SDG12_graphs.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d31aecab",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "sns.set(rc={'figure.figsize':(11.7,8.67)})\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "2c36662a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "        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>SNO</th>\n",
       "      <th>Category</th>\n",
       "      <th>States/UTs</th>\n",
       "      <th>Per capita fossil fuel consumption (in kg.)</th>\n",
       "      <th>Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)</th>\n",
       "      <th>Hazardous waste generated per 1,000 population (Metric tonnes/Annum)</th>\n",
       "      <th>Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)</th>\n",
       "      <th>Plastic waste generated per 1,000 population (Tonnes/Annum)</th>\n",
       "      <th>Percentage of BMW treated to total quantity of BMW generated</th>\n",
       "      <th>Installed capacity of grid interactive bio power per 10 lakh population (MW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>State</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>158.4</td>\n",
       "      <td>59.575931</td>\n",
       "      <td>11.279270</td>\n",
       "      <td>75.992319</td>\n",
       "      <td>1.274485</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.635735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>State</td>\n",
       "      <td>Arunachal Pradesh</td>\n",
       "      <td>179.7</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.536752</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>State</td>\n",
       "      <td>Assam</td>\n",
       "      <td>88.0</td>\n",
       "      <td>66.643685</td>\n",
       "      <td>1.337720</td>\n",
       "      <td>20.915679</td>\n",
       "      <td>0.948150</td>\n",
       "      <td>75.048046</td>\n",
       "      <td>0.057483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>State</td>\n",
       "      <td>Bihar</td>\n",
       "      <td>50.5</td>\n",
       "      <td>68.584991</td>\n",
       "      <td>0.138161</td>\n",
       "      <td>28.405407</td>\n",
       "      <td>0.582283</td>\n",
       "      <td>28.834587</td>\n",
       "      <td>1.023012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>State</td>\n",
       "      <td>Chhattisgarh</td>\n",
       "      <td>160.9</td>\n",
       "      <td>56.460471</td>\n",
       "      <td>8.557503</td>\n",
       "      <td>19.754941</td>\n",
       "      <td>0.210763</td>\n",
       "      <td>28.559829</td>\n",
       "      <td>8.376372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>State</td>\n",
       "      <td>Goa</td>\n",
       "      <td>547.1</td>\n",
       "      <td>43.631436</td>\n",
       "      <td>19.110821</td>\n",
       "      <td>4.338928</td>\n",
       "      <td>21.238931</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.218931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>State</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>351.4</td>\n",
       "      <td>71.026283</td>\n",
       "      <td>50.116802</td>\n",
       "      <td>33.099375</td>\n",
       "      <td>5.301223</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.117520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>State</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>415.0</td>\n",
       "      <td>75.838182</td>\n",
       "      <td>4.658146</td>\n",
       "      <td>177.463415</td>\n",
       "      <td>2.420170</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>7.252251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>State</td>\n",
       "      <td>Himachal Pradesh</td>\n",
       "      <td>227.4</td>\n",
       "      <td>62.892318</td>\n",
       "      <td>3.738167</td>\n",
       "      <td>65.699879</td>\n",
       "      <td>0.505228</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.249660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>State</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>103.4</td>\n",
       "      <td>70.081292</td>\n",
       "      <td>13.001647</td>\n",
       "      <td>2.062399</td>\n",
       "      <td>1.388899</td>\n",
       "      <td>52.553291</td>\n",
       "      <td>0.112816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>State</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>216.0</td>\n",
       "      <td>52.616052</td>\n",
       "      <td>6.335936</td>\n",
       "      <td>54.790481</td>\n",
       "      <td>4.167701</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>28.397197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>State</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>189.9</td>\n",
       "      <td>40.216734</td>\n",
       "      <td>3.048167</td>\n",
       "      <td>32.637893</td>\n",
       "      <td>3.808702</td>\n",
       "      <td>58.666386</td>\n",
       "      <td>0.064182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>State</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>110.3</td>\n",
       "      <td>63.037865</td>\n",
       "      <td>3.025076</td>\n",
       "      <td>67.055377</td>\n",
       "      <td>0.887769</td>\n",
       "      <td>91.800396</td>\n",
       "      <td>1.465584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>State</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>187.0</td>\n",
       "      <td>50.698150</td>\n",
       "      <td>9.236121</td>\n",
       "      <td>11.572251</td>\n",
       "      <td>3.374468</td>\n",
       "      <td>99.545003</td>\n",
       "      <td>20.998334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>State</td>\n",
       "      <td>Manipur</td>\n",
       "      <td>88.5</td>\n",
       "      <td>52.853598</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.043442</td>\n",
       "      <td>79.374825</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>State</td>\n",
       "      <td>Meghalaya</td>\n",
       "      <td>166.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.152188</td>\n",
       "      <td>1.848049</td>\n",
       "      <td>0.394688</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.227941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>State</td>\n",
       "      <td>Mizoram</td>\n",
       "      <td>127.2</td>\n",
       "      <td>64.235624</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.011242</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>State</td>\n",
       "      <td>Nagaland</td>\n",
       "      <td>77.9</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009372</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.125670</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>State</td>\n",
       "      <td>Odisha</td>\n",
       "      <td>141.4</td>\n",
       "      <td>60.634739</td>\n",
       "      <td>20.678965</td>\n",
       "      <td>62.807815</td>\n",
       "      <td>2.013199</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.302540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>State</td>\n",
       "      <td>Punjab</td>\n",
       "      <td>255.0</td>\n",
       "      <td>78.894375</td>\n",
       "      <td>4.110845</td>\n",
       "      <td>18.016513</td>\n",
       "      <td>4.020830</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>16.044269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>State</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>166.2</td>\n",
       "      <td>70.626894</td>\n",
       "      <td>8.147039</td>\n",
       "      <td>99.187497</td>\n",
       "      <td>1.367041</td>\n",
       "      <td>75.975543</td>\n",
       "      <td>1.542444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>State</td>\n",
       "      <td>Sikkim</td>\n",
       "      <td>207.1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.226100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008589</td>\n",
       "      <td>73.352152</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>State</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>199.9</td>\n",
       "      <td>49.224298</td>\n",
       "      <td>17.262642</td>\n",
       "      <td>48.734607</td>\n",
       "      <td>5.315280</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>13.379154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>State</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>198.4</td>\n",
       "      <td>65.997726</td>\n",
       "      <td>9.925169</td>\n",
       "      <td>52.250571</td>\n",
       "      <td>4.942335</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>5.485401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>State</td>\n",
       "      <td>Tripura</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.073934</td>\n",
       "      <td>93.174061</td>\n",
       "      <td>0.006611</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>91.1</td>\n",
       "      <td>73.718854</td>\n",
       "      <td>1.119218</td>\n",
       "      <td>60.404104</td>\n",
       "      <td>1.140800</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.248464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttarakhand</td>\n",
       "      <td>170.6</td>\n",
       "      <td>78.353497</td>\n",
       "      <td>2.171054</td>\n",
       "      <td>96.333486</td>\n",
       "      <td>2.812573</td>\n",
       "      <td>99.124384</td>\n",
       "      <td>11.510651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>State</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>96.2</td>\n",
       "      <td>50.199310</td>\n",
       "      <td>1.924808</td>\n",
       "      <td>49.912245</td>\n",
       "      <td>3.111255</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.273877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>558.0</td>\n",
       "      <td>46.987952</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.671717</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>412.6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.536752</td>\n",
       "      <td>43.937709</td>\n",
       "      <td>10.013162</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Dadra and Nagar Haveli</td>\n",
       "      <td>1160.5</td>\n",
       "      <td>65.217391</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.117065</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Daman and Diu</td>\n",
       "      <td>909.7</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.117065</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>291.9</td>\n",
       "      <td>89.009991</td>\n",
       "      <td>2.176167</td>\n",
       "      <td>0.049333</td>\n",
       "      <td>11.492766</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.559181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Jammu and Kashmir</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Ladakh</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Lakshadweep</td>\n",
       "      <td>235.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.716418</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.208955</td>\n",
       "      <td>20.872865</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Puducherry</td>\n",
       "      <td>435.6</td>\n",
       "      <td>71.633554</td>\n",
       "      <td>24.071573</td>\n",
       "      <td>33.124825</td>\n",
       "      <td>5.694126</td>\n",
       "      <td>135.052549</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SNO         Category                   States/UTs  \\\n",
       "0     1            State               Andhra Pradesh   \n",
       "1     2            State            Arunachal Pradesh   \n",
       "2     3            State                        Assam   \n",
       "3     4            State                        Bihar   \n",
       "4     5            State                 Chhattisgarh   \n",
       "5     6            State                          Goa   \n",
       "6     7            State                      Gujarat   \n",
       "7     8            State                      Haryana   \n",
       "8     9            State             Himachal Pradesh   \n",
       "9    10            State                    Jharkhand   \n",
       "10   11            State                    Karnataka   \n",
       "11   12            State                       Kerala   \n",
       "12   13            State               Madhya Pradesh   \n",
       "13   14            State                  Maharashtra   \n",
       "14   15            State                      Manipur   \n",
       "15   16            State                    Meghalaya   \n",
       "16   17            State                      Mizoram   \n",
       "17   18            State                     Nagaland   \n",
       "18   19            State                       Odisha   \n",
       "19   20            State                       Punjab   \n",
       "20   21            State                    Rajasthan   \n",
       "21   22            State                       Sikkim   \n",
       "22   23            State                   Tamil Nadu   \n",
       "23   24            State                    Telangana   \n",
       "24   25            State                      Tripura   \n",
       "25   26            State                Uttar Pradesh   \n",
       "26   27            State                  Uttarakhand   \n",
       "27   28            State                  West Bengal   \n",
       "28   29  Union Territory  Andaman and Nicobar Islands   \n",
       "29   30  Union Territory                   Chandigarh   \n",
       "30   31  Union Territory       Dadra and Nagar Haveli   \n",
       "31   32  Union Territory                Daman and Diu   \n",
       "32   33  Union Territory                        Delhi   \n",
       "33   34  Union Territory            Jammu and Kashmir   \n",
       "34   35  Union Territory                      Ladakh    \n",
       "35   36  Union Territory                  Lakshadweep   \n",
       "36   37  Union Territory                   Puducherry   \n",
       "\n",
       "    Per capita fossil fuel consumption (in kg.)  \\\n",
       "0                                         158.4   \n",
       "1                                         179.7   \n",
       "2                                          88.0   \n",
       "3                                          50.5   \n",
       "4                                         160.9   \n",
       "5                                         547.1   \n",
       "6                                         351.4   \n",
       "7                                         415.0   \n",
       "8                                         227.4   \n",
       "9                                         103.4   \n",
       "10                                        216.0   \n",
       "11                                        189.9   \n",
       "12                                        110.3   \n",
       "13                                        187.0   \n",
       "14                                         88.5   \n",
       "15                                        166.0   \n",
       "16                                        127.2   \n",
       "17                                         77.9   \n",
       "18                                        141.4   \n",
       "19                                        255.0   \n",
       "20                                        166.2   \n",
       "21                                        207.1   \n",
       "22                                        199.9   \n",
       "23                                        198.4   \n",
       "24                                         64.0   \n",
       "25                                         91.1   \n",
       "26                                        170.6   \n",
       "27                                         96.2   \n",
       "28                                        558.0   \n",
       "29                                        412.6   \n",
       "30                                       1160.5   \n",
       "31                                        909.7   \n",
       "32                                        291.9   \n",
       "33                                        119.7   \n",
       "34                                        119.7   \n",
       "35                                        235.0   \n",
       "36                                        435.6   \n",
       "\n",
       "    Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)  \\\n",
       "0                                           59.575931                                                 \n",
       "1                                            0.000000                                                 \n",
       "2                                           66.643685                                                 \n",
       "3                                           68.584991                                                 \n",
       "4                                           56.460471                                                 \n",
       "5                                           43.631436                                                 \n",
       "6                                           71.026283                                                 \n",
       "7                                           75.838182                                                 \n",
       "8                                           62.892318                                                 \n",
       "9                                           70.081292                                                 \n",
       "10                                          52.616052                                                 \n",
       "11                                          40.216734                                                 \n",
       "12                                          63.037865                                                 \n",
       "13                                          50.698150                                                 \n",
       "14                                          52.853598                                                 \n",
       "15                                           0.000000                                                 \n",
       "16                                          64.235624                                                 \n",
       "17                                           0.000000                                                 \n",
       "18                                          60.634739                                                 \n",
       "19                                          78.894375                                                 \n",
       "20                                          70.626894                                                 \n",
       "21                                           0.000000                                                 \n",
       "22                                          49.224298                                                 \n",
       "23                                          65.997726                                                 \n",
       "24                                           0.000000                                                 \n",
       "25                                          73.718854                                                 \n",
       "26                                          78.353497                                                 \n",
       "27                                          50.199310                                                 \n",
       "28                                          46.987952                                                 \n",
       "29                                           0.000000                                                 \n",
       "30                                          65.217391                                                 \n",
       "31                                          93.333333                                                 \n",
       "32                                          89.009991                                                 \n",
       "33                                          62.489365                                                 \n",
       "34                                          62.489365                                                 \n",
       "35                                           0.000000                                                 \n",
       "36                                          71.633554                                                 \n",
       "\n",
       "    Hazardous waste generated per 1,000 population (Metric tonnes/Annum)  \\\n",
       "0                                           11.279270                      \n",
       "1                                                 NaN                      \n",
       "2                                            1.337720                      \n",
       "3                                            0.138161                      \n",
       "4                                            8.557503                      \n",
       "5                                           19.110821                      \n",
       "6                                           50.116802                      \n",
       "7                                            4.658146                      \n",
       "8                                            3.738167                      \n",
       "9                                           13.001647                      \n",
       "10                                           6.335936                      \n",
       "11                                           3.048167                      \n",
       "12                                           3.025076                      \n",
       "13                                           9.236121                      \n",
       "14                                                NaN                      \n",
       "15                                           0.152188                      \n",
       "16                                           0.000017                      \n",
       "17                                           0.009372                      \n",
       "18                                          20.678965                      \n",
       "19                                           4.110845                      \n",
       "20                                           8.147039                      \n",
       "21                                           2.226100                      \n",
       "22                                          17.262642                      \n",
       "23                                           9.925169                      \n",
       "24                                           0.073934                      \n",
       "25                                           1.119218                      \n",
       "26                                           2.171054                      \n",
       "27                                           1.924808                      \n",
       "28                                           0.000404                      \n",
       "29                                           1.536752                      \n",
       "30                                                NaN                      \n",
       "31                                                NaN                      \n",
       "32                                           2.176167                      \n",
       "33                                           0.206700                      \n",
       "34                                           0.206700                      \n",
       "35                                           0.716418                      \n",
       "36                                          24.071573                      \n",
       "\n",
       "    Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)  \\\n",
       "0                                           75.992319                                      \n",
       "1                                                 NaN                                      \n",
       "2                                           20.915679                                      \n",
       "3                                           28.405407                                      \n",
       "4                                           19.754941                                      \n",
       "5                                            4.338928                                      \n",
       "6                                           33.099375                                      \n",
       "7                                          177.463415                                      \n",
       "8                                           65.699879                                      \n",
       "9                                            2.062399                                      \n",
       "10                                          54.790481                                      \n",
       "11                                          32.637893                                      \n",
       "12                                          67.055377                                      \n",
       "13                                          11.572251                                      \n",
       "14                                                NaN                                      \n",
       "15                                           1.848049                                      \n",
       "16                                          50.000000                                      \n",
       "17                                          50.000000                                      \n",
