "2020-06-29  Delhi  2020-06-29  233.0       Poor                0.118829   \n",
       "2020-06-30  Delhi  2020-06-30  114.0   Moderate                0.068079   \n",
       "2020-07-01  Delhi  2020-07-01  101.0   Moderate                0.094649   \n",
       "\n",
       "             NO2_new    CO_new   SO2_new    O3_new   BTX_new  \n",
       "Date                                                          \n",
       "2015-01-01  0.100442  0.086457  0.047666  0.161687  0.053748  \n",
       "2015-01-02  0.090723  0.054263  0.034253  0.116250  0.038268  \n",
       "2015-01-03  0.083655  0.060349  0.013619  0.076440  0.017671  \n",
       "2015-01-04  0.101877  0.065639  0.023833  0.098363  0.018964  \n",
       "2015-01-05  0.096383  0.052329  0.017127  0.089981  0.013114  \n",
       "...              ...       ...       ...       ...       ...  \n",
       "2020-06-27  0.059221  0.004949  0.053495  0.073219  0.024223  \n",
       "2020-06-28  0.059608  0.005347  0.055146  0.069998  0.031311  \n",
       "2020-06-29  0.059525  0.005005  0.059685  0.103213  0.029646  \n",
       "2020-06-30  0.049558  0.004778  0.054166  0.144653  0.020191  \n",
       "2020-07-01  0.058089  0.005517  0.057467  0.115319  0.028759  \n",
       "\n",
       "[2009 rows x 10 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Delhi_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "id": "CHuDZDIMgfWZ"
   },
   "outputs": [],
   "source": [
    "val = 'AQI'\n",
    "final_data = pd.DataFrame(index=np.arange('2015-01-01','2020-07-02',dtype='datetime64[D]'), columns = [val])\n",
    "final_data[val] = Delhi_data[val]\n",
    "final_data=final_data.astype('float64')\n",
    "final_data[val] = final_data[val].fillna(final_data[val].mean(axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 406
    },
    "id": "lts5D4apgfWZ",
    "outputId": "91399dfd-7194-4305-972e-ce62dd9fe54d"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AQI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-01-01</th>\n",
       "      <td>342.290323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-01</th>\n",
       "      <td>327.928571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-01</th>\n",
       "      <td>256.064516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-01</th>\n",
       "      <td>305.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05-01</th>\n",
       "      <td>348.580645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-01</th>\n",
       "      <td>135.838710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-01</th>\n",
       "      <td>113.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-01</th>\n",
       "      <td>148.645161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-01</th>\n",
       "      <td>125.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-01</th>\n",
       "      <td>101.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>67 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   AQI\n",
       "2015-01-01  342.290323\n",
       "2015-02-01  327.928571\n",
       "2015-03-01  256.064516\n",
       "2015-04-01  305.266667\n",
       "2015-05-01  348.580645\n",
       "...                ...\n",
       "2020-03-01  135.838710\n",
       "2020-04-01  113.000000\n",
       "2020-05-01  148.645161\n",
       "2020-06-01  125.733333\n",
       "2020-07-01  101.000000\n",
       "\n",
       "[67 rows x 1 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seasonal_data = final_data\n",
    "seasonal_data = seasonal_data.resample(rule='MS').mean()\n",
    "seasonal_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 296
    },
    "id": "ZuP-CNKKgfWa",
    "outputId": "853c857c-755a-4ba8-fcee-c0993db3c6b2"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "Delhi_AQI = seasonal_data[val]\n",
    "result = seasonal_decompose(Delhi_AQI, model='multiplicative')\n",
    "result.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "uBPc7NB0gfWa",
    "outputId": "1897e1f4-77d1-4b6a-92b6-3709402a1f62"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pmdarima in c:\\users\\mimansha\\appdata\\roaming\\python\\python38\\site-packages (1.8.2)\n",
      "Requirement already satisfied: setuptools!=50.0.0,>=38.6.0 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pmdarima) (50.3.1.post20201107)\n",
      "Requirement already satisfied: Cython!=0.29.18,>=0.29 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pmdarima) (0.29.21)\n",
      "Requirement already satisfied: urllib3 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pmdarima) (1.25.11)\n",
      "Requirement already satisfied: joblib>=0.11 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pmdarima) (0.17.0)\n",
      "Requirement already satisfied: numpy~=1.19.0 in c:\\users\\mimansha\\appdata\\roaming\\python\\python38\\site-packages (from pmdarima) (1.19.5)\n",
