SDG_test_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "1eb0d4c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "sns.set(rc={'figure.figsize':(11.7,8.27)})\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4ba27328",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>State/UT</th>\n",
       "      <th>SDG 6</th>\n",
       "      <th>SDG 3</th>\n",
       "      <th>Unnamed: 4</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "      <th>Unnamed: 6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>State</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>92.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>State</td>\n",
       "      <td>Arunachal Pradesh</td>\n",
       "      <td>67.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>State</td>\n",
       "      <td>Assam</td>\n",
       "      <td>64.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>State</td>\n",
       "      <td>Bihar</td>\n",
       "      <td>91.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>State</td>\n",
       "      <td>Chhattisgarh</td>\n",
       "      <td>89.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>State</td>\n",
       "      <td>Goa</td>\n",
       "      <td>100.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>State</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>93.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>State</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>80.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>State</td>\n",
       "      <td>Himachal Pradesh</td>\n",
       "      <td>85.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>State</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>83.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>State</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>85.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>State</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>89.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>State</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>88.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>State</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>90.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>State</td>\n",
       "      <td>Manipur</td>\n",
       "      <td>87.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>State</td>\n",
       "      <td>Meghalaya</td>\n",
       "      <td>75.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>State</td>\n",
       "      <td>Mizoram</td>\n",
       "      <td>85.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>State</td>\n",
       "      <td>Nagaland</td>\n",
       "      <td>87.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>State</td>\n",
       "      <td>Odisha</td>\n",
       "      <td>86.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>State</td>\n",
       "      <td>Punjab</td>\n",
       "      <td>66.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>State</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>54.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>State</td>\n",
       "      <td>Sikkim</td>\n",
       "      <td>89.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>State</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>87.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>State</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>96.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>State</td>\n",
       "      <td>Tripura</td>\n",
       "      <td>82.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>State</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>83.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>State</td>\n",
       "      <td>Uttarakhand</td>\n",
       "      <td>85.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>State</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>81.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>87.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>99.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Dadra and Nagar Haveli and Daman and Diu</td>\n",
       "      <td>95.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>61.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Jammu and Kashmir</td>\n",
       "      <td>88.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Ladakh</td>\n",
       "      <td>84.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Lakshadweep</td>\n",
       "      <td>100.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Puducherry</td>\n",
       "      <td>91.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Category                                  State/UT  SDG 6  SDG 3  \\\n",
       "0             State                            Andhra Pradesh   92.0   77.0   \n",
       "1             State                         Arunachal Pradesh   67.0   64.0   \n",
       "2             State                                     Assam   64.0   59.0   \n",
       "3             State                                     Bihar   91.0   66.0   \n",
       "4             State                              Chhattisgarh   89.0   60.0   \n",
       "5             State                                       Goa  100.0   72.0   \n",
       "6             State                                   Gujarat   93.0   86.0   \n",
       "7             State                                   Haryana   80.0   72.0   \n",
       "8             State                          Himachal Pradesh   85.0   78.0   \n",
       "9             State                                 Jharkhand   83.0   74.0   \n",
       "10            State                                 Karnataka   85.0   78.0   \n",
       "11            State                                    Kerala   89.0   72.0   \n",
       "12            State                            Madhya Pradesh   88.0   62.0   \n",
       "13            State                               Maharashtra   90.0   83.0   \n",
       "14            State                                   Manipur   87.0   68.0   \n",
       "15            State                                 Meghalaya   75.0   70.0   \n",
       "16            State                                   Mizoram   85.0   79.0   \n",
       "17            State                                  Nagaland   87.0   61.0   \n",
       "18            State                                    Odisha   86.0   67.0   \n",
       "19            State                                    Punjab   66.0   77.0   \n",
       "20            State                                 Rajasthan   54.0   70.0   \n",
       "21            State                                    Sikkim   89.0   62.0   \n",
       "22            State                                Tamil Nadu   87.0   81.0   \n",
       "23            State                                 Telangana   96.0   67.0   \n",
       "24            State                                   Tripura   82.0   67.0   \n",
       "25            State                             Uttar Pradesh   83.0   60.0   \n",
       "26            State                               Uttarakhand   85.0   77.0   \n",