       "18                                          62.807815                                      \n",
       "19                                          18.016513                                      \n",
       "20                                          99.187497                                      \n",
       "21                                           0.000000                                      \n",
       "22                                          48.734607                                      \n",
       "23                                          52.250571                                      \n",
       "24                                          93.174061                                      \n",
       "25                                          60.404104                                      \n",
       "26                                          96.333486                                      \n",
       "27                                          49.912245                                      \n",
       "28                                           0.000000                                      \n",
       "29                                          43.937709                                      \n",
       "30                                                NaN                                      \n",
       "31                                                NaN                                      \n",
       "32                                           0.049333                                      \n",
       "33                                        1264.493554                                      \n",
       "34                                        1264.493554                                      \n",
       "35                                           0.000000                                      \n",
       "36                                          33.124825                                      \n",
       "\n",
       "    Plastic waste generated per 1,000 population (Tonnes/Annum)  \\\n",
       "0                                            1.274485             \n",
       "1                                            2.536752             \n",
       "2                                            0.948150             \n",
       "3                                            0.582283             \n",
       "4                                            0.210763             \n",
       "5                                           21.238931             \n",
       "6                                            5.301223             \n",
       "7                                            2.420170             \n",
       "8                                            0.505228             \n",
       "9                                            1.388899             \n",
       "10                                           4.167701             \n",
       "11                                           3.808702             \n",
       "12                                           0.887769             \n",
       "13                                           3.374468             \n",
       "14                                           4.043442             \n",
       "15                                           0.394688             \n",
       "16                                           0.011242             \n",
       "17                                           0.125670             \n",
       "18                                           2.013199             \n",
       "19                                           4.020830             \n",
       "20                                           1.367041             \n",
       "21                                           0.008589             \n",
       "22                                           5.315280             \n",
       "23                                           4.942335             \n",
       "24                                           0.006611             \n",
       "25                                           1.140800             \n",
       "26                                           2.812573             \n",
       "27                                           3.111255             \n",
       "28                                           4.671717             \n",
       "29                                          10.013162             \n",
       "30                                           2.117065             \n",
       "31                                           2.117065             \n",
       "32                                          11.492766             \n",
       "33                                           2.616473             \n",
       "34                                           2.616473             \n",
       "35                                           2.208955             \n",
       "36                                           5.694126             \n",
       "\n",
       "    Percentage of BMW treated to total quantity of BMW generated  \\\n",
       "0                                          100.000000              \n",
       "1                                          100.000000              \n",
       "2                                           75.048046              \n",
       "3                                           28.834587              \n",
       "4                                           28.559829              \n",
       "5                                          100.000000              \n",
       "6                                          100.000000              \n",
       "7                                          100.000000              \n",
       "8                                          100.000000              \n",
       "9                                           52.553291              \n",
       "10                                         100.000000              \n",
       "11                                          58.666386              \n",
       "12                                          91.800396              \n",
       "13                                          99.545003              \n",
       "14                                          79.374825              \n",
       "15                                         100.000000              \n",
       "16                                         100.000000              \n",
       "17                                         100.000000              \n",
       "18                                         100.000000              \n",
       "19                                         100.000000              \n",
       "20                                          75.975543              \n",
       "21                                          73.352152              \n",
       "22                                         100.000000              \n",
       "23                                         100.000000              \n",
       "24                                         100.000000              \n",
       "25                                         100.000000              \n",
       "26                                          99.124384              \n",
       "27                                         100.000000              \n",
       "28                                         100.000000              \n",
       "29                                         100.000000              \n",
       "30                                         100.000000              \n",
       "31                                         100.000000              \n",
       "32                                         100.000000              \n",
       "33                                          95.473020              \n",
       "34                                          95.473020              \n",
       "35                                          20.872865              \n",
       "36                                         135.052549              \n",
       "\n",
       "    Installed capacity of grid interactive bio power per 10 lakh population (MW)  \n",
       "0                                            9.635735                             \n",
       "1                                            0.000000                             \n",
       "2                                            0.057483                             \n",
       "3                                            1.023012                             \n",
       "4                                            8.376372                             \n",
       "5                                            0.218931                             \n",
       "6                                            1.117520                             \n",
       "7                                            7.252251                             \n",
       "8                                            1.249660                             \n",
       "9                                            0.112816                             \n",
       "10                                          28.397197                             \n",
       "11                                           0.064182                             \n",
       "12                                           1.465584                             \n",
       "13                                          20.998334                             \n",
       "14                                                NaN                             \n",
       "15                                           4.227941                             \n",
       "16                                                NaN                             \n",
       "17                                                NaN                             \n",
       "18                                           1.302540                             \n",
       "19                                          16.044269                             \n",
       "20                                           1.542444                             \n",
       "21                                                NaN                             \n",
       "22                                          13.379154                             \n",
       "23                                           5.485401                             \n",
       "24                                                NaN                             \n",
       "25                                           9.248464                             \n",
       "26                                          11.510651                             \n",
       "27                                           3.273877                             \n",
       "28                                                NaN                             \n",
       "29                                                NaN                             \n",
       "30                                                NaN                             \n",
       "31                                                NaN                             \n",
       "32                                           2.559181                             \n",
       "33                                                NaN                             \n",
       "34                                                NaN                             \n",
       "35                                                NaN                             \n",
       "36                                                NaN                             "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"D:\\IIT\\Projects\\DataScienceproject\\DSpro_sustainabledev_working\\SDG 12.csv\")\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2ac715de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SNO', 'Category', 'States/UTs',\n",
       "       'Per capita fossil fuel consumption (in kg.)',\n",
       "       'Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)',\n",
       "       'Hazardous waste generated per 1,000 population (Metric tonnes/Annum)',\n",
       "       'Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)',\n",
       "       'Plastic waste generated per 1,000 population (Tonnes/Annum)',\n",
       "       'Percentage of BMW treated to total quantity of BMW generated',\n",
       "       'Installed capacity of grid interactive bio power per 10 lakh population (MW)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d2deb1cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Per capita fossil fuel consumption (in kg.)')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 842.4x624.24 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=data['States/UTs']\n",
    "y=data['Per capita fossil fuel consumption (in kg.)']\n",
    "plt.bar(x,y,align='edge',edgecolor='black',linewidth=\"2\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel(\"States & UTs\")\n",
    "plt.ylabel(\"Per capita fossil fuel consumption (in kg.)\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d2023a86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 842.4x624.24 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=data['States/UTs']\n",
    "y=data['Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)']\n",
    "plt.bar(x,y,align='edge',edgecolor='black',linewidth=\"2\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel(\"States & UTs\")\n",
    "plt.ylabel(\"Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "3a5dde10",
   "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>SNO</th>\n",
       "      <th>Category</th>\n",
       "      <th>States/UTs</th>\n",
       "      <th>Per capita fossil fuel consumption (in kg.)</th>\n",
       "      <th>Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)</th>\n",
       "      <th>Hazardous waste generated per 1,000 population (Metric tonnes/Annum)</th>\n",
       "      <th>Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)</th>\n",
       "      <th>Plastic waste generated per 1,000 population (Tonnes/Annum)</th>\n",
       "      <th>Percentage of BMW treated to total quantity of BMW generated</th>\n",
       "      <th>Installed capacity of grid interactive bio power per 10 lakh population (MW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>State</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>158.4</td>\n",
       "      <td>59.575931</td>\n",
       "      <td>11.279270</td>\n",
       "      <td>75.992319</td>\n",
       "      <td>1.274485</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.635735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>State</td>\n",
       "      <td>Assam</td>\n",
       "      <td>88.0</td>\n",
       "      <td>66.643685</td>\n",
       "      <td>1.337720</td>\n",
       "      <td>20.915679</td>\n",
       "      <td>0.948150</td>\n",
       "      <td>75.048046</td>\n",
       "      <td>0.057483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>State</td>\n",
       "      <td>Bihar</td>\n",
       "      <td>50.5</td>\n",
       "      <td>68.584991</td>\n",
       "      <td>0.138161</td>\n",
       "      <td>28.405407</td>\n",
       "      <td>0.582283</td>\n",
       "      <td>28.834587</td>\n",
       "      <td>1.023012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>State</td>\n",
       "      <td>Chhattisgarh</td>\n",
       "      <td>160.9</td>\n",
       "      <td>56.460471</td>\n",
       "      <td>8.557503</td>\n",
       "      <td>19.754941</td>\n",
       "      <td>0.210763</td>\n",
       "      <td>28.559829</td>\n",
       "      <td>8.376372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>State</td>\n",
       "      <td>Goa</td>\n",
       "      <td>547.1</td>\n",
       "      <td>43.631436</td>\n",
       "      <td>19.110821</td>\n",
       "      <td>4.338928</td>\n",
       "      <td>21.238931</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.218931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>State</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>351.4</td>\n",
       "      <td>71.026283</td>\n",
       "      <td>50.116802</td>\n",
       "      <td>33.099375</td>\n",
       "      <td>5.301223</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.117520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>State</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>415.0</td>\n",
       "      <td>75.838182</td>\n",
       "      <td>4.658146</td>\n",
       "      <td>177.463415</td>\n",
       "      <td>2.420170</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>7.252251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>State</td>\n",
       "      <td>Himachal Pradesh</td>\n",
       "      <td>227.4</td>\n",
       "      <td>62.892318</td>\n",
       "      <td>3.738167</td>\n",
       "      <td>65.699879</td>\n",
       "      <td>0.505228</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.249660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>State</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>103.4</td>\n",
       "      <td>70.081292</td>\n",
       "      <td>13.001647</td>\n",
       "      <td>2.062399</td>\n",
       "      <td>1.388899</td>\n",
       "      <td>52.553291</td>\n",
       "      <td>0.112816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>State</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>216.0</td>\n",
       "      <td>52.616052</td>\n",
       "      <td>6.335936</td>\n",
       "      <td>54.790481</td>\n",
       "      <td>4.167701</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>28.397197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>State</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>189.9</td>\n",
       "      <td>40.216734</td>\n",
       "      <td>3.048167</td>\n",
       "      <td>32.637893</td>\n",
       "      <td>3.808702</td>\n",
       "      <td>58.666386</td>\n",
       "      <td>0.064182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>State</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>110.3</td>\n",
       "      <td>63.037865</td>\n",
       "      <td>3.025076</td>\n",
       "      <td>67.055377</td>\n",
       "      <td>0.887769</td>\n",
       "      <td>91.800396</td>\n",
       "      <td>1.465584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>State</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>187.0</td>\n",
       "      <td>50.698150</td>\n",
       "      <td>9.236121</td>\n",
       "      <td>11.572251</td>\n",
       "      <td>3.374468</td>\n",
       "      <td>99.545003</td>\n",
       "      <td>20.998334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>State</td>\n",
       "      <td>Meghalaya</td>\n",
       "      <td>166.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.152188</td>\n",
       "      <td>1.848049</td>\n",
       "      <td>0.394688</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.227941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>State</td>\n",
       "      <td>Mizoram</td>\n",
       "      <td>127.2</td>\n",
       "      <td>64.235624</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.011242</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>State</td>\n",
       "      <td>Nagaland</td>\n",
       "      <td>77.9</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009372</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.125670</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>State</td>\n",
       "      <td>Odisha</td>\n",
       "      <td>141.4</td>\n",
       "      <td>60.634739</td>\n",
       "      <td>20.678965</td>\n",
       "      <td>62.807815</td>\n",
       "      <td>2.013199</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.302540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>State</td>\n",
       "      <td>Punjab</td>\n",
       "      <td>255.0</td>\n",
       "      <td>78.894375</td>\n",
       "      <td>4.110845</td>\n",
       "      <td>18.016513</td>\n",
       "      <td>4.020830</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>16.044269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>State</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>166.2</td>\n",
       "      <td>70.626894</td>\n",
       "      <td>8.147039</td>\n",
       "      <td>99.187497</td>\n",
       "      <td>1.367041</td>\n",
       "      <td>75.975543</td>\n",
       "      <td>1.542444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>State</td>\n",
       "      <td>Sikkim</td>\n",
       "      <td>207.1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.226100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008589</td>\n",
       "      <td>73.352152</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>State</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>199.9</td>\n",
       "      <td>49.224298</td>\n",
       "      <td>17.262642</td>\n",
       "      <td>48.734607</td>\n",
       "      <td>5.315280</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>13.379154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>State</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>198.4</td>\n",
       "      <td>65.997726</td>\n",
       "      <td>9.925169</td>\n",
       "      <td>52.250571</td>\n",
       "      <td>4.942335</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>5.485401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>State</td>\n",
       "      <td>Tripura</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.073934</td>\n",
       "      <td>93.174061</td>\n",
       "      <td>0.006611</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>91.1</td>\n",
       "      <td>73.718854</td>\n",
       "      <td>1.119218</td>\n",
       "      <td>60.404104</td>\n",
       "      <td>1.140800</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.248464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttarakhand</td>\n",
       "      <td>170.6</td>\n",
       "      <td>78.353497</td>\n",
       "      <td>2.171054</td>\n",
       "      <td>96.333486</td>\n",
       "      <td>2.812573</td>\n",
       "      <td>99.124384</td>\n",
       "      <td>11.510651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>State</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>96.2</td>\n",
       "      <td>50.199310</td>\n",
       "      <td>1.924808</td>\n",
       "      <td>49.912245</td>\n",
       "      <td>3.111255</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.273877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>558.0</td>\n",
       "      <td>46.987952</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.671717</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>412.6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.536752</td>\n",
       "      <td>43.937709</td>\n",
       "      <td>10.013162</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>291.9</td>\n",
       "      <td>89.009991</td>\n",
       "      <td>2.176167</td>\n",
       "      <td>0.049333</td>\n",
       "      <td>11.492766</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.559181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Jammu and Kashmir</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Ladakh</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Lakshadweep</td>\n",
       "      <td>235.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.716418</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.208955</td>\n",
       "      <td>20.872865</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Puducherry</td>\n",
       "      <td>435.6</td>\n",
       "      <td>71.633554</td>\n",
       "      <td>24.071573</td>\n",
       "      <td>33.124825</td>\n",
       "      <td>5.694126</td>\n",
       "      <td>135.052549</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SNO         Category                   States/UTs  \\\n",
       "0     1            State               Andhra Pradesh   \n",
       "2     3            State                        Assam   \n",
       "3     4            State                        Bihar   \n",
       "4     5            State                 Chhattisgarh   \n",
       "5     6            State                          Goa   \n",
       "6     7            State                      Gujarat   \n",
       "7     8            State                      Haryana   \n",
       "8     9            State             Himachal Pradesh   \n",
       "9    10            State                    Jharkhand   \n",
       "10   11            State                    Karnataka   \n",
       "11   12            State                       Kerala   \n",
       "12   13            State               Madhya Pradesh   \n",
       "13   14            State                  Maharashtra   \n",
       "15   16            State                    Meghalaya   \n",
       "16   17            State                      Mizoram   \n",
       "17   18            State                     Nagaland   \n",
       "18   19            State                       Odisha   \n",
       "19   20            State                       Punjab   \n",
       "20   21            State                    Rajasthan   \n",
       "21   22            State                       Sikkim   \n",
       "22   23            State                   Tamil Nadu   \n",
       "23   24            State                    Telangana   \n",
       "24   25            State                      Tripura   \n",
       "25   26            State                Uttar Pradesh   \n",
       "26   27            State                  Uttarakhand   \n",
       "27   28            State                  West Bengal   \n",
       "28   29  Union Territory  Andaman and Nicobar Islands   \n",
       "29   30  Union Territory                   Chandigarh   \n",
       "32   33  Union Territory                        Delhi   \n",
       "33   34  Union Territory            Jammu and Kashmir   \n",