      "Requirement already satisfied: statsmodels!=0.12.0,>=0.11 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pmdarima) (0.12.2)\n",
      "Requirement already satisfied: pandas>=0.19 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pmdarima) (1.1.3)\n",
      "Requirement already satisfied: scipy>=1.3.2 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pmdarima) (1.5.2)\n",
      "Requirement already satisfied: scikit-learn>=0.22 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pmdarima) (0.23.2)\n",
      "Requirement already satisfied: patsy>=0.5 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from statsmodels!=0.12.0,>=0.11->pmdarima) (0.5.1)\n",
      "Requirement already satisfied: pytz>=2017.2 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pandas>=0.19->pmdarima) (2020.1)\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from pandas>=0.19->pmdarima) (2.8.1)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from scikit-learn>=0.22->pmdarima) (2.1.0)\n",
      "Requirement already satisfied: six in c:\\users\\mimansha\\anaconda3\\lib\\site-packages (from patsy>=0.5->statsmodels!=0.12.0,>=0.11->pmdarima) (1.15.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install pmdarima\n",
    "import pmdarima as pm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "id": "QvN_comogfWa"
   },
   "outputs": [],
   "source": [
    "from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
    "from pmdarima import auto_arima;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "zMo_wzHpgfWb",
    "outputId": "21561ec9-6393-4b31-df30-b81d77513601"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ARIMA(order=(1, 0, 0), scoring_args={}, seasonal_order=(1, 0, 1, 12),\n",
       "      suppress_warnings=True)"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auto_arima(y=Delhi_AQI,start_p=0,start_P=0,start_q=0,start_Q=0,seasonal=True, m=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "id": "6AcxYRFZgfWb"
   },
   "outputs": [],
   "source": [
    "train = Delhi_AQI[:41] #from 2015-2018\n",
    "test = Delhi_AQI[42:54]# july 2018-june 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "_hjs5dWFgfWc",
    "outputId": "68191972-b7f2-4cdd-be1b-100758d75f29"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2018-07-01    112.419355\n",
       "2018-08-01    122.064516\n",
       "2018-09-01    121.933333\n",
       "2018-10-01    290.419355\n",
       "2018-11-01    367.066667\n",
       "2018-12-01    400.387097\n",
       "2019-01-01    365.741935\n",
       "2019-02-01    258.178571\n",
       "2019-03-01    197.354839\n",
       "2019-04-01    219.400000\n",
       "2019-05-01    235.838710\n",
       "2019-06-01    197.766667\n",
       "Freq: MS, Name: AQI, dtype: float64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 387
    },
    "id": "VoqeQMSXgfWc",
    "outputId": "bcc67c0a-645d-47ea-d8fb-4e19ac6f4bb8"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>                  <td>AQI</td>               <th>  No. Observations:  </th>    <td>41</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>SARIMAX(1, 0, 0)x(1, 0, [1], 12)</td> <th>  Log Likelihood     </th> <td>-223.005</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>                    <td>Tue, 08 Jun 2021</td>         <th>  AIC                </th>  <td>454.010</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                        <td>21:06:54</td>             <th>  BIC                </th>  <td>460.864</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>                     <td>01-01-2015</td>            <th>  HQIC               </th>  <td>456.506</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                           <td>- 05-01-2018</td>           <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>                <td>opg</td>               <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>        <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1</th>    <td>    0.8915</td> <td>    0.079</td> <td>   11.336</td> <td> 0.000</td> <td>    0.737</td> <td>    1.046</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.S.L12</th> <td>    0.9995</td> <td>    0.101</td> <td>    9.886</td> <td> 0.000</td> <td>    0.801</td> <td>    1.198</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.S.L12</th> <td>   -0.9437</td> <td>    5.834</td> <td>   -0.162</td> <td> 0.872</td> <td>  -12.379</td> <td>   10.491</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th>   <td> 1495.9050</td> <td> 8558.293</td> <td>    0.175</td> <td> 0.861</td> <td>-1.53e+04</td> <td> 1.83e+04</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>0.01</td> <th>  Jarque-Bera (JB):  </th> <td>0.62</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.94</td> <th>  Prob(JB):          </th> <td>0.74</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>0.74</td> <th>  Skew:              </th> <td>-0.23</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.57</td> <th>  Kurtosis:          </th> <td>3.39</td> \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                                      SARIMAX Results                                       \n",