       "27            State                               West Bengal   81.0   76.0   \n",
       "28  Union Territory               Andaman and Nicobar Islands   87.0   68.0   \n",
       "29  Union Territory                                Chandigarh   99.0   74.0   \n",
       "30  Union Territory  Dadra and Nagar Haveli and Daman and Diu   95.0   80.0   \n",
       "31  Union Territory                                     Delhi   61.0   90.0   \n",
       "32  Union Territory                         Jammu and Kashmir   88.0   70.0   \n",
       "33  Union Territory                                   Ladakh    84.0   70.0   \n",
       "34  Union Territory                               Lakshadweep  100.0   78.0   \n",
       "35  Union Territory                                Puducherry   91.0   70.0   \n",
       "36              NaN                                       NaN    NaN    NaN   \n",
       "\n",
       "    Unnamed: 4  Unnamed: 5  Unnamed: 6  \n",
       "0          NaN         NaN         NaN  \n",
       "1          NaN         NaN         NaN  \n",
       "2          NaN         NaN         NaN  \n",
       "3          NaN         NaN         NaN  \n",
       "4          NaN         NaN         NaN  \n",
       "5          NaN         NaN         NaN  \n",
       "6          NaN         NaN         NaN  \n",
       "7          NaN         NaN         NaN  \n",
       "8          NaN         NaN         NaN  \n",
       "9          NaN         NaN         NaN  \n",
       "10         NaN         NaN         NaN  \n",
       "11         NaN         NaN         NaN  \n",
       "12         NaN         NaN         NaN  \n",
       "13         NaN         NaN         NaN  \n",
       "14         NaN         NaN         NaN  \n",
       "15         NaN         NaN         NaN  \n",
       "16         NaN         NaN         NaN  \n",
       "17         NaN         NaN         NaN  \n",
       "18         NaN         NaN         NaN  \n",
       "19         NaN         NaN         NaN  \n",
       "20         NaN         NaN         NaN  \n",
       "21         NaN         NaN         NaN  \n",
       "22         NaN         NaN         NaN  \n",
       "23         NaN         NaN         NaN  \n",
       "24         NaN         NaN         NaN  \n",
       "25         NaN         NaN         NaN  \n",
       "26         NaN         NaN         NaN  \n",
       "27         NaN         NaN         NaN  \n",
       "28         NaN         NaN         NaN  \n",
       "29         NaN         NaN         NaN  \n",
       "30         NaN         NaN         NaN  \n",
       "31         NaN         NaN         NaN  \n",
       "32         NaN         NaN         NaN  \n",
       "33         NaN         NaN         NaN  \n",
       "34         NaN         NaN         NaN  \n",
       "35         NaN         NaN         NaN  \n",
       "36         NaN         NaN         NaN  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"D:\\IIT\\Projects\\DataScienceproject\\DSpro_sustainabledev_working\\SDG_test_1.csv\")\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "6c37e1c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "data1 = data.drop(36)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "94d6c13b",
   "metadata": {},
   "outputs": [],
   "source": [
    "data2 = data1.drop(columns = [\"Unnamed: 4\", \"Unnamed: 5\", \"Unnamed: 6\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "6ca2f005",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>State/UT</th>\n",
       "      <th>SDG 6</th>\n",
       "      <th>SDG 3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>State</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>92.0</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>State</td>\n",
       "      <td>Arunachal Pradesh</td>\n",
       "      <td>67.0</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>State</td>\n",
       "      <td>Assam</td>\n",
       "      <td>64.0</td>\n",
       "      <td>59.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>State</td>\n",
       "      <td>Bihar</td>\n",
       "      <td>91.0</td>\n",
       "      <td>66.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>State</td>\n",
       "      <td>Chhattisgarh</td>\n",
       "      <td>89.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>State</td>\n",
       "      <td>Goa</td>\n",
       "      <td>100.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>State</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>93.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>State</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>80.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>State</td>\n",
       "      <td>Himachal Pradesh</td>\n",
       "      <td>85.0</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>State</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>83.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>State</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>85.0</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>State</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>89.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>State</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>88.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>State</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>90.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>State</td>\n",
       "      <td>Manipur</td>\n",
       "      <td>87.0</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>State</td>\n",
       "      <td>Meghalaya</td>\n",
       "      <td>75.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>State</td>\n",
       "      <td>Mizoram</td>\n",
       "      <td>85.0</td>\n",
       "      <td>79.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>State</td>\n",
       "      <td>Nagaland</td>\n",
       "      <td>87.0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>State</td>\n",
       "      <td>Odisha</td>\n",
       "      <td>86.0</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>State</td>\n",
       "      <td>Punjab</td>\n",
       "      <td>66.0</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>State</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>54.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>State</td>\n",
       "      <td>Sikkim</td>\n",
       "      <td>89.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>State</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>87.0</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>State</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>96.0</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>State</td>\n",
       "      <td>Tripura</td>\n",
       "      <td>82.0</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>State</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>83.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>State</td>\n",
       "      <td>Uttarakhand</td>\n",