       "34   35  Union Territory                      Ladakh    \n",
       "35   36  Union Territory                  Lakshadweep   \n",
       "36   37  Union Territory                   Puducherry   \n",
       "\n",
       "    Per capita fossil fuel consumption (in kg.)  \\\n",
       "0                                         158.4   \n",
       "2                                          88.0   \n",
       "3                                          50.5   \n",
       "4                                         160.9   \n",
       "5                                         547.1   \n",
       "6                                         351.4   \n",
       "7                                         415.0   \n",
       "8                                         227.4   \n",
       "9                                         103.4   \n",
       "10                                        216.0   \n",
       "11                                        189.9   \n",
       "12                                        110.3   \n",
       "13                                        187.0   \n",
       "15                                        166.0   \n",
       "16                                        127.2   \n",
       "17                                         77.9   \n",
       "18                                        141.4   \n",
       "19                                        255.0   \n",
       "20                                        166.2   \n",
       "21                                        207.1   \n",
       "22                                        199.9   \n",
       "23                                        198.4   \n",
       "24                                         64.0   \n",
       "25                                         91.1   \n",
       "26                                        170.6   \n",
       "27                                         96.2   \n",
       "28                                        558.0   \n",
       "29                                        412.6   \n",
       "32                                        291.9   \n",
       "33                                        119.7   \n",
       "34                                        119.7   \n",
       "35                                        235.0   \n",
       "36                                        435.6   \n",
       "\n",
       "    Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)  \\\n",
       "0                                           59.575931                                                 \n",
       "2                                           66.643685                                                 \n",
       "3                                           68.584991                                                 \n",
       "4                                           56.460471                                                 \n",
       "5                                           43.631436                                                 \n",
       "6                                           71.026283                                                 \n",
       "7                                           75.838182                                                 \n",
       "8                                           62.892318                                                 \n",
       "9                                           70.081292                                                 \n",
       "10                                          52.616052                                                 \n",
       "11                                          40.216734                                                 \n",
       "12                                          63.037865                                                 \n",
       "13                                          50.698150                                                 \n",
       "15                                           0.000000                                                 \n",
       "16                                          64.235624                                                 \n",
       "17                                           0.000000                                                 \n",
       "18                                          60.634739                                                 \n",
       "19                                          78.894375                                                 \n",
       "20                                          70.626894                                                 \n",
       "21                                           0.000000                                                 \n",
       "22                                          49.224298                                                 \n",
       "23                                          65.997726                                                 \n",
       "24                                           0.000000                                                 \n",
       "25                                          73.718854                                                 \n",
       "26                                          78.353497                                                 \n",
       "27                                          50.199310                                                 \n",
       "28                                          46.987952                                                 \n",
       "29                                           0.000000                                                 \n",
       "32                                          89.009991                                                 \n",
       "33                                          62.489365                                                 \n",
       "34                                          62.489365                                                 \n",
       "35                                           0.000000                                                 \n",
       "36                                          71.633554                                                 \n",
       "\n",
       "    Hazardous waste generated per 1,000 population (Metric tonnes/Annum)  \\\n",
       "0                                           11.279270                      \n",
       "2                                            1.337720                      \n",
       "3                                            0.138161                      \n",
       "4                                            8.557503                      \n",
       "5                                           19.110821                      \n",
       "6                                           50.116802                      \n",
       "7                                            4.658146                      \n",
       "8                                            3.738167                      \n",
       "9                                           13.001647                      \n",
       "10                                           6.335936                      \n",
       "11                                           3.048167                      \n",
       "12                                           3.025076                      \n",
       "13                                           9.236121                      \n",
       "15                                           0.152188                      \n",
       "16                                           0.000017                      \n",
       "17                                           0.009372                      \n",
       "18                                          20.678965                      \n",
       "19                                           4.110845                      \n",
       "20                                           8.147039                      \n",
       "21                                           2.226100                      \n",
       "22                                          17.262642                      \n",
       "23                                           9.925169                      \n",
       "24                                           0.073934                      \n",
       "25                                           1.119218                      \n",
       "26                                           2.171054                      \n",
       "27                                           1.924808                      \n",
       "28                                           0.000404                      \n",
       "29                                           1.536752                      \n",
       "32                                           2.176167                      \n",
       "33                                           0.206700                      \n",
       "34                                           0.206700                      \n",
       "35                                           0.716418                      \n",
       "36                                          24.071573                      \n",
       "\n",
       "    Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)  \\\n",
       "0                                           75.992319                                      \n",
       "2                                           20.915679                                      \n",
       "3                                           28.405407                                      \n",
       "4                                           19.754941                                      \n",
       "5                                            4.338928                                      \n",
       "6                                           33.099375                                      \n",
       "7                                          177.463415                                      \n",
       "8                                           65.699879                                      \n",
       "9                                            2.062399                                      \n",
       "10                                          54.790481                                      \n",
       "11                                          32.637893                                      \n",
       "12                                          67.055377                                      \n",
       "13                                          11.572251                                      \n",
       "15                                           1.848049                                      \n",
       "16                                          50.000000                                      \n",
       "17                                          50.000000                                      \n",
       "18                                          62.807815                                      \n",
       "19                                          18.016513                                      \n",
       "20                                          99.187497                                      \n",
       "21                                           0.000000                                      \n",
       "22                                          48.734607                                      \n",
       "23                                          52.250571                                      \n",
       "24                                          93.174061                                      \n",
       "25                                          60.404104                                      \n",
       "26                                          96.333486                                      \n",
       "27                                          49.912245                                      \n",
       "28                                           0.000000                                      \n",
       "29                                          43.937709                                      \n",
       "32                                           0.049333                                      \n",
       "33                                        1264.493554                                      \n",
       "34                                        1264.493554                                      \n",
       "35                                           0.000000                                      \n",
       "36                                          33.124825                                      \n",
       "\n",
       "    Plastic waste generated per 1,000 population (Tonnes/Annum)  \\\n",
       "0                                            1.274485             \n",
       "2                                            0.948150             \n",
       "3                                            0.582283             \n",
       "4                                            0.210763             \n",
       "5                                           21.238931             \n",
       "6                                            5.301223             \n",
       "7                                            2.420170             \n",
       "8                                            0.505228             \n",
       "9                                            1.388899             \n",
       "10                                           4.167701             \n",
       "11                                           3.808702             \n",
       "12                                           0.887769             \n",
       "13                                           3.374468             \n",
       "15                                           0.394688             \n",
       "16                                           0.011242             \n",
       "17                                           0.125670             \n",
       "18                                           2.013199             \n",
       "19                                           4.020830             \n",
       "20                                           1.367041             \n",
       "21                                           0.008589             \n",
       "22                                           5.315280             \n",
       "23                                           4.942335             \n",
       "24                                           0.006611             \n",
       "25                                           1.140800             \n",
       "26                                           2.812573             \n",
       "27                                           3.111255             \n",
       "28                                           4.671717             \n",
       "29                                          10.013162             \n",
       "32                                          11.492766             \n",
       "33                                           2.616473             \n",
       "34                                           2.616473             \n",
       "35                                           2.208955             \n",
       "36                                           5.694126             \n",
       "\n",
       "    Percentage of BMW treated to total quantity of BMW generated  \\\n",
       "0                                          100.000000              \n",
       "2                                           75.048046              \n",
       "3                                           28.834587              \n",
       "4                                           28.559829              \n",
       "5                                          100.000000              \n",
       "6                                          100.000000              \n",
       "7                                          100.000000              \n",
       "8                                          100.000000              \n",
       "9                                           52.553291              \n",
       "10                                         100.000000              \n",
       "11                                          58.666386              \n",
       "12                                          91.800396              \n",
       "13                                          99.545003              \n",
       "15                                         100.000000              \n",
       "16                                         100.000000              \n",
       "17                                         100.000000              \n",
       "18                                         100.000000              \n",
       "19                                         100.000000              \n",
       "20                                          75.975543              \n",
       "21                                          73.352152              \n",
       "22                                         100.000000              \n",
       "23                                         100.000000              \n",
       "24                                         100.000000              \n",
       "25                                         100.000000              \n",
       "26                                          99.124384              \n",
       "27                                         100.000000              \n",
       "28                                         100.000000              \n",
       "29                                         100.000000              \n",
       "32                                         100.000000              \n",
       "33                                          95.473020              \n",
       "34                                          95.473020              \n",
       "35                                          20.872865              \n",
       "36                                         135.052549              \n",
       "\n",
       "    Installed capacity of grid interactive bio power per 10 lakh population (MW)  \n",
       "0                                            9.635735                             \n",
       "2                                            0.057483                             \n",
       "3                                            1.023012                             \n",
       "4                                            8.376372                             \n",
       "5                                            0.218931                             \n",
       "6                                            1.117520                             \n",
       "7                                            7.252251                             \n",
       "8                                            1.249660                             \n",
       "9                                            0.112816                             \n",
       "10                                          28.397197                             \n",
       "11                                           0.064182                             \n",
       "12                                           1.465584                             \n",
       "13                                          20.998334                             \n",
       "15                                           4.227941                             \n",
       "16                                                NaN                             \n",
       "17                                                NaN                             \n",
       "18                                           1.302540                             \n",
       "19                                          16.044269                             \n",
       "20                                           1.542444                             \n",
       "21                                                NaN                             \n",
       "22                                          13.379154                             \n",
       "23                                           5.485401                             \n",
       "24                                                NaN                             \n",
       "25                                           9.248464                             \n",
       "26                                          11.510651                             \n",
       "27                                           3.273877                             \n",
       "28                                                NaN                             \n",
       "29                                                NaN                             \n",
       "32                                           2.559181                             \n",
       "33                                                NaN                             \n",
       "34                                                NaN                             \n",
       "35                                                NaN                             \n",
       "36                                                NaN                             "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1= data.dropna(subset=['Hazardous waste generated per 1,000 population (Metric tonnes/Annum)'])\n",
    "data1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "187b43b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Hazardous waste generated per 1,000 population (Metric tonnes/Annum)')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 842.4x624.24 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=data1['States/UTs']\n",
    "y=data1['Hazardous waste generated per 1,000 population (Metric tonnes/Annum)']\n",
    "plt.bar(x,y,align='edge',edgecolor='black',linewidth=\"2\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel(\"States & UTs\")\n",
    "plt.ylabel(\"Hazardous waste generated per 1,000 population (Metric tonnes/Annum)\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "217dc147",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SNO', 'Category', 'States/UTs',\n",
       "       'Per capita fossil fuel consumption (in kg.)',\n",
       "       'Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)',\n",
       "       'Hazardous waste generated per 1,000 population (Metric tonnes/Annum)',\n",
       "       'Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)',\n",
       "       'Plastic waste generated per 1,000 population (Tonnes/Annum)',\n",
       "       'Percentage of BMW treated to total quantity of BMW generated',\n",
       "       'Installed capacity of grid interactive bio power per 10 lakh population (MW)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c4537c3a",
   "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>SNO</th>\n",
       "      <th>Category</th>\n",
       "      <th>States/UTs</th>\n",
       "      <th>Per capita fossil fuel consumption (in kg.)</th>\n",
       "      <th>Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)</th>\n",
       "      <th>Hazardous waste generated per 1,000 population (Metric tonnes/Annum)</th>\n",
       "      <th>Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)</th>\n",
       "      <th>Plastic waste generated per 1,000 population (Tonnes/Annum)</th>\n",
       "      <th>Percentage of BMW treated to total quantity of BMW generated</th>\n",
       "      <th>Installed capacity of grid interactive bio power per 10 lakh population (MW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>State</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>158.4</td>\n",
       "      <td>59.575931</td>\n",
       "      <td>11.279270</td>\n",
       "      <td>75.992319</td>\n",
       "      <td>1.274485</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.635735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>State</td>\n",
       "      <td>Assam</td>\n",
       "      <td>88.0</td>\n",
       "      <td>66.643685</td>\n",
       "      <td>1.337720</td>\n",
       "      <td>20.915679</td>\n",
       "      <td>0.948150</td>\n",
       "      <td>75.048046</td>\n",
       "      <td>0.057483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>State</td>\n",
       "      <td>Bihar</td>\n",
       "      <td>50.5</td>\n",
       "      <td>68.584991</td>\n",
       "      <td>0.138161</td>\n",
       "      <td>28.405407</td>\n",
       "      <td>0.582283</td>\n",
       "      <td>28.834587</td>\n",
       "      <td>1.023012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>State</td>\n",
       "      <td>Chhattisgarh</td>\n",
       "      <td>160.9</td>\n",
       "      <td>56.460471</td>\n",
       "      <td>8.557503</td>\n",
       "      <td>19.754941</td>\n",
       "      <td>0.210763</td>\n",
       "      <td>28.559829</td>\n",
       "      <td>8.376372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>State</td>\n",
       "      <td>Goa</td>\n",
       "      <td>547.1</td>\n",
       "      <td>43.631436</td>\n",
       "      <td>19.110821</td>\n",
       "      <td>4.338928</td>\n",
       "      <td>21.238931</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.218931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>State</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>351.4</td>\n",
       "      <td>71.026283</td>\n",
       "      <td>50.116802</td>\n",
       "      <td>33.099375</td>\n",
       "      <td>5.301223</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.117520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>State</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>415.0</td>\n",
       "      <td>75.838182</td>\n",
       "      <td>4.658146</td>\n",
       "      <td>177.463415</td>\n",
       "      <td>2.420170</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>7.252251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>State</td>\n",