       "============================================================================================\n",
       "Dep. Variable:                                  AQI   No. Observations:                   41\n",
       "Model:             SARIMAX(1, 0, 0)x(1, 0, [1], 12)   Log Likelihood                -223.005\n",
       "Date:                              Tue, 08 Jun 2021   AIC                            454.010\n",
       "Time:                                      21:06:54   BIC                            460.864\n",
       "Sample:                                  01-01-2015   HQIC                           456.506\n",
       "                                       - 05-01-2018                                         \n",
       "Covariance Type:                                opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "ar.L1          0.8915      0.079     11.336      0.000       0.737       1.046\n",
       "ar.S.L12       0.9995      0.101      9.886      0.000       0.801       1.198\n",
       "ma.S.L12      -0.9437      5.834     -0.162      0.872     -12.379      10.491\n",
       "sigma2      1495.9050   8558.293      0.175      0.861   -1.53e+04    1.83e+04\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                   0.01   Jarque-Bera (JB):                 0.62\n",
       "Prob(Q):                              0.94   Prob(JB):                         0.74\n",
       "Heteroskedasticity (H):               0.74   Skew:                            -0.23\n",
       "Prob(H) (two-sided):                  0.57   Kurtosis:                         3.39\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model=SARIMAX(train,order=(1,0,0),seasonal_order=(1,0,1,12),)\n",
    "results=model.fit()\n",
    "results.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "id": "xHAD1-B3gfWc"
   },
   "outputs": [],
   "source": [
    "predictions = results.predict(start=42, end=53, typ='levels').rename('Predictions')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 276
    },
    "id": "KD0KTJNXgfWd",
    "outputId": "b6259fcc-0ade-4916-90cf-418bf1b073cf"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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27GDZsmV8/fXX/PLLL06O1HVo8lfOcz4Wpt4FMx6BKi1g5HLrrN/VVY2AEUugQT+Y9zpMGmh1R1VOce7cOZYtW8ZXX311Kfl/8skn3HvvvbRo0QKA8uXL8/bbb/POO+84M1SXoo8wKueInAe/PgzxJ6HHf6DtI9aZdVHhXwZu/QbWfgOzn7eeCRgwDup0d3JgTjTreevJa0eq2BT6vJVlkV9//ZXevXtTr149goKCWLduHVu3bmXo0KFXlAsPD89yZi53U4T+21SxkHwBZv4LJt0C/kEwfCG0f6xoJf6LRCD8Phi+CEqUt97TnFessYdUoZk8eTKDBw8GYPDgwUyePNnhI3EWR3rmrwpP9Cb4aRic2AmtR0L318Db39lR5V+FhtZB7K8XYflH1gNpg762Bp1zJ9mcoReE2NhYFixYwJYtWxARUlNTERHuvvtu1qxZw0033XSp7Nq1awkPz9MwOMVSETzdUkXRht8/IXV8F0zCaWtqxT5vFY/Ef5G3P/QbA7dOtHoujbvemmBGFajp06dzzz33cODAAfbv38+hQ4eoWbMmvXv35ptvvrk0zn9sbCwvvfQSr7zyinMDdiGa/FWBizm0i/prXmdVSj2+bjYJ6mQ4B1Dx0Phm62ZwhYbw0wOw6H/OjqhYmzx5MgMGDLhi2S233MIPP/zApEmTGD58OPXr16dy5co89thj2Y6r7050SGdVsIxh+/t9qHZmHa9VncD0SHj/tuYMbBHq7MgKVmoy/Hgv7FkAT20D/7LOjqhAFJUhnT/55BPGjRvH4sWLKVu2aP4udEhnVaQcXD6Vhmf/4Z9qD/HmvX1oX6cc/5q+iaW7i/msWZ7e0Pl5SI63hoRQTjVq1Cg2b95cZBN/QdDkrwqMSThDyfkvsZPqtBr8Ij5eHnx2V0vqVAhgxKS1bDtyxtkhFqyKTa0hqFeNt64ElHIhmvxVgTn48yuUTY1lT+v/EljSurlb2s+bCfe1IsDXi/u+WcWRuGI+VHLbUXDmMGzXeQGUa9HkrwpEctQGQnd9yx8+vejRs98V6yoF+vPN/a2IT0zl3gmrOH2hGJ8V1+1lDQ/9z6fOjqTAuMJ9w+KuID5jTf7K8dJSiZs2ipMmgLI3/hdvz2v/zBpULM3nd7dk34nzPPTdGhJTUp0QaCHw8LCeaTi8Bg6tcnY0Dufn50dsbKweAAqQMYbY2Fj8/Pwcut9sH/ISET9gMeBrl59ujHlNRF4HHgRi7KIvGmNm2tu8ADwApAKPGWP+cmjUyqXF//MVwWe28Fm55xjRtE6m5drVKc87g5rzxNQNPPvjJj64PQwPj2L4VGbYnbDgv7DiU2tcoGIkNDSUqKgoYmJisi+s8szPz4/QUMf2kMvJE76JQFdjzDkR8QaWisgse90YY8wV46KKSCNgMNAYqAzME5F6xphiemqnrnD2GB4L3mB5WmO63Doq20fsb76uCkdOX+Dt2TupXMaf5/s0KKRAC5FvALS8x2r6iTsEZao6OyKH8fb2pmZNN3uSuZjIttnHWM7ZP3rbX1ld4/UHphhjEo0x+4BIoHid7qhMnfv9OTxSEvinwYs0qJSzYZlHdqrNXW2qMe7vPXz3z/6CDdBZIh6yvq/63LlxKGXLUZu/iHiKyAbgODDXGLPSXvWIiGwSka9F5GIH2irAoXSbR9nLVHG3ZyEBu37hS/pz9405H91SRHjjpiZ0bxjCazO2Mmfr0QIM0knKVIVGN8Hab635iZVyshwlf2NMqjEmDAgFIkSkCfAZUBsIA6KB9+ziGV3nX3OlICLDRWSNiKzR9sJiIDmBC78+wb60EDw6Pk2FUrm7OeXpIYy94zqahpbhsSnrWXfwVAEF6kRtRkHiadjwg7MjUSp3vX2MMXHAIqC3MeaYfVBIA77gctNOFJC+UTMUOJLBvsYbY8KNMeHBwcF5iV25kLSlY/A/u58PfUdwb8e8tdv7+3jy1dBwQkr7MWziGvafOO/gKJ2saiuoEg4rP9PZv5TTZZv8RSRYRMrYr/2B7sAOEamUrtgAYIv9egYwWER8RaQmUBcofn3c1GWxezBL3uO31HZ0ueF2/Lw987yr8gG+TLzPOo8YOmEVsecSHRWla2j7MJzcC7tmOzsS5eZycuZfCVgoIpuA1Vht/n8Ab4vIZnt5F+BJAGPMVmAasA2YDYzSnj7FmDGk/v4E8Wne/FLhYW5qXjnfu6xRviRfDg3n2JkE7p+4hgtJxejPp2F/KB1qdftUyoly0ttnkzHmOmNMM2NME2PMv+3ldxtjmtrLbzLGRKfbZrQxprYxpr4xZlbme1dF3ubpeO5fzP+Sb+fRm9o7bPakFtXK8tHg69gcFcejk9eRklpMmkk8vSDiQdi/xJrcRikn0Sd8Vd5dOEXq7OfZaGoT12gILasHOXT3PRtX5PWbGjNv+3Fe/31r8XmKtOVQ8C4BKz5zdiTKjWnyV3k3/z9I/EleTRnGc30aF0gV97StwYhOtZm04iDj/t5bIHUUOv+yEDYEtkyHs8ecHY1yU5r8Vd5ErcGs+ZoJKb1o06ELVYNKFFhV/+pVn5uaV+Z/s3fw6/rDBVZPoWo9AlKTYM1Xzo5EuSlN/ir3UlMwfzzBSY9yfONzJ6O6ZD5+jyN4eAjv3NqMNrWCeHb6RpZHFoOJYMrXgXq9YfVXkJzg7GiUG9Lkr3Jv1efI0c28lHAXD/VsTmk/7wKv0tfLk8/vDqdm+ZI89N1adhwtBhPBtHkY4k/A5mnOjkS5IU3+KndOR2EWjOYfz5bsKdeFwa0Kb5CyQH9vvrkvghK+ntw3YTXRp4v4RDA1O0JIE+vGb3G5ma2KDE3+KndmP09qairPxt/NS/0a4ZXBWP0FqXIZf765L4KzCSncN2E1ZxKK8EQwItBmJBzfBnsXOTsa5WY0+auc2zkbtv/Ox2kDqVW3MZ3rV3BKGA0rlWbcXS2JPH6OEd+tJSnFNZ8BOBB7nlPnk7Iu1GQQlAzWh75UodPkr3ImKR5mPstxv5p8ltibl/o2dGo4HeqW5+1BzVi+J5bnftrkMs8ARB4/y0fzd9P7g8V0emcR/cYuJepUfOYbePtBq2Gwew6c2F14gSq3p8lf5czf/4PTB3n87N0MiqhF/YqlnB0RA1uE8kzPevyy/jDvztnptDh2HTvLmLm76Dnmb7q/v5gx83ZRys+LZ3rW42xCMnd8sSLrierD7wdPH33oSxWqnMzkpdzdsW3wz8csDejN5rNNGNujnrMjumRUlzocjkvgk4V7qBToz11tqhd4ncYYdh47y8xN0czccpTI4+cQgVY1gnjjpsb0blKRkNLWkNYd6wUz5MuV3PHFCqYOb0vFwAyGug6oAE1vg42ToevLUMKxT0orlRFN/ipraWnw51Mke5fi0RM3M6p3HcoH+Do7qktEhP/0b8yxMwm8+tsWKpb2o3ujEIfXY4xhe/RZZm6OZuaWaPbGnMdDIKJmEEPbNqZXk4oZzmHQLLQM394fwd1frbIPAG2oUDqDA0CbkbBhEqybCB2edHj8Sl1NXKGtNDw83KxZs8bZYaiMrPsOZjzC+yUe56e0zsx/ulO+hmwuKPFJKQwev4Jdx84yZXhbwqqWyfc+jTFsPXLGSvibo9kfG4+HQNva5ejTpBK9GlckuFTODoRrD5zknq9WUTHQj8nD22Q82c3EG+FEJDyxCTwL/tkJVfSJyFpjTHiettXkrzJ1PhY+bkmMfy0ijjzJR3e05EYHDNlcUGLOJjLws2XEJ6by88PtqF6uZK73YYxh8+HTzNx8lFlbojkQG4+nh9DuUsIPoVwer3xW7TvJ0K9XEVrWn8nD21x7BbVzNky+HW75CpoOylMdyr1o8lcF49dRmE1TGOzxDslB9flpZDuHDdlcUPbGnOOWz5YT6O/NTyPb5ShRG2PYGHX60hl+1KkLeHkI7eqU54amFenRqCJBJX0cEt8/e2K575tVVA8qyeThba7cb1oafNIKfEvDgwus5wCUyoImf+V4+5fBN31ZVWUot+3pxc8Pt6NFtbLOjipH1h44yZ1frKRR5dL8MKwN/j7XNlMZY1h/KI6Zm6KZteUoh+Mu4O0ptK9Tnr5NK9GzUQhlSjgm4V9tWeQJ7v9mNbWCA/hhWGvKpj8ArPoCZj4D98+Baq0LpH5VfGjyV46VkgTjOpCSFE/4qf/SsVF1PrrjOmdHlSuztxxl5Pdr6d4whHF3tcTTQ0hLM6w/dIo/Nx1l9pZojpxOwMfTg+vrlqdP00r0aBhCYInCaWtfvCuGYd+uoW6FAH4Y1uZyvYnnYEwjqNUZbvu2UGJRRVd+kr/29lHX+mcsnNjJhNC3iD/py79613d2RLnWu0lFXuvXiNd/38a/pm+ilJ8Xs7cc5egZK+F3rBfMM73q071RSKEMTHe1jvWC+fzuljz07Vru/nol3z3QmkB/b/ANgJb3wvKxcOoAlC34rqvKPemZv7rSyX3waRviQrsQtuNuHu5cm3/1buDsqPLszZnbGb94Lz5eHnSuF8wNzSrRtUEFSjkh4Wdk/vZjjJi0lsaVA/nugQgrrtNR8EEzq/tnr9HODlG5MG32UY5hDHx/K+bgP4wI/JS1p0qw8JnOLpMo8yItzbDu4CkaVCpNgK9rXujO2XqUh79fR/OqZZh4f4QV54/3QeQ8eGob+Dr/aWrlmvKT/HV4B3XZtt8gci47GjzKX4e8eKpH/SKd+MGaCCa8RpDLJn6w5ir++M7r2HAojvsmrOJ8Ygq0HQWJZ2D9984OTxVTmvyVJeEMzH6etJCmPLw7nPohpbgtPNTZUbmN3k0q8eHgMNYeOMX936wmvkIYhEbAynGQlurs8FQxpMlfWRa+CWePMiP0WfadSuTlfg0Lfax+d9evWWXG3B7G6v0nGTZxDUnhD8GpfbBrtrNDU8WQ/ncrOLIBVn1OQvOhvLLWjy71g7m+brCzo3JL/cOq8O6tzflnbywPrqmMKR0K/+hY/8rxsk3+IuInIqtEZKOIbBWRN+zlQSIyV0R229/LptvmBRGJFJGdItKrIN+Ayqe0VPjjSShRnvfTBhOflMqLTh6r390NbBHK27c0Y/GeU0z16AsHlkL0RmeHpYqZnJz5JwJdjTHNgTCgt4i0AZ4H5htj6gLz7Z8RkUbAYKAx0Bv4VERcbyQwZVnzNRxZx9F2r/LV2lPcGVGNuiHau8TZbg2vyv8NaMqbR1uRIH6kLtezf+VY2SZ/Yzln/+htfxmgPzDRXj4RuNl+3R+YYoxJNMbsAyKBCEcGrRzk7FGY/2+o1ZkXd9WnhLcnT3Sv6+yolG1wRDWeG9CaKckdMZunkxx3xNkhqWIkR23+IuIpIhuA48BcY8xKIMQYEw1gf784oWsV4FC6zaPsZVfvc7iIrBGRNTExMfl4CyrP/noRUhJZ3fhlFuyM4ZGudfI8YqUqGENaVyew86N4mFTmThxNcqprzlesip4cJX9jTKoxJgwIBSJEpEkWxTMaivCaJ8mMMeONMeHGmPDgYL25WOgi58OWn0jr8CSvLLlA1SB/7m1fw9lRqQwM6N6RQ8GdaH3yN56dvJIUPQAoB8hVbx9jTBywCKst/5iIVAKwvx+3i0UBVdNtFgro9aorSb4Afz4NQbX50W8QO46e5YU+DfH10lszrqr6DU9TTs7iu/0nnpq2kdQ05z+Zr4q2nPT2CRaRMvZrf6A7sAOYAQy1iw0FfrNfzwAGi4iviNQE6gKrHBy3yo+lY+DUPi70eod35u8nvHpZ+jSp6OyoVFZqXA8hTXkucAEzNh7m2R/1AKDyJydn/pWAhSKyCViN1eb/B/AW0ENEdgM97J8xxmwFpgHbgNnAKGOMPqLoKk7stpJ/09v4eH8VTpxL4uV+jVx+kha3JwJtHyYofg8ftjrFz+sP89xPm0jTA4DKo2wHPDHGbAKuGczdGBMLdMtkm9GADkfoaoyBP58CL3+OtH6ZL8Zt4+awyg6Z71YVgia3wNzX6H/hN/Z1f5MP5u3Gy0N4c0BTPDz04K1yR5/wdSfRG2DfYujyAv9behIBni3CwzW7HS9faDUMIufyeLM0Hu1ahymrD/Hyb1twhdF5VdGiyd+dRM4DYHPZbvy24QjDO9aiShl/JwelciX8fvD0RVaO46ke9RjZuTY/rDzIazO26gFA5YrrjnOrHC9yPqZSc16bH0NwKV9GdKrt7IhUbgUEQ7PbYOMUpNur/KtXfVLTDOMX78XTQ3hV79+oHNIzf3dxIQ4OrSKydBvWHYzjmZ71KOnCY9yrLLQZCSkXYO0ERIQX+jTg/vY1mbBsP2/O3K5XACpH9L/fXez7G0wqY/ZVo0HFUgxqWTX7bZRrCmlsTfC+6gto+yji5cMr/RqSmpbGF0v24enhwXO96+sVgMqSnvm7i8h5pHgHMOdMVZ7qUQ9P7R1StLUZBWejrdnXABHh9ZsaM6R1Ncb9vYf35uxycoDK1WnydwfGQOQCtvm1wN/Pj871K2S/jXJtdbpDubqw4hPr94t1APhP/yYMblWVjxdGMm3NoWx2otyZJn93ELMTzkTxy9kG9GgUgo+X/tqLPA8PaDMCjqyHgyvSLRZGD2hK+zrleOXXLWw9ctqJQSpXplnAHdhdPP9KaELfJpWcHIxymOZ3gF8ZWHHlWP+eHsKHg6+jbAkfRk5ax+kLyc6JT7k0Tf7uIHIex3xrcMa3ItfXK+/saJSj+JSElvfCjj/g1P4rVpUP8OWTIddxJO4Cz/y4UXsAqWto8i/uks5jDizjr8QmdG9YQUfuLG4ihoN4wMrx16xqWT2IF/s2ZO62Y3y+eK8TglOuTJN/cbd/GZKaxJykpvRpqk0+xU5gFWh0M6z7FhLOXLP6vvY1uKFZJd6evYN/9sQWfnzKZWnyL+4i55Ekvmz1akSnejppTrHU5mFIOgsbvr9mlYjwv1uaUaN8SR6dvJ5jZxKcEKByRZr8izkTOY9VpjEdGlbFz1ubfIql0JZQtTWs+AzSrh09PcDXi3F3teR8YgqP/LBOp4JUgCb/4u3kXuTkHuYmN6WvTtZSvLV5GOIOwM6ZGa6uF1KKt25pyur9p3h79o5CDk65Ik3+xVnkfABWeYTpg13FXYN+EFjNOvvPRP+wKtzTtjpfLNnH7C3RhRicckWa/IsxEzmPKCpQs34z/