       "      <td>85.0</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>State</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>81.0</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>87.0</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>99.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Dadra and Nagar Haveli and Daman and Diu</td>\n",
       "      <td>95.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>61.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Jammu and Kashmir</td>\n",
       "      <td>88.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Ladakh</td>\n",
       "      <td>84.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Lakshadweep</td>\n",
       "      <td>100.0</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Puducherry</td>\n",
       "      <td>91.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Category                                  State/UT  SDG 6  SDG 3\n",
       "0             State                            Andhra Pradesh   92.0   77.0\n",
       "1             State                         Arunachal Pradesh   67.0   64.0\n",
       "2             State                                     Assam   64.0   59.0\n",
       "3             State                                     Bihar   91.0   66.0\n",
       "4             State                              Chhattisgarh   89.0   60.0\n",
       "5             State                                       Goa  100.0   72.0\n",
       "6             State                                   Gujarat   93.0   86.0\n",
       "7             State                                   Haryana   80.0   72.0\n",
       "8             State                          Himachal Pradesh   85.0   78.0\n",
       "9             State                                 Jharkhand   83.0   74.0\n",
       "10            State                                 Karnataka   85.0   78.0\n",
       "11            State                                    Kerala   89.0   72.0\n",
       "12            State                            Madhya Pradesh   88.0   62.0\n",
       "13            State                               Maharashtra   90.0   83.0\n",
       "14            State                                   Manipur   87.0   68.0\n",
       "15            State                                 Meghalaya   75.0   70.0\n",
       "16            State                                   Mizoram   85.0   79.0\n",
       "17            State                                  Nagaland   87.0   61.0\n",
       "18            State                                    Odisha   86.0   67.0\n",
       "19            State                                    Punjab   66.0   77.0\n",
       "20            State                                 Rajasthan   54.0   70.0\n",
       "21            State                                    Sikkim   89.0   62.0\n",
       "22            State                                Tamil Nadu   87.0   81.0\n",
       "23            State                                 Telangana   96.0   67.0\n",
       "24            State                                   Tripura   82.0   67.0\n",
       "25            State                             Uttar Pradesh   83.0   60.0\n",
       "26            State                               Uttarakhand   85.0   77.0\n",
       "27            State                               West Bengal   81.0   76.0\n",
       "28  Union Territory               Andaman and Nicobar Islands   87.0   68.0\n",
       "29  Union Territory                                Chandigarh   99.0   74.0\n",
       "30  Union Territory  Dadra and Nagar Haveli and Daman and Diu   95.0   80.0\n",
       "31  Union Territory                                     Delhi   61.0   90.0\n",
       "32  Union Territory                         Jammu and Kashmir   88.0   70.0\n",
       "33  Union Territory                                   Ladakh    84.0   70.0\n",
       "34  Union Territory                               Lakshadweep  100.0   78.0\n",
       "35  Union Territory                                Puducherry   91.0   70.0"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "bf7081b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "71.80555555555556"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean1 = np.mean(data2['SDG 3'])\n",
    "mean1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "374ed727",
   "metadata": {},
   "source": [
    "# # SDG 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "98ef73f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>State/UT</th>\n",
       "      <th>SDG 6</th>\n",
       "      <th>SDG 3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Lakshadweep</td>\n",
       "      <td>100.0</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>State</td>\n",
       "      <td>Goa</td>\n",
       "      <td>100.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>99.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>State</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>96.0</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Dadra and Nagar Haveli and Daman and Diu</td>\n",
       "      <td>95.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>State</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>93.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>State</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>92.0</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Category                                  State/UT  SDG 6  SDG 3\n",
       "34  Union Territory                               Lakshadweep  100.0   78.0\n",
       "5             State                                       Goa  100.0   72.0\n",
       "29  Union Territory                                Chandigarh   99.0   74.0\n",
       "23            State                                 Telangana   96.0   67.0\n",
       "30  Union Territory  Dadra and Nagar Haveli and Daman and Diu   95.0   80.0\n",
       "6             State                                   Gujarat   93.0   86.0\n",
       "0             State                            Andhra Pradesh   92.0   77.0"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sorting the data of SDG 3 wrt SDG 6 in descending order and taking a sample of 7 data\n",
    "data3 = data2.sort_values('SDG 6',ascending=False).head(7)\n",
    "data3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "479b3a46",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "76.28571428571429\n",
      "we are accepting null hypothesis\n"
     ]
    }
   ],
   "source": [
    "#applying t-test to the sample\n",
    "from scipy.stats import ttest_1samp\n",
    "mean01 = np.mean(data3['SDG 3'])\n",
    "print(mean01)\n",
    "tset, pval = ttest_1samp(data3['SDG 3'], mean1)\n",
    "# print(“p-values”,pval)\n",
    "if pval < 0.025 or pval>0.975:    # alpha value is 0.05 or 5%\n",
    "   print(\" we are rejecting null hypothesis\")\n",
    "else:\n",
    "  print(\"we are accepting null hypothesis\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45a23e45",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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