       "      <td>Himachal Pradesh</td>\n",
       "      <td>227.4</td>\n",
       "      <td>62.892318</td>\n",
       "      <td>3.738167</td>\n",
       "      <td>65.699879</td>\n",
       "      <td>0.505228</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.249660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>State</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>103.4</td>\n",
       "      <td>70.081292</td>\n",
       "      <td>13.001647</td>\n",
       "      <td>2.062399</td>\n",
       "      <td>1.388899</td>\n",
       "      <td>52.553291</td>\n",
       "      <td>0.112816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>State</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>216.0</td>\n",
       "      <td>52.616052</td>\n",
       "      <td>6.335936</td>\n",
       "      <td>54.790481</td>\n",
       "      <td>4.167701</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>28.397197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>State</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>189.9</td>\n",
       "      <td>40.216734</td>\n",
       "      <td>3.048167</td>\n",
       "      <td>32.637893</td>\n",
       "      <td>3.808702</td>\n",
       "      <td>58.666386</td>\n",
       "      <td>0.064182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>State</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>110.3</td>\n",
       "      <td>63.037865</td>\n",
       "      <td>3.025076</td>\n",
       "      <td>67.055377</td>\n",
       "      <td>0.887769</td>\n",
       "      <td>91.800396</td>\n",
       "      <td>1.465584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>State</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>187.0</td>\n",
       "      <td>50.698150</td>\n",
       "      <td>9.236121</td>\n",
       "      <td>11.572251</td>\n",
       "      <td>3.374468</td>\n",
       "      <td>99.545003</td>\n",
       "      <td>20.998334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>State</td>\n",
       "      <td>Meghalaya</td>\n",
       "      <td>166.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.152188</td>\n",
       "      <td>1.848049</td>\n",
       "      <td>0.394688</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.227941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>State</td>\n",
       "      <td>Mizoram</td>\n",
       "      <td>127.2</td>\n",
       "      <td>64.235624</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.011242</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>State</td>\n",
       "      <td>Nagaland</td>\n",
       "      <td>77.9</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009372</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.125670</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>State</td>\n",
       "      <td>Odisha</td>\n",
       "      <td>141.4</td>\n",
       "      <td>60.634739</td>\n",
       "      <td>20.678965</td>\n",
       "      <td>62.807815</td>\n",
       "      <td>2.013199</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.302540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>State</td>\n",
       "      <td>Punjab</td>\n",
       "      <td>255.0</td>\n",
       "      <td>78.894375</td>\n",
       "      <td>4.110845</td>\n",
       "      <td>18.016513</td>\n",
       "      <td>4.020830</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>16.044269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>State</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>166.2</td>\n",
       "      <td>70.626894</td>\n",
       "      <td>8.147039</td>\n",
       "      <td>99.187497</td>\n",
       "      <td>1.367041</td>\n",
       "      <td>75.975543</td>\n",
       "      <td>1.542444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>State</td>\n",
       "      <td>Sikkim</td>\n",
       "      <td>207.1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.226100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008589</td>\n",
       "      <td>73.352152</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>State</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>199.9</td>\n",
       "      <td>49.224298</td>\n",
       "      <td>17.262642</td>\n",
       "      <td>48.734607</td>\n",
       "      <td>5.315280</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>13.379154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>State</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>198.4</td>\n",
       "      <td>65.997726</td>\n",
       "      <td>9.925169</td>\n",
       "      <td>52.250571</td>\n",
       "      <td>4.942335</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>5.485401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>State</td>\n",
       "      <td>Tripura</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.073934</td>\n",
       "      <td>93.174061</td>\n",
       "      <td>0.006611</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>91.1</td>\n",
       "      <td>73.718854</td>\n",
       "      <td>1.119218</td>\n",
       "      <td>60.404104</td>\n",
       "      <td>1.140800</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.248464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttarakhand</td>\n",
       "      <td>170.6</td>\n",
       "      <td>78.353497</td>\n",
       "      <td>2.171054</td>\n",
       "      <td>96.333486</td>\n",
       "      <td>2.812573</td>\n",
       "      <td>99.124384</td>\n",
       "      <td>11.510651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>State</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>96.2</td>\n",
       "      <td>50.199310</td>\n",
       "      <td>1.924808</td>\n",
       "      <td>49.912245</td>\n",
       "      <td>3.111255</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.273877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>558.0</td>\n",
       "      <td>46.987952</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.671717</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>412.6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.536752</td>\n",
       "      <td>43.937709</td>\n",
       "      <td>10.013162</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>291.9</td>\n",
       "      <td>89.009991</td>\n",
       "      <td>2.176167</td>\n",
       "      <td>0.049333</td>\n",
       "      <td>11.492766</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.559181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Jammu and Kashmir</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Ladakh</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Lakshadweep</td>\n",
       "      <td>235.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.716418</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.208955</td>\n",
       "      <td>20.872865</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Puducherry</td>\n",
       "      <td>435.6</td>\n",
       "      <td>71.633554</td>\n",
       "      <td>24.071573</td>\n",
       "      <td>33.124825</td>\n",
       "      <td>5.694126</td>\n",
       "      <td>135.052549</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SNO         Category                   States/UTs  \\\n",
       "0     1            State               Andhra Pradesh   \n",
       "2     3            State                        Assam   \n",
       "3     4            State                        Bihar   \n",
       "4     5            State                 Chhattisgarh   \n",
       "5     6            State                          Goa   \n",
       "6     7            State                      Gujarat   \n",
       "7     8            State                      Haryana   \n",
       "8     9            State             Himachal Pradesh   \n",
       "9    10            State                    Jharkhand   \n",
       "10   11            State                    Karnataka   \n",
       "11   12            State                       Kerala   \n",
       "12   13            State               Madhya Pradesh   \n",
       "13   14            State                  Maharashtra   \n",
       "15   16            State                    Meghalaya   \n",
       "16   17            State                      Mizoram   \n",
       "17   18            State                     Nagaland   \n",
       "18   19            State                       Odisha   \n",
       "19   20            State                       Punjab   \n",
       "20   21            State                    Rajasthan   \n",
       "21   22            State                       Sikkim   \n",
       "22   23            State                   Tamil Nadu   \n",
       "23   24            State                    Telangana   \n",
       "24   25            State                      Tripura   \n",
       "25   26            State                Uttar Pradesh   \n",
       "26   27            State                  Uttarakhand   \n",
       "27   28            State                  West Bengal   \n",
       "28   29  Union Territory  Andaman and Nicobar Islands   \n",
       "29   30  Union Territory                   Chandigarh   \n",
       "32   33  Union Territory                        Delhi   \n",
       "33   34  Union Territory            Jammu and Kashmir   \n",
       "34   35  Union Territory                      Ladakh    \n",
       "35   36  Union Territory                  Lakshadweep   \n",
       "36   37  Union Territory                   Puducherry   \n",
       "\n",
       "    Per capita fossil fuel consumption (in kg.)  \\\n",
       "0                                         158.4   \n",
       "2                                          88.0   \n",
       "3                                          50.5   \n",
       "4                                         160.9   \n",
       "5                                         547.1   \n",
       "6                                         351.4   \n",
       "7                                         415.0   \n",
       "8                                         227.4   \n",
       "9                                         103.4   \n",
       "10                                        216.0   \n",
       "11                                        189.9   \n",
       "12                                        110.3   \n",
       "13                                        187.0   \n",
       "15                                        166.0   \n",
       "16                                        127.2   \n",
       "17                                         77.9   \n",
       "18                                        141.4   \n",
       "19                                        255.0   \n",
       "20                                        166.2   \n",
       "21                                        207.1   \n",
       "22                                        199.9   \n",
       "23                                        198.4   \n",
       "24                                         64.0   \n",
       "25                                         91.1   \n",
       "26                                        170.6   \n",
       "27                                         96.2   \n",
       "28                                        558.0   \n",
       "29                                        412.6   \n",
       "32                                        291.9   \n",
       "33                                        119.7   \n",
       "34                                        119.7   \n",
       "35                                        235.0   \n",
       "36                                        435.6   \n",
       "\n",
       "    Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)  \\\n",
       "0                                           59.575931                                                 \n",
       "2                                           66.643685                                                 \n",
       "3                                           68.584991                                                 \n",
       "4                                           56.460471                                                 \n",
       "5                                           43.631436                                                 \n",
       "6                                           71.026283                                                 \n",
       "7                                           75.838182                                                 \n",
       "8                                           62.892318                                                 \n",
       "9                                           70.081292                                                 \n",
       "10                                          52.616052                                                 \n",
       "11                                          40.216734                                                 \n",
       "12                                          63.037865                                                 \n",
       "13                                          50.698150                                                 \n",
       "15                                           0.000000                                                 \n",
       "16                                          64.235624                                                 \n",
       "17                                           0.000000                                                 \n",
       "18                                          60.634739                                                 \n",
       "19                                          78.894375                                                 \n",
       "20                                          70.626894                                                 \n",
       "21                                           0.000000                                                 \n",
       "22                                          49.224298                                                 \n",
       "23                                          65.997726                                                 \n",
       "24                                           0.000000                                                 \n",
       "25                                          73.718854                                                 \n",
       "26                                          78.353497                                                 \n",
       "27                                          50.199310                                                 \n",
       "28                                          46.987952                                                 \n",
       "29                                           0.000000                                                 \n",
       "32                                          89.009991                                                 \n",
       "33                                          62.489365                                                 \n",
       "34                                          62.489365                                                 \n",
       "35                                           0.000000                                                 \n",
       "36                                          71.633554                                                 \n",
       "\n",
       "    Hazardous waste generated per 1,000 population (Metric tonnes/Annum)  \\\n",
       "0                                           11.279270                      \n",
       "2                                            1.337720                      \n",
       "3                                            0.138161                      \n",
       "4                                            8.557503                      \n",
       "5                                           19.110821                      \n",
       "6                                           50.116802                      \n",
       "7                                            4.658146                      \n",
       "8                                            3.738167                      \n",
       "9                                           13.001647                      \n",
       "10                                           6.335936                      \n",
       "11                                           3.048167                      \n",
       "12                                           3.025076                      \n",
       "13                                           9.236121                      \n",
       "15                                           0.152188                      \n",
       "16                                           0.000017                      \n",
       "17                                           0.009372                      \n",
       "18                                          20.678965                      \n",
       "19                                           4.110845                      \n",
       "20                                           8.147039                      \n",
       "21                                           2.226100                      \n",
       "22                                          17.262642                      \n",
       "23                                           9.925169                      \n",
       "24                                           0.073934                      \n",
       "25                                           1.119218                      \n",
       "26                                           2.171054                      \n",
       "27                                           1.924808                      \n",
       "28                                           0.000404                      \n",
       "29                                           1.536752                      \n",
       "32                                           2.176167                      \n",
       "33                                           0.206700                      \n",
       "34                                           0.206700                      \n",
       "35                                           0.716418                      \n",
       "36                                          24.071573                      \n",
       "\n",
       "    Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)  \\\n",
       "0                                           75.992319                                      \n",
       "2                                           20.915679                                      \n",
       "3                                           28.405407                                      \n",
       "4                                           19.754941                                      \n",
       "5                                            4.338928                                      \n",
       "6                                           33.099375                                      \n",
       "7                                          177.463415                                      \n",
       "8                                           65.699879                                      \n",
       "9                                            2.062399                                      \n",
       "10                                          54.790481                                      \n",
       "11                                          32.637893                                      \n",
       "12                                          67.055377                                      \n",
       "13                                          11.572251                                      \n",
       "15                                           1.848049                                      \n",
       "16                                          50.000000                                      \n",
       "17                                          50.000000                                      \n",
       "18                                          62.807815                                      \n",
       "19                                          18.016513                                      \n",
       "20                                          99.187497                                      \n",
       "21                                           0.000000                                      \n",
       "22                                          48.734607                                      \n",
       "23                                          52.250571                                      \n",
       "24                                          93.174061                                      \n",
       "25                                          60.404104                                      \n",
       "26                                          96.333486                                      \n",
       "27                                          49.912245                                      \n",
       "28                                           0.000000                                      \n",
       "29                                          43.937709                                      \n",
       "32                                           0.049333                                      \n",
       "33                                        1264.493554                                      \n",
       "34                                        1264.493554                                      \n",
       "35                                           0.000000                                      \n",
       "36                                          33.124825                                      \n",
       "\n",
       "    Plastic waste generated per 1,000 population (Tonnes/Annum)  \\\n",
       "0                                            1.274485             \n",
       "2                                            0.948150             \n",
       "3                                            0.582283             \n",
       "4                                            0.210763             \n",
       "5                                           21.238931             \n",
       "6                                            5.301223             \n",
       "7                                            2.420170             \n",
       "8                                            0.505228             \n",
       "9                                            1.388899             \n",
       "10                                           4.167701             \n",
       "11                                           3.808702             \n",
       "12                                           0.887769             \n",
       "13                                           3.374468             \n",
       "15                                           0.394688             \n",
       "16                                           0.011242             \n",
       "17                                           0.125670             \n",
       "18                                           2.013199             \n",
       "19                                           4.020830             \n",
       "20                                           1.367041             \n",
       "21                                           0.008589             \n",
       "22                                           5.315280             \n",
       "23                                           4.942335             \n",
       "24                                           0.006611             \n",
       "25                                           1.140800             \n",
       "26                                           2.812573             \n",
       "27                                           3.111255             \n",
       "28                                           4.671717             \n",
       "29                                          10.013162             \n",
       "32                                          11.492766             \n",
       "33                                           2.616473             \n",
       "34                                           2.616473             \n",
       "35                                           2.208955             \n",
       "36                                           5.694126             \n",
       "\n",
       "    Percentage of BMW treated to total quantity of BMW generated  \\\n",
       "0                                          100.000000              \n",
       "2                                           75.048046              \n",
       "3                                           28.834587              \n",
       "4                                           28.559829              \n",
       "5                                          100.000000              \n",
       "6                                          100.000000              \n",
       "7                                          100.000000              \n",
       "8                                          100.000000              \n",
       "9                                           52.553291              \n",
       "10                                         100.000000              \n",
       "11                                          58.666386              \n",
       "12                                          91.800396              \n",
       "13                                          99.545003              \n",
       "15                                         100.000000              \n",
       "16                                         100.000000              \n",