H20yadY8/SC1sPhwDI4siHTYi/d0JDmVcvwzI+b2BtzrvDiUy5Hk39xlZJI2t7FLExpRt9mlZ0djSoMLe4Bn4BrHvpKz9fLk0+HtMDbUxg5aR3xSSmFGKByJZr8i6uDK/BMiWe5hNFFm3zcg18gXHcXbPkZzmTerFOljD8fDr6OXcfP8vIvOgtYbiUkpxJ9+gLbjpxheeQJ/tp6tEgeRHVI52LK7J5HCl541+mk4/a7k9YPwcrPYfWX0O2VTIt1rBfM493q8sG83bSsUZYhrasXYpCuISU1jdMXkjkVn0xcfBJx8cmcSvf9VHwypy8kcer85eVxF5JISL62t9QdEVX5v4HNnPAu8k6zQjF1YcdfbEitR7fmOluXWwmqBfX7wpqvof3j4Fc606KPda3L+oNxvDFjG02rBNIstEzhxelgxhgOx124lKhPXZXM4+xknv77mYTMz9Y9PYSyJbwpU8KHMv7ehJYtQdMq3pQt6UOgvzdlS/hcWv/bhsNMXX2Ioe1q0KBi5p+3q9HkXxydOUKJUztZyp2MbKBNPm6n49PwZQ/4dSTcPgkymdTFw0P44PYw+o1dyshJ6/jj0Q6ULelTyMHm3+n4ZJ6Yup6FO2MyXF/Kz+tSsg4s4UON8iUpW8KHMiW8KeNvJfQyF5O5vw9lSnpTytcrx5PhNKxUillbjjL6z+1890BrR761AqXJvxhK2z0PDyC+WmdK+Xk7OxxV2Kq0hJ7/gb9ehGUfQocnMi1atqQPnw5pwa3j/uHJaRv4emgrPIrQRD87j55l+HdrOBJ3gad71KNBpdKXz9jt5O7lWbC3NsuU8OGxbnX5zx/bWLTzeJHpVp3tpyIiVUVkoYhsF5GtIvK4vfx1ETksIhvsr77ptnlBRCJFZKeI9CrIN6CudXrzbI6ZMjRr0c7ZoShnafMwNB4A89+AfYuzLNq8ahleubERi3bG8PHCyEIKMP/+3BTNgE+XEZ+UypThbXi0W116NAohvEYQdSoEUD7At8AT/0V3t6lOjXIlGP3ndlKKyBPUOflkUoCnjTENgTbAKBFpZK8bY4wJs79mAtjrBgONgd7ApyKincwLS2oKfocWs8Q0p1sjfarXbYnATWOhXB2Yfj+cOZJl8btaV+PmsMqMmbeLJbszbj5xFalphv/N3sGoH9bRoGIp/ni0Ay2rBzk1Jh8vD57v05Ddx88xZXXRmEEt2+RvjIk2xqyzX58FtgNVstikPzDFGJNojNkHRAIRjghWZc8cXot/6lliQq4n0F+bfNyabymrzT/5AkwbCilJmRYVEd4c2JS6FQJ4fMoGjsRdKMRAcy4uPol7J6zis0V7uLN1NSYPb0NIaT9nhwVAr8YhRNQMYszcXZxNcP0JdHJ1TSQiNYDrgJX2okdEZJOIfC0iZe1lVYD0h74oMjhYiMhwEVkjImtiYlz7TKMoObb+T1KNUOm6Ps4ORbmC4PrQ/xOIWgVzXsqyaAkfLz67qyVJKWk8/P06klJcq/li25Ez3PjxUlbuPclbA5vy5oCmLjU/hYjw8g0NiT2fxKeL9jg7nGzlOPmLSADwE/CEMeYM8BlQGwgDooH3LhbNYPNrniIxxow3xoQbY8KDg3WoYUdJ2zWXjaYOncPqOTsU5Soa3wxtH4FV42HTtCyL1g4O4O1BzdhwKI43Z24vnPhyYMbGIwz8bBlJKWlMfagNgyOqOTukDDULLcPA66rw1dJ9HDoZ7+xwspSj5C8i3liJ/3tjzM8AxphjxphUY0wa8AWXm3aigKrpNg8Fsm5wVA5hzp+g4vnt7CvbljIlil6XPVWAur8O1drB74/Dsa1ZFu3btBIPdKjJN8v3M2Ojc/91U1LTeHPmdh6bvJ6mVQL5/dEOXFetbPYbOtEzverjIfDOXzudHUqWctLbR4CvgO3GmPfTLU8/LdQAYIv9egYwWER8RaQmUBdY5biQVWai1szEA0PpJr2dHYpyNZ7ecOs34Fsapt4FCaezLP58nwaEVy/L8z9tYvexs4UT41VOnk9i6IRVjF+8l3vaVuf7YW2oUMo12vezUrmMPw9eX4sZG4+w7uApZ4eTqZyc+bcH7ga6XtWt820R2Swim4AuwJMAxpitwDRgGzAbGGWMuXaGCeVwpzfP4qQJoGWbrs4ORbmiUiHWASDuIPz6MGQxpo+3pwcf39mCEj6ejJi0lnOJhTt2zZbDp7lx7FJr/oFBzfh3/yb4eBWdochGdKpNcClf/vvHNpcdOyknvX2WGmPEGNMsfbdOY8zdxpim9vKbjDHR6bYZbYypbYypb4yZVbBvQQGYtFQqxy5nR4lWBJXyd3Y4ylVVbws9/gM7/oBlH2RZtGKgHx/dcR37Tpzn+Z82FVoS+2V9FLd8tpw0Y/jxobbcFl41+41cTElfL57pWY91B+OYufmos8PJUNE5lKos7du6kiATB3W7OTsU5erajITGA2H+v2Hv31kWbVe7PM/0qs8fm6KZuHx/gYaVnJrGv3/fxpNTNxJWtQy/P9qB5lXLFGidBWlQy6o0qFiKt2ZvJyHZ9Ro/NPkXE4dX/w5A/fb9nRyJcnkXHwArX896AOz04SyLj+hYm+4NK/DfP7ez9kDBtGGfOJfI3V+t5Otl+7ivfQ0mDWtN+QDfAqmrsHh6CC/f0IhDJy8U+IEzLzT5FwPGGEof/pt93nUoF+KaXeCUi/ENgNu+g5QE+DHrB8A8PIT3bg2jUhk/HvlhHbHnEh0ayqaoOG4au5T1B+N4/7bmvHZjY7wLaViGfEu+APuXQWLGN8U71C1P1wYV+HhBpMM/t/wqIp+wysqeQ0dolLKDc6GdnB2KKkqC69kPgK22BoHLQmAJbz4b0pLY80k8PmUDqWmOaf+fvjaKQeP+QUT4aWQ7BrYIdch+C1RqMuyeCz8/BO/UhW/6wvguELMrw+Iv9m1AfHIqH87fXciBZk2TfzGwffkfeEsqoRE3OjsUVdQ0vhnaPQqrv4CNU7Ms2qRKIP/p35ilkSf4YF7GiS6nklPTeO23LTzz40bCq5dlxiPtaVIlMF/7LFBpadYZ/h9Pwnv14ftBsHMWNO4PN34EF07BF12tZVepU6EUd0ZU4/uVB4k87pxusxnRIZ2LAY+984mXEpSt18HZoaiiqNvrcHi99QBYSGOo2CTTore3qsbaA6cYuyCS66qVoWuDkFxXF3M2kVHfr2PV/pMM61CT5/s0KLTRN3PFGIjeAJunw9Zf4Mxh8PKH+n2g6SCo0x287PsSdbrBlCEweTB0fhE6Pgsel9/TE93r8uv6w7w5cwdf39vKOe/nKi74iavciDx2luaJa4kp39p6kEep3PL0gkFfW3MAT7sbLsRlWfzf/ZvQqFJpnpy6MddDGKw/eIobxy5l0+E4Phwcxsv9Grle4o/ZCQtGw9iWML6zNS1mxaYw8Et4NhJunQANbric+AECQ+H+2dBsMCx60/oc090HKBfgyyNd67Bgx3GW7j5R+O8pAy72qavcWrHqH0LlBGWa9c2+sFKZKRUCt020HwAbaTVzZMLP25PP7mpBmjE8/P26HHdjnLr6ILd/vgIvT6t9v39YVoMDF7K4g7B0DHzWAT6JgMXvQGAVq0nnmV1w51Rodqt1ozwz3v4wYBz0fstq/vmyO8ReHuBtaLsahJb1579/bnPYPZP80ORfxJ3f9hcAgU10zhyVT9XaQM/RsHMmLBuTZdHq5Ury3q3N2Xz4NP/+Y1uWZZNS0njpl80899NmWtcK4vdHOtC4sgu07587DivHw1c94YOmMO9162y+91vw9A4Y+ju0HAolcjFXgIj1HMXdv1j7H9/FujmMddB8vk8Ddhw9y/S1zh/zX9v8i7B9J87T8NxK4krVpEzZ6s4ORxUHrR+yev8s+K81HWStzpkW7dm4IiM61Wbc33toWa0st7S8tqfO8TMJjPx+HWsPnOKhTrV4tmd95zbzXIiD7b/Dlp9g399g0qBCY+j2qvXgW1BNx9RTqxMMX2TdB/j+Vmv/HZ7khqaV+LraPt6ds4t+zSpT0td5KVjP/IuwvzbsI8JjB171ezg7FFVciMCNH6Z7ACwqy+LP9KxHm1pBvPTrZrZHn7li3doDp+g3dinbjpzh4zuv44U+DZ2T+JPirWQ/+U54ty7MeARO7YMOT8HDK+Dh5XD9045L/BeVrQ4PzIEmA63pNH+8F0k6z8v9GhFzNpHP/3bumP+a/IuwIxvn4SfJBDTWJh/lQL4B1gxgKUkw7R5IyfzhJC9PD8be0YLSft6MnLSWM/YMVj+sPMjg8f/g5+3JL6Pa0a9Z5cKK3pKSBDtnw0/D4B17Kssj66DVg/DgAnhsA3R7BSo0LNg4fErALV9Bj3/D9hnwVU9aBMRxY/PKjF+yl+jTzpsxTVxhxLnw8HCzZs0aZ4dRpByMjWfemPu4x2chXi8csG42KeVI22ZYvVbCH4B+72dZdNW+k9zxxQq6NahAuQAfJq86RMd6wXw0OKzw5pZIS4X9S2HLdCv2hDjwLwuN+kOTQVC9HXg4ceavyPnWQQg43nscHaZDv2aVeP+2sDzvUkTWGmPC87KttvkXUbO2RNPdYyPJVdvhpYlfFYRGN0G7x2D5RxDaCsLuyLRoRM0gXujTgP/+ac3+9XDn2jzdsz6eHhlN7Odg509Y3THXfQvnjoJPgNUVs8kg656Fl4tMbFSnGwxfCFOGUOG3O/m81ijuW9eGe9vVoFlomUIPR5N/EbVmw3oe8oiGho87OxRVnHV7DY6shz+esB7+qtg006IPdKhJYkoa9UJK0aNR7h/+yrVT+2H5x7B+EqRcgHq9oflgqNvLam5xRUG14IG58OtIumwfy2f+63n7j5J891BnrHmzCo8