       "17                                         100.000000              \n",
       "18                                         100.000000              \n",
       "19                                         100.000000              \n",
       "20                                          75.975543              \n",
       "21                                          73.352152              \n",
       "22                                         100.000000              \n",
       "23                                         100.000000              \n",
       "24                                         100.000000              \n",
       "25                                         100.000000              \n",
       "26                                          99.124384              \n",
       "27                                         100.000000              \n",
       "28                                         100.000000              \n",
       "29                                         100.000000              \n",
       "32                                         100.000000              \n",
       "33                                          95.473020              \n",
       "34                                          95.473020              \n",
       "35                                          20.872865              \n",
       "36                                         135.052549              \n",
       "\n",
       "    Installed capacity of grid interactive bio power per 10 lakh population (MW)  \n",
       "0                                            9.635735                             \n",
       "2                                            0.057483                             \n",
       "3                                            1.023012                             \n",
       "4                                            8.376372                             \n",
       "5                                            0.218931                             \n",
       "6                                            1.117520                             \n",
       "7                                            7.252251                             \n",
       "8                                            1.249660                             \n",
       "9                                            0.112816                             \n",
       "10                                          28.397197                             \n",
       "11                                           0.064182                             \n",
       "12                                           1.465584                             \n",
       "13                                          20.998334                             \n",
       "15                                           4.227941                             \n",
       "16                                                NaN                             \n",
       "17                                                NaN                             \n",
       "18                                           1.302540                             \n",
       "19                                          16.044269                             \n",
       "20                                           1.542444                             \n",
       "21                                                NaN                             \n",
       "22                                          13.379154                             \n",
       "23                                           5.485401                             \n",
       "24                                                NaN                             \n",
       "25                                           9.248464                             \n",
       "26                                          11.510651                             \n",
       "27                                           3.273877                             \n",
       "28                                                NaN                             \n",
       "29                                                NaN                             \n",
       "32                                           2.559181                             \n",
       "33                                                NaN                             \n",
       "34                                                NaN                             \n",
       "35                                                NaN                             \n",
       "36                                                NaN                             "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2=data.dropna(subset=['Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)'])\n",
    "data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f1fc3d4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 842.4x624.24 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=data2['States/UTs']\n",
    "y=data2['Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)']\n",
    "plt.bar(x,y,align='edge',edgecolor='black',linewidth=\"2\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel(\"States & UTs\")\n",
    "plt.ylabel(\"Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "c446aca1",
   "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>SNO</th>\n",
       "      <th>Category</th>\n",
       "      <th>States/UTs</th>\n",
       "      <th>Per capita fossil fuel consumption (in kg.)</th>\n",
       "      <th>Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)</th>\n",
       "      <th>Hazardous waste generated per 1,000 population (Metric tonnes/Annum)</th>\n",
       "      <th>Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)</th>\n",
       "      <th>Plastic waste generated per 1,000 population (Tonnes/Annum)</th>\n",
       "      <th>Percentage of BMW treated to total quantity of BMW generated</th>\n",
       "      <th>Installed capacity of grid interactive bio power per 10 lakh population (MW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>State</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>158.4</td>\n",
       "      <td>59.575931</td>\n",
       "      <td>11.279270</td>\n",
       "      <td>75.992319</td>\n",
       "      <td>1.274485</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.635735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>State</td>\n",
       "      <td>Arunachal Pradesh</td>\n",
       "      <td>179.7</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.536752</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>State</td>\n",
       "      <td>Assam</td>\n",
       "      <td>88.0</td>\n",
       "      <td>66.643685</td>\n",
       "      <td>1.337720</td>\n",
       "      <td>20.915679</td>\n",
       "      <td>0.948150</td>\n",
       "      <td>75.048046</td>\n",
       "      <td>0.057483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>State</td>\n",
       "      <td>Bihar</td>\n",
       "      <td>50.5</td>\n",
       "      <td>68.584991</td>\n",
       "      <td>0.138161</td>\n",
       "      <td>28.405407</td>\n",
       "      <td>0.582283</td>\n",
       "      <td>28.834587</td>\n",
       "      <td>1.023012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>State</td>\n",
       "      <td>Chhattisgarh</td>\n",
       "      <td>160.9</td>\n",
       "      <td>56.460471</td>\n",
       "      <td>8.557503</td>\n",
       "      <td>19.754941</td>\n",
       "      <td>0.210763</td>\n",
       "      <td>28.559829</td>\n",
       "      <td>8.376372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>State</td>\n",
       "      <td>Goa</td>\n",
       "      <td>547.1</td>\n",
       "      <td>43.631436</td>\n",
       "      <td>19.110821</td>\n",
       "      <td>4.338928</td>\n",
       "      <td>21.238931</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.218931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>State</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>351.4</td>\n",
       "      <td>71.026283</td>\n",
       "      <td>50.116802</td>\n",
       "      <td>33.099375</td>\n",
       "      <td>5.301223</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.117520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>State</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>415.0</td>\n",
       "      <td>75.838182</td>\n",
       "      <td>4.658146</td>\n",
       "      <td>177.463415</td>\n",
       "      <td>2.420170</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>7.252251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>State</td>\n",
       "      <td>Himachal Pradesh</td>\n",
       "      <td>227.4</td>\n",
       "      <td>62.892318</td>\n",
       "      <td>3.738167</td>\n",
       "      <td>65.699879</td>\n",
       "      <td>0.505228</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.249660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>State</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>103.4</td>\n",
       "      <td>70.081292</td>\n",
       "      <td>13.001647</td>\n",
       "      <td>2.062399</td>\n",
       "      <td>1.388899</td>\n",
       "      <td>52.553291</td>\n",
       "      <td>0.112816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>State</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>216.0</td>\n",
       "      <td>52.616052</td>\n",
       "      <td>6.335936</td>\n",
       "      <td>54.790481</td>\n",
       "      <td>4.167701</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>28.397197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>State</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>189.9</td>\n",
       "      <td>40.216734</td>\n",
       "      <td>3.048167</td>\n",
       "      <td>32.637893</td>\n",
       "      <td>3.808702</td>\n",
       "      <td>58.666386</td>\n",
       "      <td>0.064182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>State</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>110.3</td>\n",
       "      <td>63.037865</td>\n",
       "      <td>3.025076</td>\n",
       "      <td>67.055377</td>\n",
       "      <td>0.887769</td>\n",
       "      <td>91.800396</td>\n",
       "      <td>1.465584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>State</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>187.0</td>\n",
       "      <td>50.698150</td>\n",
       "      <td>9.236121</td>\n",
       "      <td>11.572251</td>\n",
       "      <td>3.374468</td>\n",
       "      <td>99.545003</td>\n",
       "      <td>20.998334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>State</td>\n",
       "      <td>Manipur</td>\n",
       "      <td>88.5</td>\n",
       "      <td>52.853598</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.043442</td>\n",
       "      <td>79.374825</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>State</td>\n",
       "      <td>Meghalaya</td>\n",
       "      <td>166.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.152188</td>\n",
       "      <td>1.848049</td>\n",
       "      <td>0.394688</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.227941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>State</td>\n",
       "      <td>Mizoram</td>\n",
       "      <td>127.2</td>\n",
       "      <td>64.235624</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.011242</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>State</td>\n",
       "      <td>Nagaland</td>\n",
       "      <td>77.9</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009372</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.125670</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>State</td>\n",
       "      <td>Odisha</td>\n",
       "      <td>141.4</td>\n",
       "      <td>60.634739</td>\n",
       "      <td>20.678965</td>\n",
       "      <td>62.807815</td>\n",
       "      <td>2.013199</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.302540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>State</td>\n",
       "      <td>Punjab</td>\n",
       "      <td>255.0</td>\n",
       "      <td>78.894375</td>\n",
       "      <td>4.110845</td>\n",
       "      <td>18.016513</td>\n",
       "      <td>4.020830</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>16.044269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>State</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>166.2</td>\n",
       "      <td>70.626894</td>\n",
       "      <td>8.147039</td>\n",
       "      <td>99.187497</td>\n",
       "      <td>1.367041</td>\n",
       "      <td>75.975543</td>\n",
       "      <td>1.542444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>State</td>\n",
       "      <td>Sikkim</td>\n",
       "      <td>207.1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.226100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008589</td>\n",
       "      <td>73.352152</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>State</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>199.9</td>\n",
       "      <td>49.224298</td>\n",
       "      <td>17.262642</td>\n",
       "      <td>48.734607</td>\n",
       "      <td>5.315280</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>13.379154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>State</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>198.4</td>\n",
       "      <td>65.997726</td>\n",
       "      <td>9.925169</td>\n",
       "      <td>52.250571</td>\n",
       "      <td>4.942335</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>5.485401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>State</td>\n",
       "      <td>Tripura</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.073934</td>\n",
       "      <td>93.174061</td>\n",
       "      <td>0.006611</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>91.1</td>\n",
       "      <td>73.718854</td>\n",
       "      <td>1.119218</td>\n",
       "      <td>60.404104</td>\n",
       "      <td>1.140800</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.248464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttarakhand</td>\n",
       "      <td>170.6</td>\n",
       "      <td>78.353497</td>\n",
       "      <td>2.171054</td>\n",
       "      <td>96.333486</td>\n",
       "      <td>2.812573</td>\n",
       "      <td>99.124384</td>\n",
       "      <td>11.510651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>State</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>96.2</td>\n",
       "      <td>50.199310</td>\n",
       "      <td>1.924808</td>\n",
       "      <td>49.912245</td>\n",
       "      <td>3.111255</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.273877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>558.0</td>\n",
       "      <td>46.987952</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.671717</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>412.6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.536752</td>\n",
       "      <td>43.937709</td>\n",
       "      <td>10.013162</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Dadra and Nagar Haveli</td>\n",
       "      <td>1160.5</td>\n",
       "      <td>65.217391</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.117065</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Daman and Diu</td>\n",
       "      <td>909.7</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.117065</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>291.9</td>\n",
       "      <td>89.009991</td>\n",
       "      <td>2.176167</td>\n",
       "      <td>0.049333</td>\n",
       "      <td>11.492766</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.559181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Jammu and Kashmir</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Ladakh</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Lakshadweep</td>\n",
       "      <td>235.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.716418</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.208955</td>\n",
       "      <td>20.872865</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Puducherry</td>\n",
       "      <td>435.6</td>\n",
       "      <td>71.633554</td>\n",
       "      <td>24.071573</td>\n",
       "      <td>33.124825</td>\n",
       "      <td>5.694126</td>\n",
       "      <td>135.052549</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SNO         Category                   States/UTs  \\\n",
       "0     1            State               Andhra Pradesh   \n",
       "1     2            State            Arunachal Pradesh   \n",
       "2     3            State                        Assam   \n",
       "3     4            State                        Bihar   \n",
       "4     5            State                 Chhattisgarh   \n",
       "5     6            State                          Goa   \n",
       "6     7            State                      Gujarat   \n",
       "7     8            State                      Haryana   \n",
       "8     9            State             Himachal Pradesh   \n",
       "9    10            State                    Jharkhand   \n",
       "10   11            State                    Karnataka   \n",
       "11   12            State                       Kerala   \n",
       "12   13            State               Madhya Pradesh   \n",
       "13   14            State                  Maharashtra   \n",
       "14   15            State                      Manipur   \n",
       "15   16            State                    Meghalaya   \n",
       "16   17            State                      Mizoram   \n",
       "17   18            State                     Nagaland   \n",
       "18   19            State                       Odisha   \n",
       "19   20            State                       Punjab   \n",
       "20   21            State                    Rajasthan   \n",
       "21   22            State                       Sikkim   \n",
       "22   23            State                   Tamil Nadu   \n",
       "23   24            State                    Telangana   \n",
       "24   25            State                      Tripura   \n",
       "25   26            State                Uttar Pradesh   \n",
       "26   27            State                  Uttarakhand   \n",
       "27   28            State                  West Bengal   \n",
       "28   29  Union Territory  Andaman and Nicobar Islands   \n",
       "29   30  Union Territory                   Chandigarh   \n",
       "30   31  Union Territory       Dadra and Nagar Haveli   \n",
       "31   32  Union Territory                Daman and Diu   \n",
       "32   33  Union Territory                        Delhi   \n",
       "33   34  Union Territory            Jammu and Kashmir   \n",
       "34   35  Union Territory                      Ladakh    \n",
       "35   36  Union Territory                  Lakshadweep   \n",
       "36   37  Union Territory                   Puducherry   \n",
       "\n",
       "    Per capita fossil fuel consumption (in kg.)  \\\n",
       "0                                         158.4   \n",
       "1                                         179.7   \n",
       "2                                          88.0   \n",
       "3                                          50.5   \n",
       "4                                         160.9   \n",
       "5                                         547.1   \n",
       "6                                         351.4   \n",
       "7                                         415.0   \n",
       "8                                         227.4   \n",
       "9                                         103.4   \n",
       "10                                        216.0   \n",
       "11                                        189.9   \n",
       "12                                        110.3   \n",
       "13                                        187.0   \n",
       "14                                         88.5   \n",
       "15                                        166.0   \n",
       "16                                        127.2   \n",
       "17                                         77.9   \n",
       "18                                        141.4   \n",
       "19                                        255.0   \n",
       "20                                        166.2   \n",
       "21                                        207.1   \n",
       "22                                        199.9   \n",
       "23                                        198.4   \n",
       "24                                         64.0   \n",
       "25                                         91.1   \n",
       "26                                        170.6   \n",
       "27                                         96.2   \n",
       "28                                        558.0   \n",
       "29                                        412.6   \n",
       "30                                       1160.5   \n",
       "31                                        909.7   \n",
       "32                                        291.9   \n",
       "33                                        119.7   \n",
       "34                                        119.7   \n",
       "35                                        235.0   \n",
       "36                                        435.6   \n",
       "\n",
       "    Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)  \\\n",
       "0                                           59.575931                                                 \n",
       "1                                            0.000000                                                 \n",
       "2                                           66.643685                                                 \n",
       "3                                           68.584991                                                 \n",
       "4                                           56.460471                                                 \n",
       "5                                           43.631436                                                 \n",
       "6                                           71.026283                                                 \n",
       "7                                           75.838182                                                 \n",
       "8                                           62.892318                                                 \n",
       "9                                           70.081292                                                 \n",
       "10                                          52.616052                                                 \n",
       "11                                          40.216734                                                 \n",
       "12                                          63.037865                                                 \n",
       "13                                          50.698150                                                 \n",
       "14                                          52.853598                                                 \n",
       "15                                           0.000000                                                 \n",
       "16                                          64.235624                                                 \n",
       "17                                           0.000000                                                 \n",
       "18                                          60.634739                                                 \n",
       "19                                          78.894375                                                 \n",
       "20                                          70.626894                                                 \n",
       "21                                           0.000000                                                 \n",
       "22                                          49.224298                                                 \n",
       "23                                          65.997726                                                 \n",
       "24                                           0.000000                                                 \n",
       "25                                          73.718854                                                 \n",
       "26                                          78.353497                                                 \n",
       "27                                          50.199310                                                 \n",
       "28                                          46.987952                                                 \n",
       "29                                           0.000000                                                 \n",
       "30                                          65.217391                                                 \n",
       "31                                          93.333333                                                 \n",
       "32                                          89.009991                                                 \n",
       "33                                          62.489365                                                 \n",
       "34                                          62.489365                                                 \n",
       "35                                           0.000000                                                 \n",
       "36                                          71.633554                                                 \n",
       "\n",
       "    Hazardous waste generated per 1,000 population (Metric tonnes/Annum)  \\\n",
       "0                                           11.279270                      \n",
       "1                                                 NaN                      \n",