m/yIo6lQ8FY4vA2+spwyVKigXHwD7vCNMvdvqweJfJsOiIsKoLnUKPqajm2HZh7DlZxAPaH47tHvcGquoKPANgNu+hSXv0XvBf6l25BCLV0+gU0TLQg1Db/gWQbO3HKWTx0ZSSleFcoXwz6bcW0AFuHUinD4Ev4zI8gGwAmMM7FsCk26BcR2sh6jajIQnNlmD0xWVxH+RCHR8hrTBk6nucYLmM28mOTLruRUcTZN/ETRn00E6eG7Dq14P649IqYJWrTX0ehN2zYKl7xVevWlpVr/8L7vBxH4QvRG6vgJPboFeo6F0IfcicjDPBn3YcsMvxKSVwvP7AbBiXJbTazqSNvsUMUfiLuBxeDUlfC5ok48qXBHD4dAqa9ybKi2hdgHOFZ2SCJumwrKPIHY3lK0BN7wHYUOKXc+21uERDN/wMXccfpOus5+zDnD9xoB3wU5Wr2f+RczFJh/j4QU1Ozo7HOVOROCmj6y+8dMfgLgCGKIg4YzVnv9hc5jxqJXoB30Nj6yFVsOKXeIH617J0zeG82Di4yyqNAw2/gATemf7gF1+afIvYmZtiaanzxakWlvwLeXscJS78SlpzQCWlpLtA2C5cvaYNbbOmCYw91XrCeO7f4GHFkOTW6wbz8VYg4qlua1VDYYd6Maxvl/Did3WiKIHlhdYnZr8i5BjZxI4eGAvtdP2WX2GlXKG8nXg5k+tJ2ZnPZe/fcXugd+fsAZWW/oB1O4MDy6EoTOsZiU3uqf1VI96+Hp58OrO6jBsPviWhok3wuovC+Q+gCb/ImT2lqNc77HJ+kHb+5UzNbwR2j8OayfAhh9yv/2R9TBtKHwcDhu+tx4ge3St1QWySgvHx1sEBJfy5eEudfhr6zFWnAu2hqGo3RX+fBp+f8xxV1m2bJO/iFQVkYUisl1EtorI4/byIBGZKyK77e9l023zgohEishOEdGBZxxk5uZobvDfBgEhEJL5bEtKFYqur0KN662pDaM3ZV/eGNizECbeZDVp7FlgPUH8xGZrMLlytQs8ZFf3QIeaVA70479/biPNNxDumALXP2M9vfzNDXAm2mF15eTMPwV42hjTEGgDjBKRRsDzwHxjTF1gvv0z9rrBQGOgN/CpiDhxQI3iIeZsImv2n6AtG62zfje6HFYuytMLBk0A/yCYepc1j21G0lKtB7LGd4LvboaYHdD9Dau7Zo83oFTFQg3blfl5e/Kv3g3YcvgMv244bI1F1O0V6zmLY9usz/DQKofUlW3yN8ZEG2PW2a/PAtuBKkB/YKJdbCJws/26PzDFGJNojNkHRAIRDonWjf219SjN2INfyhlt71euIyDYmgHszBH4+aErHwBLToDVX1nTIU6/DxLPWTNjPbEZOjxhTRuprnFT88o0Dw3k7dk7uZBkz5LW+GYYNtfq7TShL6ydmOU+ciJXbf4iUgO4DlgJhBhjosE6QAAV7GJVgPR9wKLsZVfva7iIrBGRNTExMXkI3b3M3BzNzaW2YxCo1cXZ4Sh1WdUI6P1/sPsvWPKeNWHKkvesm7h/PmWNrHnbt/DIamtmrPRz36preHgIL/drxNEzCXyxZO/lFSGNrZvhNa+37gH88VS+6slx/ykRCQB+Ap4wxpzJYhCijFZcc6vaGDMeGA/WkM45jcMdxZ5LZMXeWN4ttwUJbpm7aeWUKgythlnNEQtHW/30k85C7W7WGX6N67WZMpda1QiiT5OKjPt7D4NbVaVCafuBrxJBMGS6NTnMsg/zVUeOzvxFxBsr8X9vjPnZXnxMRCrZ6ysBx+3lUUDVdJuHAkfyFaWbm7PtGKXNWSqd36a9fJRrEoEbP7B6p9TrafXPv/tn60FETfx58nyfBiSnpvHenF1XrvDwtCaHueWrfO0/J719BPgK2G6MST+jwwxgqP16KPBbuuWDRcRXRGoCdQHH3KFwUzM3RzMgcDdi0jT5K9flU9JK+IO+hkrNnR1NkVe9XEnubVeDaWsPse3ImWsLNB2Ur/3n5My/PXA30FVENthffYG3gB4ishvoYf+MMWYrMA3YBswGRhljUvMVpRs7dT6J5XtiGVh6O/iVcds+0Eq5o0e61qWMvzejZ27D0bMuZtvmb4xZSsbt+AAZdjsxxowGRucjLmWbu+0YqWlpNDi3yrqkduY0dEqpQhXo783j3ery+u/bWLjzOF0bOG6SHH3C18XN3BJN5zLH8L4Qo00+SrmhIW2qU6t8SUb/uZ3kVMfNpaDJ34Wdjk9mWeQJhpaPtBZo/36l3I63pwcv9m3InpjzTF510GH71eTvwuZuP0ZyqiE8dR2ENNUnIZVyU90aVqBtrXJ8MG83py8kO2Sfmvxd2KzN0dQNhIBja/SsXyk3JiK8dENDTsUn8enCSIfsU5O/izqTkMyS3Sd4MPQQkpai7f1KubkmVQIZ1CKUCcv2c+hkfL73p8nfRS3Yfpyk1DS6eG0CnwCo2trZISmlnOyZXvXx9BDemr0j3/vS5O+i/twcTcVSvpQ/tgRqdgIvH2eHpJRyspDSfjzUqRZ/bopm7YGT+dqXJn8XdC4xhb93xTCkbhISd1Db+5VSlwzvWIuQ0r7854/t+dqPJn8XtGDHcZJS0ugfYP9yNfkrpWwlfLx4pmd9NhyKy9d+NPm7oFmbo6lQypeqscuhXF0oW8PZISmlXMgtLUJpXLl0vvahyd/FxCelsHDncfo1KoscWKq9fJRS1/DwEP7dP39TuWrydzELd8SQkJzGoPIHISVBk79SKkMtq5fNvlAWNPm7mJlboikf4EODcyvByw9qtHd2SEqpYkiTvwu5kJTKwh3H6dW4Ih575kP19tacnUop5WCa/F3I37uOE5+UyoCaaXBilzb5KKUKjCZ/FzJz81GCSvpwXfJaa4Emf6VUAdHk7yISklOZv/0YvRqH4LlnPgRWhfJ1nR2WUqqY0uTvIpbsPsH5pFT6NioPe/+2HuzSia+VUgVEk7+LmLk5mkB/b9r67IGks9rko5QqUJr8XUBiSirzth2jZ6MQvPYuAA8vqNnR2WEppYoxTf4uYFnkCc4mptC3WSWInGcN3+wX6OywlFLFmCZ/FzBz81FK+XnRPiQVjm7SgdyUUgVOk7+TJaWkMWfrUXo0CsFn/yJrobb3K6UKWLbJX0S+FpHjIrIl3bLXReSwiGywv/qmW/eCiESKyE4R6VVQgRcXy/ec4ExCCn2b2E0+JStYk7UrpVQBysmZ/zdA7wyWjzHGhNlfMwFEpBEwGGhsb/OpiHg6KtjiaNbmowT4enF9nbKwZ4HV5OOhF2RKqYKVbZYxxiwGcjpfWH9gijEm0RizD4gEIvIRX7GWnJrGX9uO0r1hBXyPb4YLJ7XJRylVKPJzivmIiGyym4Uuji1aBTiUrkyUvUxlYMXeWOLik+nT1G7yQaBWF2eHpZRyA3lN/p8BtYEwIBp4z16e0SOpJqMdiMhwEVkjImtiYmLyGEbRNnPzUUr6eNKpXrCV/Ku0gJLlnB2WUsoN5Cn5G2OOGWNSjTFpwBdcbtqJAqqmKxoKHMlkH+ONMeHGmPDg4OC8hFGkpaRavXy6NgzBL/k0HF6jTT5KqUKTp+QvIpXS/TgAuNgTaAYwWER8RaQmUBdYlb8Qi6dV+04Sez6Jvk0qwt5FYNI0+SulCo1XdgVEZDLQGSgvIlHAa0BnEQnDatLZDzwEYIzZKiLTgG1ACjDKGJNaIJEXcTO3ROPv7Unn+hVg5nzwKwOVWzg7LKWUm8g2+Rtj7shg8VdZlB8NjM5PUMVdapph9pZjdG1QAX9vD9gzH2p3Ac9sfx1KKeUQ2qHcCdbsP8mJc4n0aVoRjm+Ds9Ha5KOUKlSa/AvZjqNnePnXLfh7e9KlfgW7iydQW8fzUUoVHm1nKCTGGCYu38+bs3ZQ2s+b8fe0pKSvl5X8Q5pA6UrZ70QppRxEk38hOHEukWd/3MjCnTF0qR/MO7c2p3yALySegwP/QNuHnR2iUsrNaPIvYH/viuHpaRs5k5DM6zc2Ymi7GsjF6Rn3L4G0ZG3vV0oVOk3+BSQxJZV3Zu/ky6X7qBcSwKRhETSoWPrKQpHzwLskVG3jnCCVUm5Lk38BiDx+lscmb2Bb9BnuaVudF/s2xM/7qsFNjYHdc63pGr18nBOoUsptafJ3IGMMP6w6yH/+2Ia/tydf3hNO90YhGRc+uRfiDkC7Rws3SKWUQpO/w5w6n8TzP2/ir63H6FCnPO/d1pyQ0n6Zb3Cxi6e29yulnECTvwMsjzzBU9M2Ens+kZf6NuSBDjXx8MhogNN0IudBUG0Iqlk4QSqlVDqa/PMhOTWN9+fuYtzfe6hZriRfDm1PkyqBOdgwAfYtgRb3FHyQSimVAfdN/qkpELsbks7bC8SejcA+Yxexl0m69XJp/eG4BN6avYOdx87xaJNKjOxcHn+foxBz9Jqyl/Zx8XvUWki5oE0+SimncY/kn5YKsZFwZL31dXgdHN1sJeA8qgKMBfAFdttfueHlBzXa57l+pZTKj+KX/I2xetJcTPRH1kP0Rkg6Z633LgmVmkP4/VA5DPzLWttg7O9k8tpwPimVH1bsZ+2BU9StEMB97asTVMI7k+24vN/0ry+uL1cbfEoW3OeglFJZKNrJ3xiIO3hVot8ACaet9V5+ULEphN0Jla+zvsrXAw/PLHebkdX7T/LEbxs4eqYeT/Wox4hOtfHM7qauUkq5qKKT/I2xhj5On+iPrIf4WGu9hzeENIbGA625cCtfB8ENwNM7X9WmpKbx0YJIPl6wm9CyJZg+oi3XVSub/YZKKeXCXDf5nzsORzbAkXWXE/25Y9Y68YQKDaF+38tn9CGNwcvXoSEcOhnPE1M3sPbAKQa2qMIbNzWmlF/+