       "2                                            1.337720                      \n",
       "3                                            0.138161                      \n",
       "4                                            8.557503                      \n",
       "5                                           19.110821                      \n",
       "6                                           50.116802                      \n",
       "7                                            4.658146                      \n",
       "8                                            3.738167                      \n",
       "9                                           13.001647                      \n",
       "10                                           6.335936                      \n",
       "11                                           3.048167                      \n",
       "12                                           3.025076                      \n",
       "13                                           9.236121                      \n",
       "14                                                NaN                      \n",
       "15                                           0.152188                      \n",
       "16                                           0.000017                      \n",
       "17                                           0.009372                      \n",
       "18                                          20.678965                      \n",
       "19                                           4.110845                      \n",
       "20                                           8.147039                      \n",
       "21                                           2.226100                      \n",
       "22                                          17.262642                      \n",
       "23                                           9.925169                      \n",
       "24                                           0.073934                      \n",
       "25                                           1.119218                      \n",
       "26                                           2.171054                      \n",
       "27                                           1.924808                      \n",
       "28                                           0.000404                      \n",
       "29                                           1.536752                      \n",
       "30                                                NaN                      \n",
       "31                                                NaN                      \n",
       "32                                           2.176167                      \n",
       "33                                           0.206700                      \n",
       "34                                           0.206700                      \n",
       "35                                           0.716418                      \n",
       "36                                          24.071573                      \n",
       "\n",
       "    Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)  \\\n",
       "0                                           75.992319                                      \n",
       "1                                                 NaN                                      \n",
       "2                                           20.915679                                      \n",
       "3                                           28.405407                                      \n",
       "4                                           19.754941                                      \n",
       "5                                            4.338928                                      \n",
       "6                                           33.099375                                      \n",
       "7                                          177.463415                                      \n",
       "8                                           65.699879                                      \n",
       "9                                            2.062399                                      \n",
       "10                                          54.790481                                      \n",
       "11                                          32.637893                                      \n",
       "12                                          67.055377                                      \n",
       "13                                          11.572251                                      \n",
       "14                                                NaN                                      \n",
       "15                                           1.848049                                      \n",
       "16                                          50.000000                                      \n",
       "17                                          50.000000                                      \n",
       "18                                          62.807815                                      \n",
       "19                                          18.016513                                      \n",
       "20                                          99.187497                                      \n",
       "21                                           0.000000                                      \n",
       "22                                          48.734607                                      \n",
       "23                                          52.250571                                      \n",
       "24                                          93.174061                                      \n",
       "25                                          60.404104                                      \n",
       "26                                          96.333486                                      \n",
       "27                                          49.912245                                      \n",
       "28                                           0.000000                                      \n",
       "29                                          43.937709                                      \n",
       "30                                                NaN                                      \n",
       "31                                                NaN                                      \n",
       "32                                           0.049333                                      \n",
       "33                                        1264.493554                                      \n",
       "34                                        1264.493554                                      \n",
       "35                                           0.000000                                      \n",
       "36                                          33.124825                                      \n",
       "\n",
       "    Plastic waste generated per 1,000 population (Tonnes/Annum)  \\\n",
       "0                                            1.274485             \n",
       "1                                            2.536752             \n",
       "2                                            0.948150             \n",
       "3                                            0.582283             \n",
       "4                                            0.210763             \n",
       "5                                           21.238931             \n",
       "6                                            5.301223             \n",
       "7                                            2.420170             \n",
       "8                                            0.505228             \n",
       "9                                            1.388899             \n",
       "10                                           4.167701             \n",
       "11                                           3.808702             \n",
       "12                                           0.887769             \n",
       "13                                           3.374468             \n",
       "14                                           4.043442             \n",
       "15                                           0.394688             \n",
       "16                                           0.011242             \n",
       "17                                           0.125670             \n",
       "18                                           2.013199             \n",
       "19                                           4.020830             \n",
       "20                                           1.367041             \n",
       "21                                           0.008589             \n",
       "22                                           5.315280             \n",
       "23                                           4.942335             \n",
       "24                                           0.006611             \n",
       "25                                           1.140800             \n",
       "26                                           2.812573             \n",
       "27                                           3.111255             \n",
       "28                                           4.671717             \n",
       "29                                          10.013162             \n",
       "30                                           2.117065             \n",
       "31                                           2.117065             \n",
       "32                                          11.492766             \n",
       "33                                           2.616473             \n",
       "34                                           2.616473             \n",
       "35                                           2.208955             \n",
       "36                                           5.694126             \n",
       "\n",
       "    Percentage of BMW treated to total quantity of BMW generated  \\\n",
       "0                                          100.000000              \n",
       "1                                          100.000000              \n",
       "2                                           75.048046              \n",
       "3                                           28.834587              \n",
       "4                                           28.559829              \n",
       "5                                          100.000000              \n",
       "6                                          100.000000              \n",
       "7                                          100.000000              \n",
       "8                                          100.000000              \n",
       "9                                           52.553291              \n",
       "10                                         100.000000              \n",
       "11                                          58.666386              \n",
       "12                                          91.800396              \n",
       "13                                          99.545003              \n",
       "14                                          79.374825              \n",
       "15                                         100.000000              \n",
       "16                                         100.000000              \n",
       "17                                         100.000000              \n",
       "18                                         100.000000              \n",
       "19                                         100.000000              \n",
       "20                                          75.975543              \n",
       "21                                          73.352152              \n",
       "22                                         100.000000              \n",
       "23                                         100.000000              \n",
       "24                                         100.000000              \n",
       "25                                         100.000000              \n",
       "26                                          99.124384              \n",
       "27                                         100.000000              \n",
       "28                                         100.000000              \n",
       "29                                         100.000000              \n",
       "30                                         100.000000              \n",
       "31                                         100.000000              \n",
       "32                                         100.000000              \n",
       "33                                          95.473020              \n",
       "34                                          95.473020              \n",
       "35                                          20.872865              \n",
       "36                                         135.052549              \n",
       "\n",
       "    Installed capacity of grid interactive bio power per 10 lakh population (MW)  \n",
       "0                                            9.635735                             \n",
       "1                                            0.000000                             \n",
       "2                                            0.057483                             \n",
       "3                                            1.023012                             \n",
       "4                                            8.376372                             \n",
       "5                                            0.218931                             \n",
       "6                                            1.117520                             \n",
       "7                                            7.252251                             \n",
       "8                                            1.249660                             \n",
       "9                                            0.112816                             \n",
       "10                                          28.397197                             \n",
       "11                                           0.064182                             \n",
       "12                                           1.465584                             \n",
       "13                                          20.998334                             \n",
       "14                                                NaN                             \n",
       "15                                           4.227941                             \n",
       "16                                                NaN                             \n",
       "17                                                NaN                             \n",
       "18                                           1.302540                             \n",
       "19                                          16.044269                             \n",
       "20                                           1.542444                             \n",
       "21                                                NaN                             \n",
       "22                                          13.379154                             \n",
       "23                                           5.485401                             \n",
       "24                                                NaN                             \n",
       "25                                           9.248464                             \n",
       "26                                          11.510651                             \n",
       "27                                           3.273877                             \n",
       "28                                                NaN                             \n",
       "29                                                NaN                             \n",
       "30                                                NaN                             \n",
       "31                                                NaN                             \n",
       "32                                           2.559181                             \n",
       "33                                                NaN                             \n",
       "34                                                NaN                             \n",
       "35                                                NaN                             \n",
       "36                                                NaN                             "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3=data.dropna(subset=['Plastic waste generated per 1,000 population (Tonnes/Annum)'])\n",
    "data3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3b42a46f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Plastic waste generated per 1,000 population (Tonnes/Annum)')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 842.4x624.24 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=data3['States/UTs']\n",
    "y=data3['Plastic waste generated per 1,000 population (Tonnes/Annum)']\n",
    "plt.bar(x,y,align='edge',edgecolor='black',linewidth=\"2\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel(\"States & UTs\")\n",
    "plt.ylabel(\"Plastic waste generated per 1,000 population (Tonnes/Annum)\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6fe8d90c",
   "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>SNO</th>\n",
       "      <th>Category</th>\n",
       "      <th>States/UTs</th>\n",
       "      <th>Per capita fossil fuel consumption (in kg.)</th>\n",
       "      <th>Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)</th>\n",
       "      <th>Hazardous waste generated per 1,000 population (Metric tonnes/Annum)</th>\n",
       "      <th>Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)</th>\n",
       "      <th>Plastic waste generated per 1,000 population (Tonnes/Annum)</th>\n",
       "      <th>Percentage of BMW treated to total quantity of BMW generated</th>\n",
       "      <th>Installed capacity of grid interactive bio power per 10 lakh population (MW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>State</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>158.4</td>\n",
       "      <td>59.575931</td>\n",
       "      <td>11.279270</td>\n",
       "      <td>75.992319</td>\n",
       "      <td>1.274485</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.635735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>State</td>\n",
       "      <td>Arunachal Pradesh</td>\n",
       "      <td>179.7</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.536752</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>State</td>\n",
       "      <td>Assam</td>\n",
       "      <td>88.0</td>\n",
       "      <td>66.643685</td>\n",
       "      <td>1.337720</td>\n",
       "      <td>20.915679</td>\n",
       "      <td>0.948150</td>\n",
       "      <td>75.048046</td>\n",
       "      <td>0.057483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>State</td>\n",
       "      <td>Bihar</td>\n",
       "      <td>50.5</td>\n",
       "      <td>68.584991</td>\n",
       "      <td>0.138161</td>\n",
       "      <td>28.405407</td>\n",
       "      <td>0.582283</td>\n",
       "      <td>28.834587</td>\n",
       "      <td>1.023012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>State</td>\n",
       "      <td>Chhattisgarh</td>\n",
       "      <td>160.9</td>\n",
       "      <td>56.460471</td>\n",
       "      <td>8.557503</td>\n",
       "      <td>19.754941</td>\n",
       "      <td>0.210763</td>\n",
       "      <td>28.559829</td>\n",
       "      <td>8.376372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>State</td>\n",
       "      <td>Goa</td>\n",
       "      <td>547.1</td>\n",
       "      <td>43.631436</td>\n",
       "      <td>19.110821</td>\n",
       "      <td>4.338928</td>\n",
       "      <td>21.238931</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.218931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>State</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>351.4</td>\n",
       "      <td>71.026283</td>\n",
       "      <td>50.116802</td>\n",
       "      <td>33.099375</td>\n",
       "      <td>5.301223</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.117520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>State</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>415.0</td>\n",
       "      <td>75.838182</td>\n",
       "      <td>4.658146</td>\n",
       "      <td>177.463415</td>\n",
       "      <td>2.420170</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>7.252251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>State</td>\n",
       "      <td>Himachal Pradesh</td>\n",
       "      <td>227.4</td>\n",
       "      <td>62.892318</td>\n",
       "      <td>3.738167</td>\n",
       "      <td>65.699879</td>\n",
       "      <td>0.505228</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.249660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>State</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>103.4</td>\n",
       "      <td>70.081292</td>\n",
       "      <td>13.001647</td>\n",
       "      <td>2.062399</td>\n",
       "      <td>1.388899</td>\n",
       "      <td>52.553291</td>\n",
       "      <td>0.112816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>State</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>216.0</td>\n",
       "      <td>52.616052</td>\n",
       "      <td>6.335936</td>\n",
       "      <td>54.790481</td>\n",
       "      <td>4.167701</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>28.397197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>State</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>189.9</td>\n",
       "      <td>40.216734</td>\n",
       "      <td>3.048167</td>\n",
       "      <td>32.637893</td>\n",
       "      <td>3.808702</td>\n",
       "      <td>58.666386</td>\n",
       "      <td>0.064182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>State</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>110.3</td>\n",
       "      <td>63.037865</td>\n",
       "      <td>3.025076</td>\n",
       "      <td>67.055377</td>\n",
       "      <td>0.887769</td>\n",
       "      <td>91.800396</td>\n",
       "      <td>1.465584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>State</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>187.0</td>\n",
       "      <td>50.698150</td>\n",
       "      <td>9.236121</td>\n",
       "      <td>11.572251</td>\n",
       "      <td>3.374468</td>\n",
       "      <td>99.545003</td>\n",
       "      <td>20.998334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>State</td>\n",
       "      <td>Manipur</td>\n",
       "      <td>88.5</td>\n",
       "      <td>52.853598</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.043442</td>\n",
       "      <td>79.374825</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>State</td>\n",
       "      <td>Meghalaya</td>\n",
       "      <td>166.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.152188</td>\n",
       "      <td>1.848049</td>\n",
       "      <td>0.394688</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.227941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>State</td>\n",
       "      <td>Mizoram</td>\n",
       "      <td>127.2</td>\n",
       "      <td>64.235624</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.011242</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>State</td>\n",
       "      <td>Nagaland</td>\n",
       "      <td>77.9</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009372</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.125670</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>State</td>\n",
       "      <td>Odisha</td>\n",
       "      <td>141.4</td>\n",
       "      <td>60.634739</td>\n",
       "      <td>20.678965</td>\n",
       "      <td>62.807815</td>\n",
       "      <td>2.013199</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.302540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>State</td>\n",
       "      <td>Punjab</td>\n",
       "      <td>255.0</td>\n",
       "      <td>78.894375</td>\n",
       "      <td>4.110845</td>\n",
       "      <td>18.016513</td>\n",
       "      <td>4.020830</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>16.044269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>State</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>166.2</td>\n",
       "      <td>70.626894</td>\n",
       "      <td>8.147039</td>\n",
       "      <td>99.187497</td>\n",
       "      <td>1.367041</td>\n",
       "      <td>75.975543</td>\n",
       "      <td>1.542444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>State</td>\n",
       "      <td>Sikkim</td>\n",
       "      <td>207.1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.226100</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008589</td>\n",
       "      <td>73.352152</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>State</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>199.9</td>\n",
       "      <td>49.224298</td>\n",
       "      <td>17.262642</td>\n",
       "      <td>48.734607</td>\n",
       "      <td>5.315280</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>13.379154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>State</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>198.4</td>\n",
       "      <td>65.997726</td>\n",
       "      <td>9.925169</td>\n",
       "      <td>52.250571</td>\n",
       "      <td>4.942335</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>5.485401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>State</td>\n",
       "      <td>Tripura</td>\n",
       "      <td>64.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.073934</td>\n",
       "      <td>93.174061</td>\n",
       "      <td>0.006611</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>91.1</td>\n",
       "      <td>73.718854</td>\n",
       "      <td>1.119218</td>\n",
       "      <td>60.404104</td>\n",
       "      <td>1.140800</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.248464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttarakhand</td>\n",
       "      <td>170.6</td>\n",
       "      <td>78.353497</td>\n",
       "      <td>2.171054</td>\n",
       "      <td>96.333486</td>\n",
       "      <td>2.812573</td>\n",
       "      <td>99.124384</td>\n",
       "      <td>11.510651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>State</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>96.2</td>\n",
       "      <td>50.199310</td>\n",
       "      <td>1.924808</td>\n",
       "      <td>49.912245</td>\n",
       "      <td>3.111255</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.273877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Andaman and Nicobar Islands</td>\n",
       "      <td>558.0</td>\n",
       "      <td>46.987952</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.671717</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>412.6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.536752</td>\n",
       "      <td>43.937709</td>\n",
       "      <td>10.013162</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Dadra and Nagar Haveli</td>\n",
       "      <td>1160.5</td>\n",
       "      <td>65.217391</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.117065</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Daman and Diu</td>\n",
       "      <td>909.7</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.117065</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>291.9</td>\n",
       "      <td>89.009991</td>\n",
       "      <td>2.176167</td>\n",
       "      <td>0.049333</td>\n",
       "      <td>11.492766</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.559181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Jammu and Kashmir</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Ladakh</td>\n",
       "      <td>119.7</td>\n",
       "      <td>62.489365</td>\n",
       "      <td>0.206700</td>\n",
       "      <td>1264.493554</td>\n",
       "      <td>2.616473</td>\n",
       "      <td>95.473020</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Lakshadweep</td>\n",
       "      <td>235.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.716418</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.208955</td>\n",
       "      <td>20.872865</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Puducherry</td>\n",
       "      <td>435.6</td>\n",
       "      <td>71.633554</td>\n",
       "      <td>24.071573</td>\n",
       "      <td>33.124825</td>\n",
       "      <td>5.694126</td>\n",
       "      <td>135.052549</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SNO         Category                   States/UTs  \\\n",
       "0     1            State               Andhra Pradesh   \n",
       "1     2            State            Arunachal Pradesh   \n",
       "2     3            State                        Assam   \n",
       "3     4            State                        Bihar   \n",
       "4     5            State                 Chhattisgarh   \n",
       "5     6            State                          Goa   \n",
       "6     7            State                      Gujarat   \n",
       "7     8            State                      Haryana   \n",
       "8     9            State             Himachal Pradesh   \n",
       "9    10            State                    Jharkhand   \n",
       "10   11            State                    Karnataka   \n",
       "11   12            State                       Kerala   \n",
       "12   13            State               Madhya Pradesh   \n",
       "13   14            State                  Maharashtra   \n",
       "14   15            State                      Manipur   \n",
       "15   16            State                    Meghalaya   \n",
       "16   17            State                      Mizoram   \n",
       "17   18            State                     Nagaland   \n",
       "18   19            State                       Odisha   \n",
       "19   20            State                       Punjab   \n",
       "20   21            State                    Rajasthan   \n",
       "21   22            State                       Sikkim   \n",
       "22   23            State                   Tamil Nadu   \n",
       "23   24            State                    Telangana   \n",
       "24   25            State                      Tripura   \n",
       "25   26            State                Uttar Pradesh   \n",
       "26   27            State                  Uttarakhand   \n",
       "27   28            State                  West Bengal   \n",
       "28   29  Union Territory  Andaman and Nicobar Islands   \n",
       "29   30  Union Territory                   Chandigarh   \n",
       "30   31  Union Territory       Dadra and Nagar Haveli   \n",
       "31   32  Union Territory                Daman and Diu   \n",
       "32   33  Union Territory                        Delhi   \n",
       "33   34  Union Territory            Jammu and Kashmir   \n",
       "34   35  Union Territory                      Ladakh    \n",
       "35   36  Union Territory                  Lakshadweep   \n",
       "36   37  Union Territory                   Puducherry   \n",
       "\n",
       "    Per capita fossil fuel consumption (in kg.)  \\\n",
       "0                                         158.4   \n",
       "1                                         179.7   \n",
       "2                                          88.0   \n",
       "3                                          50.5   \n",
       "4                                         160.9   \n",
       "5                                         547.1   \n",
       "6                                         351.4   \n",
       "7                                         415.0   \n",
       "8                                         227.4   \n",
       "9                                         103.4   \n",
       "10                                        216.0   \n",
       "11                                        189.9   \n",
       "12                                        110.3   \n",
       "13                                        187.0   \n",
       "14                                         88.5   \n",
       "15                                        166.0   \n",
       "16                                        127.2   \n",
       "17                                         77.9   \n",
       "18                                        141.4   \n",
       "19                                        255.0   \n",
       "20                                        166.2   \n",
       "21                                        207.1   \n",
       "22                                        199.9   \n",
       "23                                        198.4   \n",
       "24                                         64.0   \n",
       "25                                         91.1   \n",
       "26                                        170.6   \n",
       "27                                         96.2   \n",
       "28                                        558.0   \n",
       "29                                        412.6   \n",
       "30                                       1160.5   \n",
       "31                                        909.7   \n",
       "32                                        291.9   \n",
       "33                                        119.7   \n",
       "34                                        119.7   \n",
       "35                                        235.0   \n",
       "36                                        435.6   \n",
       "\n",
       "    Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)  \\\n",
       "0                                           59.575931                                                 \n",
       "1                                            0.000000                                                 \n",
       "2                                           66.643685                                                 \n",
       "3                                           68.584991                                                 \n",
       "4                                           56.460471                                                 \n",
       "5                                           43.631436                                                 \n",
       "6                                           71.026283                                                 \n",
       "7                                           75.838182                                                 \n",
       "8                                           62.892318                                                 \n",
       "9                                           70.081292                                                 \n",
       "10                                          52.616052                                                 \n",
       "11                                          40.216734                                                 \n",
       "12                                          63.037865                                                 \n",
       "13                                          50.698150                                                 \n",
       "14                                          52.853598                                                 \n",
       "15                                           0.000000                                                 \n",
       "16                                          64.235624                                                 \n",
       "17                                           0.000000                                                 \n",
       "18                                          60.634739                                                 \n",
       "19                                          78.894375                                                 \n",
       "20                                          70.626894                                                 \n",
       "21                                           0.000000                                                 \n",
       "22                                          49.224298                                                 \n",
       "23                                          65.997726                                                 \n",
       "24                                           0.000000                                                 \n",
       "25                                          73.718854                                                 \n",
       "26                                          78.353497                                                 \n",
       "27                                          50.199310                                                 \n",
       "28                                          46.987952                                                 \n",
       "29                                           0.000000                                                 \n",
       "30                                          65.217391                                                 \n",
       "31                                          93.333333                                                 \n",
       "32                                          89.009991                                                 \n",
       "33                                          62.489365                                                 \n",
       "34                                          62.489365                                                 \n",
       "35                                           0.000000                                                 \n",
       "36                                          71.633554                                                 \n",
       "\n",
       "    Hazardous waste generated per 1,000 population (Metric tonnes/Annum)  \\\n",
       "0                                           11.279270                      \n",
       "1                                                 NaN                      \n",
       "2                                            1.337720                      \n",
       "3                                            0.138161                      \n",
       "4                                            8.557503                      \n",
       "5                                           19.110821                      \n",
       "6                                           50.116802                      \n",
       "7                                            4.658146                      \n",
       "8                                            3.738167                      \n",
       "9                                           13.001647                      \n",
       "10                                           6.335936                      \n",
       "11                                           3.048167                      \n",
       "12                                           3.025076                      \n",
       "13                                           9.236121                      \n",
       "14                                                NaN                      \n",
       "15                                           0.152188                      \n",
       "16                                           0.000017                      \n",
       "17                                           0.009372                      \n",
       "18                                          20.678965                      \n",
       "19                                           4.110845                      \n",
       "20                                           8.147039                      \n",
       "21                                           2.226100                      \n",
       "22                                          17.262642                      \n",
       "23                                           9.925169                      \n",
       "24                                           0.073934                      \n",
       "25                                           1.119218                      \n",
       "26                                           2.171054                      \n",
       "27                                           1.924808                      \n",
       "28                                           0.000404                      \n",
       "29                                           1.536752                      \n",
       "30                                                NaN                      \n",
       "31                                                NaN                      \n",
       "32                                           2.176167                      \n",
       "33                                           0.206700                      \n",
       "34                                           0.206700                      \n",
       "35                                           0.716418                      \n",
       "36                                          24.071573                      \n",
       "\n",
       "    Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)  \\\n",
       "0                                           75.992319                                      \n",
       "1                                                 NaN                                      \n",
       "2                                           20.915679                                      \n",
       "3                                           28.405407                                      \n",
       "4                                           19.754941                                      \n",
       "5                                            4.338928                                      \n",
       "6                                           33.099375                                      \n",
       "7                                          177.463415                                      \n",
       "8                                           65.699879                                      \n",
       "9                                            2.062399                                      \n",
       "10                                          54.790481                                      \n",
       "11                                          32.637893                                      \n",
       "12                                          67.055377                                      \n",
       "13                                          11.572251                                      \n",
       "14                                                NaN                                      \n",
       "15                                           1.848049                                      \n",
       "16                                          50.000000                                      \n",
       "17                                          50.000000                                      \n",
       "18                                          62.807815                                      \n",
       "19                                          18.016513                                      \n",
       "20                                          99.187497                                      \n",
       "21                                           0.000000                                      \n",
       "22                                          48.734607                                      \n",
       "23                                          52.250571                                      \n",
       "24                                          93.174061                                      \n",
       "25                                          60.404104                                      \n",
       "26                                          96.333486                                      \n",
       "27                                          49.912245                                      \n",
       "28                                           0.000000                                      \n",
       "29                                          43.937709                                      \n",
       "30                                                NaN                                      \n",
       "31                                                NaN                                      \n",
       "32                                           0.049333                                      \n",
       "33                                        1264.493554                                      \n",
       "34                                        1264.493554                                      \n",
       "35                                           0.000000                                      \n",
       "36                                          33.124825                                      \n",
       "\n",
       "    Plastic waste generated per 1,000 population (Tonnes/Annum)  \\\n",
       "0                                            1.274485             \n",
       "1                                            2.536752             \n",
       "2                                            0.948150             \n",
       "3                                            0.582283             \n",
       "4                                            0.210763             \n",
       "5                                           21.238931             \n",
       "6                                            5.301223             \n",
       "7                                            2.420170             \n",
       "8                                            0.505228             \n",
       "9                                            1.388899             \n",
       "10                                           4.167701             \n",
       "11                                           3.808702             \n",
       "12                                           0.887769             \n",
       "13                                           3.374468             \n",
       "14                                           4.043442             \n",
       "15                                           0.394688             \n",
       "16                                           0.011242             \n",
       "17                                           0.125670             \n",
       "18                                           2.013199             \n",
       "19                                           4.020830             \n",
       "20                                           1.367041             \n",
       "21                                           0.008589             \n",
       "22                                           5.315280             \n",
       "23                                           4.942335             \n",
       "24                                           0.006611             \n",
       "25                                           1.140800             \n",
       "26                                           2.812573             \n",
       "27                                           3.111255             \n",
       "28                                           4.671717             \n",
       "29                                          10.013162             \n",
       "30                                           2.117065             \n",
       "31                                           2.117065             \n",
       "32                                          11.492766             \n",
       "33                                           2.616473             \n",
       "34                                           2.616473             \n",
       "35                                           2.208955             \n",
       "36                                           5.694126             \n",
       "\n",
       "    Percentage of BMW treated to total quantity of BMW generated  \\\n",
       "0                                          100.000000              \n",
       "1                                          100.000000              \n",
       "2                                           75.048046              \n",
       "3                                           28.834587              \n",
       "4                                           28.559829              \n",
       "5                                          100.000000              \n",
       "6                                          100.000000              \n",
       "7                                          100.000000              \n",
       "8                                          100.000000              \n",
       "9                                           52.553291              \n",
       "10                                         100.000000              \n",
       "11                                          58.666386              \n",
       "12                                          91.800396              \n",
       "13                                          99.545003              \n",
       "14                                          79.374825              \n",
       "15                                         100.000000              \n",
       "16                                         100.000000              \n",
       "17                                         100.000000              \n",
       "18                                         100.000000              \n",
       "19                                         100.000000              \n",
       "20                                          75.975543              \n",
       "21                                          73.352152              \n",
       "22                                         100.000000              \n",
       "23                                         100.000000              \n",
       "24                                         100.000000              \n",
       "25                                         100.000000              \n",
       "26                                          99.124384              \n",
       "27                                         100.000000              \n",
       "28                                         100.000000              \n",
       "29                                         100.000000              \n",
       "30                                         100.000000              \n",
       "31                                         100.000000              \n",
       "32                                         100.000000              \n",
       "33                                          95.473020              \n",
       "34                                          95.473020              \n",
       "35                                          20.872865              \n",
       "36                                         135.052549              \n",
       "\n",
       "    Installed capacity of grid interactive bio power per 10 lakh population (MW)  \n",
       "0                                            9.635735                             \n",
       "1                                            0.000000                             \n",
       "2                                            0.057483                             \n",
       "3                                            1.023012                             \n",