DiZKKeUKXCP5p6VA5Px0Z/Qb4EyUvVIguD7U7pou0TcBnxIFGtJvGw7z8i/W1MQfDg6jf1iVAq1PKaUKk2sk/6ObYdJA63VQbajWxkryVVpYbfa+pQotlHOJKbz62xZ+XneYltXL8sHtYVQNKtgDjVJKFTbXSP6lK8M9k6xeOP5lnBbGhkNxPDZ5PVGn4nm8W10e7VoHL0+d7EwpVfy4RvIPCIFanZxWfWqaYdzfexgzdxchpf2Y+lBbWtUIclo8SilV0Fwj+TvRkbgLPDl1Ayv3naRfs0qMHtCUQH+9qauUKt7cNvmfS0xhztajvPH7NpJT03j31ubc0qLK5Vm2lFKqGMs2+YvI10A/4Lgxpom9LAiYCtQA9gO3GWNO2eteAB4AUoHHjDF/FUjkuZSQnMq6g6dYHhnL8j0n2Bh1mtQ0Q7PQQD4cfB01y+vTtkop95GTM/9vgI+Bb9Mtex6Yb4x5S0Set39+TkQaAYOBxkBlYJ6I1DPGpDo27OylpKax6fBp/tljJfs1+0+RmJKGp4fQLDSQEZ1q0a52eVrXDNKbukopt5Nt8jfGLBaRGlct7g90tl9PBBYBz9nLpxhjEoF9IhIJRAD/OCjeTKWlGXYeO8vyPbEsjzzByn0nOZeYAkCDiqUY0ro67euUo1XNIErrg1pKKTeX1zb/EGNMNIAxJlpEKtjLqwAr0pWLspc5nDGGA7HxLNtzguV7YlmxJ5bY80kA1ChXgpvCKtOudjna1ipHuQDHPvmrlFJFnaNv+GZ0t9RksAwRGQ4MB6hWrVqOdn70dALL7WT/z55YDsdZQzKHlPalU71g2tYuR7s65alSxj9v0SullJvIa/I/JiKV7LP+SsBxe3kUUDVduVDgSEY7MMaMB8YDhIeHZ3iAOHU+iRV7Yy+d3e+NsSZeKVPCm7a1yjGic23a1S5HrfIltZeOUkrlQl6T/wxgKPCW/f23dMt/EJH3sW741gVW5XSn5xNTWLX/JMsjrWS/LfoMxkAJH09a1wzijlbVaFu7HI0qlc5+jlyllFKZyklXz8lYN3fLi0gU8BpW0p8mIg8AB4FbAYwxW0VkGrANSAFG5aSnz7EzCQz6bDkbDsWRkmbw8fSgRfUyPNm9Hu3rlKNZaBm8tUeOUko5jBiTYYtLofKtVNf0fvkb2tcuR7va5WlZvSz+PrmfcEUppdyJiKw1xoTnZVuXeMK3UaXS/DZK57NVSqnC4hJtKTodolJKFS6XSP5KKaUKlyZ/pZRyQ5r8lVLKDWnyV0opN6TJXyml3JAmf6WUckOa/JVSyg25xBO+InIa2O2k6gOB025UrzPrdsf3XB444YR63fGzdsf3XNcYE5inLY0xTv8Cxrtb3fqe3aNuYI07vV8nf9b6nnPx5SrNPr+7Yd36nt2nbmdwx89a33MuuESzj1LFlYisMXkceEupguQqZ/5KFVfjnR2AUhnRM3+llHJDTjnzF5Fz2axfJCIOuVQWkQEiYkSkgSP2l8u6XxKRrSKySUQ2iEjrQqw7VER+E5HdIrJHRD4UEZ8syj8hIiXyUZ8RkffS/fyMiLye1/3lsu5U+/PdKiIbReQpESn2V7Xp3vfFrxpZlHXI/5T9e/4u3c9eIhIjIn/kd9+5iKHQ/qdd4f3a9WaZM/Oi2P+DAHcAS4HBhVmpiLQF+gEtjDHNgO7AoUKqW4CfgV+NMXWBekAAMDqLzZ4A8pz8gURgoIiUz8c+8uqCMSbMGNMY6AH0xZpxrri7+L4vfu0vhDrPA01ExN/+uQdwODc7EJH8ziOSp/9pEcnLDFH5fr+uymnJX0Q6pz96isjHInKvg+sIANoDD2D/oWRVr4j0FZEdIrJURD7K59G9EnDCGJMIYIw5YYw5IiItReRvEVkrIn+JSCW77kUi8oGILBeRLSISkY+6uwIJxpgJdt2pwJPA/SJSUkTeFZHN9hXJoyLyGNacywtFZGEe60zBat9+8uoVIlJdRObb9c0XkWoiEigi+y+eoYtICRE5JCLeeawfAGPMcWA48IhYPEXkHRFZbdf/ULq4/mV/DhtF5K381FsQZ2Z5kdnfl+0uB/19zQJusF/fAUxOV3+EXcd6+3t9e/m9IvKjiPwOzMlrxVn8Ty8WkV9EZJuIjEv3d3VORP4tIiuBtnmsNi/vd4mIhKUrt0xEmuWx/ov7yCp37ReRN0Rknf03ne1VUXE/878ZmG2M2QWcFJEWmRUUET/gc6CPMaYDEJzPuucAVUVkl4h8KiKd7MQ2FhhkjGkJfM2VZ+MljTHtgIftdXnVGFibfoEx5gzWfMvDgJrAdfYVyffGmI+AI0AXY0yXfNT7CTBERK5+6ORj4NuL9QEfGWNOAxuBTnaZG4G/jDHJ+agfAGPMXqy/7QpYSeK0MaYV0Ap4UERqikgfrL+P1saY5sDb+a3XCfzlcpPPL4X49zUFGGz/zzQDVqZbtwPoaIy5DngVeDPdurbAUGNM13zUfTMZ/09HAE8DTYHawEB7eUlgizGmtTFmaR7rzMv7/RK4F0BE6gG+xphNeaw/p04YY1oAnwHPZFe4uCf/O7B+cdjf78iibANgrzFmn/3z5CzKZssYcw5oiXUWGgNMBR4CmgBzRWQD8DIQmm6zyfa2i4HSIlImj9ULkNGdfAE6AuOMMSl2XSfzWMc17APMt8BjV61qC/xgv/4O6GC/ngrcbr8ebP/sKBenh+sJ3GN/3iuBckBdrGa4CcaYeDv2fH8OIhJgX9lcPPvqby+vISLbReQLse5LzJHLzQj5kb7ZZwBQn0L4+7KTWA2s/6eZV60OBH4UkS3AGKwTkYvmOuBzzux/epUxZq99lTuZy39jqcBP+akwj+/3R6CffUC+H/gmPzHk0M/297VY8WbJmXP4pnDlwcfPkTsXkXJYzR9NRMQAnlgJcUYm9Tp8Lkn7D3ERsEhENgOjgK3GmMwuP69O2HntirUVuCX9AhEpDVQF9uZjvznxAbAOmJBFmYv1zwD+T0SCsA6UCxwRgIjUwvqnP471e33UGPPXVWV64/jPIQEYYIw5I9a9jxUiMsNeVxe4wxjzoIhMw/r9THJw/ULh/H2B9bt7F+iMdUC96D/AQmPMALFuQC9Kt+58PurL6n96Jpm/twT7/zC/cvV+jTHxIjIX6A/cBjiiA0t2OTPR/p5KDnK7M8/8DwCNRMTXbibo5uD9D8JqaqhujKlhjKkKXDyrz6jeHUAtudxj4nbyQUTqi0jddIvCgO1AsFg3gxERbxFJf2Z0u728A1ZTRV7HCpkPlBCRe+z9eQLvYZ19zAFGiH3TzU68AGeBUnms7xL7zG4aVnPLRcu5fHNuCNbNuotXR6uAD4E/HPFPKiLBwDjgY2P1Y/4LGGmfgSEi9USkJNbncL/YPZzSfQ75qh54U0Q2AfOAKkCIvW6fMWaD/TpHZ2Z5sJPC+fsCq9no38aYzVctD+TyDdF787H/jGT2P90BiLCb8zyw3mdem3gyk5f3+yXwEbDaQVfYDs2ZhX7mbyedRGPMIfsMaBPWoG7rHVzVHcDVN/F+Au7ESk5X1GuMuSAiDwOzReQEVlLKjwBgrH1pnQJEYjUBjQc+sn95XlhnylvtbU6JyHKgNNalYp4YY4yIDAA+FZFXsA7yM4EXsc4K6gGbRCQZ+AKrTX48MEtEovPZ7g/WgeaRdD8/BnwtIs9iNYHdl27dVKxL5M75qM/fbubwxvqsvwPet9d9iZVo14mI2PXfbIyZbd+QWyMiSVz+fPJjCNa9opbGmGQR2c/ls7PEdOVSAUc0+1zBGJMkIoMo4L8vu64orIP21d4GJorIUzjoSi6dzP6nRwL/2OuaAouBXxxZcV7erzFmrYicIeur4GwVVM4s9Ie8RKQ58IUxJj+9DQqEiAQYY87ZSeITYLcxZkwh1b0IeMYYs6Yw6lOOJVZvn5eAOsaYR0WkC1YyqGkX+cMY08Qu+wwQYIx53SnBFjMi0hnrf6efk0O5gohUxmoGamCMScvHfgokZxZqs4+IjMC6GfNyYdabCw/aZ5BbsS7nPnduOKoouHhmhtWTKVxE1mBdBexwamDKaewm15XAS/lM/AWWM3V4B6XyyZWvZpXKTHHv6qlUgSoCV7NKZUjP/JVSyg3pmb9SuSAiVUVkof3Q1lYRedxeHiQic8UaSG+uiJS1l5ezy58TkY+v2tftYg05sVVEiuITxqoI0+SvVO6kAE8bYxoCbYBRItIIeB6Ybw+kN9/+GawHv17hqsft7QeW3gG62QPShYiIo591USpTmvyVygVjTLQxZp39+izWg3tVsJ7knGgXm4g1Bg3GmPP2mDIJV+2qFrDLGBNj/zyPq57KVqogafJXKo/sp8Gvw+rSF2KMiQbrAIE1qFxWIoEG9rg/XlgHi6oFF61SV9Lkr1QeiDW08E/AE/aAdrlijDmF9WTqVGAJsB+rSUmpQqHJX6lcsscJ+glrOOyLIykek8tzM1TCGlQuS8aY3+2hhttijcuzu6BiVupqmvyVygV76I+vgO3GmPfTrZoBDLVfDwV+y8G+Ktjfy2KNsf+lY6NVKnPaz1+pXLBHxFwCbAYuPrb/Ila7/zSgGtakObdeHMnRHuCtNOADxAE9jTHbRGQy0Nzex7+NMRfHqVeqwGnyV0opN6TNPkop5YY0+SullBvS5K+UUm5Ik79SSrkhTf5KKeWGNPkrpZQb0uSvlFJuSJO/Ukq5of8HuIQhpHIE4aoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "predictions.plot(legend=True)\n",
    "test.plot(legend=True,title=\"Delhi Prediction data\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "56oSayvNgfWd",
    "outputId": "825de3f2-1dc4-47ac-fa82-ec0a01771c5b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Root Mean Squared Error:  33.481045609363534\n",
      "Mean AQI: 240.71425371223765\n",
      "Bias: 5.343937\n",
      "MSE: 1120.9804150962814\n",
      "MAE: 26.155436064942666\n",
      "RMSE: 33.481045609363534\n",
      "MAPE: 0.11530528492842286\n",
      "r2score: 0.8762677450758353\n",
      "explainedVariance_score: 0.8794199004816929\n",
      "me: 86.9858909017222\n",
      "mpd: 4.1680077450658075\n",
      "mgd: 0.018491245211032587\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score, explained_variance_score, max_error,mean_poisson_deviance,mean_gamma_deviance\n",
    "import math\n",
    "RMSE=np.sqrt(mean_squared_error(predictions,test))\n",
    "print('Root Mean Squared Error: ', RMSE)\n",
    "print('Mean AQI:',test.mean())\n",
    "forecast_errors = [test[i]-predictions[i] for i in range(len(test))]\n",
    "bias = sum(forecast_errors) * 1.0/len(test)\n",
    "print('Bias: %f' % bias)\n",
    "mse = mean_squared_error(test, predictions)\n",
    "print('MSE: '+str(mse))\n",
    "mae = mean_absolute_error(test, predictions)\n",
    "print('MAE: '+str(mae))\n",
    "rmse = math.sqrt(mean_squared_error(test, predictions))\n",
    "print('RMSE: '+str(rmse))\n",
    "mape = np.mean(np.abs(predictions - test)/np.abs(test))\n",
    "print('MAPE: '+str(mape))\n",
    "r2score=r2_score(test, predictions)\n",
    "print('r2score: '+str(r2score))\n",
    "explainedVariance_score=explained_variance_score(test, predictions)\n",
    "print('explainedVariance_score: '+str(explainedVariance_score))\n",
    "me=max_error(test, predictions)\n",
    "print('me: '+str(me))\n",
    "mpd=mean_poisson_deviance(test, predictions)\n",
    "print('mpd: '+str(mpd))\n",
    "mgd=mean_gamma_deviance(test, predictions)\n",
    "print('mgd: '+str(mgd))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 483
    },
    "id": "ozaIOkyCgfWe",
    "outputId": "35b9806c-371a-4e38-98ed-265243f6b449"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Forming the model:\n",
    "final_model = SARIMAX(train,order=(1,0,0),seasonal_order=(1,0,1,12))\n",
    "results = final_model.fit()\n",
    "#Obtaining predicted values:\n",
    "predictions = results.predict(start=64, end=77, typ='levels').rename('Predictions')\n",
    "#Plotting predicted values against the true values:\n",
    "predictions.plot(legend=True)\n",
    "Delhi_AQI.plot(legend=True,figsize=(12,8),grid=True,title=\"Delhi AQI\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_anova = pd.read_csv('newCityData.csv')\n",
    "df_anova = df_anova[['AQI','City']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p-value for significance is:  2.3993548794919526e-203\n",
      "We reject the null hypothesis\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "Citys = pd.unique(df_anova.City.values)\n",
    "d_data = {city:df_anova['AQI'][df_anova.City == city] for city in Citys}\n",
    " \n",
    "F, p = stats.f_oneway(d_data['Mumbai'], d_data['Shillong'], d_data['Lucknow'])\n",
    "\n",
    "print(\"p-value for significance is: \", p)\n",
    "\n",
    "if p<0.05:\n",
    "    print(\"We reject the null hypothesis\")\n",
    "else:\n",
    "    print(\"We accept the null hypothesis\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p-value for significance is:  2.189526810141999e-282\n",
      "We reject the null hypothesis\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "Citys = pd.unique(df_anova.City.values)\n",
    "d_data = {city:df_anova['AQI'][df_anova.City == city] for city in Citys}\n",
    " \n",
    "F, p = stats.f_oneway(d_data['Delhi'], d_data['Visakhapatnam'])\n",
    "\n",
    "print(\"p-value for significance is: \", p)\n",
    "\n",
    "if p<0.05:\n",
    "    print(\"We reject the null hypothesis\")\n",
    "else:\n",
    "    print(\"We accept the null hypothesis\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p-value for significance is:  1.3185248240573501e-39\n",
      "We reject the null hypothesis\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "Citys = pd.unique(df_anova.City.values)\n",
    "d_data = {city:df_anova['AQI'][df_anova.City == city] for city in Citys}\n",
    " \n",
    "F, p = stats.f_oneway(d_data['Patna'], d_data['Bhopal'])\n",
    "\n",
    "print(\"p-value for significance is: \", p)\n",
    "\n",
    "if p<0.05:\n",
    "    print(\"We reject the null hypothesis\")\n",
    "else:\n",
    "    print(\"We accept the null hypothesis\")"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "name": "test1 (2).ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
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 },
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}