       "4                                            8.376372                             \n",
       "5                                            0.218931                             \n",
       "6                                            1.117520                             \n",
       "7                                            7.252251                             \n",
       "8                                            1.249660                             \n",
       "9                                            0.112816                             \n",
       "10                                          28.397197                             \n",
       "11                                           0.064182                             \n",
       "12                                           1.465584                             \n",
       "13                                          20.998334                             \n",
       "14                                                NaN                             \n",
       "15                                           4.227941                             \n",
       "16                                                NaN                             \n",
       "17                                                NaN                             \n",
       "18                                           1.302540                             \n",
       "19                                          16.044269                             \n",
       "20                                           1.542444                             \n",
       "21                                                NaN                             \n",
       "22                                          13.379154                             \n",
       "23                                           5.485401                             \n",
       "24                                                NaN                             \n",
       "25                                           9.248464                             \n",
       "26                                          11.510651                             \n",
       "27                                           3.273877                             \n",
       "28                                                NaN                             \n",
       "29                                                NaN                             \n",
       "30                                                NaN                             \n",
       "31                                                NaN                             \n",
       "32                                           2.559181                             \n",
       "33                                                NaN                             \n",
       "34                                                NaN                             \n",
       "35                                                NaN                             \n",
       "36                                                NaN                             "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data4=data.dropna(subset=['Percentage of BMW treated to total quantity of BMW generated'])\n",
    "data4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "f506764b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Percentage of BMW treated to total quantity of BMW generated')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 842.4x624.24 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=data4['States/UTs']\n",
    "y=data4['Percentage of BMW treated to total quantity of BMW generated']\n",
    "plt.bar(x,y,align='edge',edgecolor='black',linewidth=\"2\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel(\"States & UTs\")\n",
    "plt.ylabel(\"Percentage of BMW treated to total quantity of BMW generated\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "9d2a0ce8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SNO', 'Category', 'States/UTs',\n",
       "       'Per capita fossil fuel consumption (in kg.)',\n",
       "       'Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)',\n",
       "       'Hazardous waste generated per 1,000 population (Metric tonnes/Annum)',\n",
       "       'Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)',\n",
       "       'Plastic waste generated per 1,000 population (Tonnes/Annum)',\n",
       "       'Percentage of BMW treated to total quantity of BMW generated',\n",
       "       'Installed capacity of grid interactive bio power per 10 lakh population (MW)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "fdf4c26d",
   "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>SNO</th>\n",
       "      <th>Category</th>\n",
       "      <th>States/UTs</th>\n",
       "      <th>Per capita fossil fuel consumption (in kg.)</th>\n",
       "      <th>Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)</th>\n",
       "      <th>Hazardous waste generated per 1,000 population (Metric tonnes/Annum)</th>\n",
       "      <th>Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)</th>\n",
       "      <th>Plastic waste generated per 1,000 population (Tonnes/Annum)</th>\n",
       "      <th>Percentage of BMW treated to total quantity of BMW generated</th>\n",
       "      <th>Installed capacity of grid interactive bio power per 10 lakh population (MW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>State</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>158.4</td>\n",
       "      <td>59.575931</td>\n",
       "      <td>11.279270</td>\n",
       "      <td>75.992319</td>\n",
       "      <td>1.274485</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.635735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>State</td>\n",
       "      <td>Arunachal Pradesh</td>\n",
       "      <td>179.7</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.536752</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>State</td>\n",
       "      <td>Assam</td>\n",
       "      <td>88.0</td>\n",
       "      <td>66.643685</td>\n",
       "      <td>1.337720</td>\n",
       "      <td>20.915679</td>\n",
       "      <td>0.948150</td>\n",
       "      <td>75.048046</td>\n",
       "      <td>0.057483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>State</td>\n",
       "      <td>Bihar</td>\n",
       "      <td>50.5</td>\n",
       "      <td>68.584991</td>\n",
       "      <td>0.138161</td>\n",
       "      <td>28.405407</td>\n",
       "      <td>0.582283</td>\n",
       "      <td>28.834587</td>\n",
       "      <td>1.023012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>State</td>\n",
       "      <td>Chhattisgarh</td>\n",
       "      <td>160.9</td>\n",
       "      <td>56.460471</td>\n",
       "      <td>8.557503</td>\n",
       "      <td>19.754941</td>\n",
       "      <td>0.210763</td>\n",
       "      <td>28.559829</td>\n",
       "      <td>8.376372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>State</td>\n",
       "      <td>Goa</td>\n",
       "      <td>547.1</td>\n",
       "      <td>43.631436</td>\n",
       "      <td>19.110821</td>\n",
       "      <td>4.338928</td>\n",
       "      <td>21.238931</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.218931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>State</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>351.4</td>\n",
       "      <td>71.026283</td>\n",
       "      <td>50.116802</td>\n",
       "      <td>33.099375</td>\n",
       "      <td>5.301223</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.117520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>State</td>\n",
       "      <td>Haryana</td>\n",
       "      <td>415.0</td>\n",
       "      <td>75.838182</td>\n",
       "      <td>4.658146</td>\n",
       "      <td>177.463415</td>\n",
       "      <td>2.420170</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>7.252251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>State</td>\n",
       "      <td>Himachal Pradesh</td>\n",
       "      <td>227.4</td>\n",
       "      <td>62.892318</td>\n",
       "      <td>3.738167</td>\n",
       "      <td>65.699879</td>\n",
       "      <td>0.505228</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.249660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>State</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>103.4</td>\n",
       "      <td>70.081292</td>\n",
       "      <td>13.001647</td>\n",
       "      <td>2.062399</td>\n",
       "      <td>1.388899</td>\n",
       "      <td>52.553291</td>\n",
       "      <td>0.112816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>State</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>216.0</td>\n",
       "      <td>52.616052</td>\n",
       "      <td>6.335936</td>\n",
       "      <td>54.790481</td>\n",
       "      <td>4.167701</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>28.397197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>State</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>189.9</td>\n",
       "      <td>40.216734</td>\n",
       "      <td>3.048167</td>\n",
       "      <td>32.637893</td>\n",
       "      <td>3.808702</td>\n",
       "      <td>58.666386</td>\n",
       "      <td>0.064182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>State</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>110.3</td>\n",
       "      <td>63.037865</td>\n",
       "      <td>3.025076</td>\n",
       "      <td>67.055377</td>\n",
       "      <td>0.887769</td>\n",
       "      <td>91.800396</td>\n",
       "      <td>1.465584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>State</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>187.0</td>\n",
       "      <td>50.698150</td>\n",
       "      <td>9.236121</td>\n",
       "      <td>11.572251</td>\n",
       "      <td>3.374468</td>\n",
       "      <td>99.545003</td>\n",
       "      <td>20.998334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>State</td>\n",
       "      <td>Meghalaya</td>\n",
       "      <td>166.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.152188</td>\n",
       "      <td>1.848049</td>\n",
       "      <td>0.394688</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.227941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>State</td>\n",
       "      <td>Odisha</td>\n",
       "      <td>141.4</td>\n",
       "      <td>60.634739</td>\n",
       "      <td>20.678965</td>\n",
       "      <td>62.807815</td>\n",
       "      <td>2.013199</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.302540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>State</td>\n",
       "      <td>Punjab</td>\n",
       "      <td>255.0</td>\n",
       "      <td>78.894375</td>\n",
       "      <td>4.110845</td>\n",
       "      <td>18.016513</td>\n",
       "      <td>4.020830</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>16.044269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>State</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>166.2</td>\n",
       "      <td>70.626894</td>\n",
       "      <td>8.147039</td>\n",
       "      <td>99.187497</td>\n",
       "      <td>1.367041</td>\n",
       "      <td>75.975543</td>\n",
       "      <td>1.542444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>State</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>199.9</td>\n",
       "      <td>49.224298</td>\n",
       "      <td>17.262642</td>\n",
       "      <td>48.734607</td>\n",
       "      <td>5.315280</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>13.379154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>State</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>198.4</td>\n",
       "      <td>65.997726</td>\n",
       "      <td>9.925169</td>\n",
       "      <td>52.250571</td>\n",
       "      <td>4.942335</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>5.485401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>91.1</td>\n",
       "      <td>73.718854</td>\n",
       "      <td>1.119218</td>\n",
       "      <td>60.404104</td>\n",
       "      <td>1.140800</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.248464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>State</td>\n",
       "      <td>Uttarakhand</td>\n",
       "      <td>170.6</td>\n",
       "      <td>78.353497</td>\n",
       "      <td>2.171054</td>\n",
       "      <td>96.333486</td>\n",
       "      <td>2.812573</td>\n",
       "      <td>99.124384</td>\n",
       "      <td>11.510651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>State</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>96.2</td>\n",
       "      <td>50.199310</td>\n",
       "      <td>1.924808</td>\n",
       "      <td>49.912245</td>\n",
       "      <td>3.111255</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>3.273877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Union Territory</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>291.9</td>\n",
       "      <td>89.009991</td>\n",
       "      <td>2.176167</td>\n",
       "      <td>0.049333</td>\n",
       "      <td>11.492766</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.559181</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SNO         Category         States/UTs  \\\n",
       "0     1            State     Andhra Pradesh   \n",
       "1     2            State  Arunachal Pradesh   \n",
       "2     3            State              Assam   \n",
       "3     4            State              Bihar   \n",
       "4     5            State       Chhattisgarh   \n",
       "5     6            State                Goa   \n",
       "6     7            State            Gujarat   \n",
       "7     8            State            Haryana   \n",
       "8     9            State   Himachal Pradesh   \n",
       "9    10            State          Jharkhand   \n",
       "10   11            State          Karnataka   \n",
       "11   12            State             Kerala   \n",
       "12   13            State     Madhya Pradesh   \n",
       "13   14            State        Maharashtra   \n",
       "15   16            State          Meghalaya   \n",
       "18   19            State             Odisha   \n",
       "19   20            State             Punjab   \n",
       "20   21            State          Rajasthan   \n",
       "22   23            State         Tamil Nadu   \n",
       "23   24            State          Telangana   \n",
       "25   26            State      Uttar Pradesh   \n",
       "26   27            State        Uttarakhand   \n",
       "27   28            State        West Bengal   \n",
       "32   33  Union Territory              Delhi   \n",
       "\n",
       "    Per capita fossil fuel consumption (in kg.)  \\\n",
       "0                                         158.4   \n",
       "1                                         179.7   \n",
       "2                                          88.0   \n",
       "3                                          50.5   \n",
       "4                                         160.9   \n",
       "5                                         547.1   \n",
       "6                                         351.4   \n",
       "7                                         415.0   \n",
       "8                                         227.4   \n",
       "9                                         103.4   \n",
       "10                                        216.0   \n",
       "11                                        189.9   \n",
       "12                                        110.3   \n",
       "13                                        187.0   \n",
       "15                                        166.0   \n",
       "18                                        141.4   \n",
       "19                                        255.0   \n",
       "20                                        166.2   \n",
       "22                                        199.9   \n",
       "23                                        198.4   \n",
       "25                                         91.1   \n",
       "26                                        170.6   \n",
       "27                                         96.2   \n",
       "32                                        291.9   \n",
       "\n",
       "    Percentage use of nitrogenous fertilizer out of total N,P,K, (Nitrogen, Phosphorous, Potassium)  \\\n",
       "0                                           59.575931                                                 \n",
       "1                                            0.000000                                                 \n",
       "2                                           66.643685                                                 \n",
       "3                                           68.584991                                                 \n",
       "4                                           56.460471                                                 \n",
       "5                                           43.631436                                                 \n",
       "6                                           71.026283                                                 \n",
       "7                                           75.838182                                                 \n",
       "8                                           62.892318                                                 \n",
       "9                                           70.081292                                                 \n",
       "10                                          52.616052                                                 \n",
       "11                                          40.216734                                                 \n",
       "12                                          63.037865                                                 \n",
       "13                                          50.698150                                                 \n",
       "15                                           0.000000                                                 \n",
       "18                                          60.634739                                                 \n",
       "19                                          78.894375                                                 \n",
       "20                                          70.626894                                                 \n",
       "22                                          49.224298                                                 \n",
       "23                                          65.997726                                                 \n",
       "25                                          73.718854                                                 \n",
       "26                                          78.353497                                                 \n",
       "27                                          50.199310                                                 \n",
       "32                                          89.009991                                                 \n",
       "\n",
       "    Hazardous waste generated per 1,000 population (Metric tonnes/Annum)  \\\n",
       "0                                           11.279270                      \n",
       "1                                                 NaN                      \n",
       "2                                            1.337720                      \n",
       "3                                            0.138161                      \n",
       "4                                            8.557503                      \n",
       "5                                           19.110821                      \n",
       "6                                           50.116802                      \n",
       "7                                            4.658146                      \n",
       "8                                            3.738167                      \n",
       "9                                           13.001647                      \n",
       "10                                           6.335936                      \n",
       "11                                           3.048167                      \n",
       "12                                           3.025076                      \n",
       "13                                           9.236121                      \n",
       "15                                           0.152188                      \n",
       "18                                          20.678965                      \n",
       "19                                           4.110845                      \n",
       "20                                           8.147039                      \n",
       "22                                          17.262642                      \n",
       "23                                           9.925169                      \n",
       "25                                           1.119218                      \n",
       "26                                           2.171054                      \n",
       "27                                           1.924808                      \n",
       "32                                           2.176167                      \n",
       "\n",
       "    Quantity of hazardous waste recycled/utilized to total hazardous waste generated (%)  \\\n",
       "0                                           75.992319                                      \n",
       "1                                                 NaN                                      \n",
       "2                                           20.915679                                      \n",
       "3                                           28.405407                                      \n",
       "4                                           19.754941                                      \n",
       "5                                            4.338928                                      \n",
       "6                                           33.099375                                      \n",
       "7                                          177.463415                                      \n",
       "8                                           65.699879                                      \n",
       "9                                            2.062399                                      \n",
       "10                                          54.790481                                      \n",
       "11                                          32.637893                                      \n",
       "12                                          67.055377                                      \n",
       "13                                          11.572251                                      \n",
       "15                                           1.848049                                      \n",
       "18                                          62.807815                                      \n",
       "19                                          18.016513                                      \n",
       "20                                          99.187497                                      \n",
       "22                                          48.734607                                      \n",
       "23                                          52.250571                                      \n",
       "25                                          60.404104                                      \n",
       "26                                          96.333486                                      \n",
       "27                                          49.912245                                      \n",
       "32                                           0.049333                                      \n",
       "\n",
       "    Plastic waste generated per 1,000 population (Tonnes/Annum)  \\\n",
       "0                                            1.274485             \n",
       "1                                            2.536752             \n",
       "2                                            0.948150             \n",
       "3                                            0.582283             \n",
       "4                                            0.210763             \n",
       "5                                           21.238931             \n",
       "6                                            5.301223             \n",
       "7                                            2.420170             \n",
       "8                                            0.505228             \n",
       "9                                            1.388899             \n",
       "10                                           4.167701             \n",
       "11                                           3.808702             \n",
       "12                                           0.887769             \n",
       "13                                           3.374468             \n",
       "15                                           0.394688             \n",
       "18                                           2.013199             \n",
       "19                                           4.020830             \n",
       "20                                           1.367041             \n",
       "22                                           5.315280             \n",
       "23                                           4.942335             \n",
       "25                                           1.140800             \n",
       "26                                           2.812573             \n",
       "27                                           3.111255             \n",
       "32                                          11.492766             \n",
       "\n",
       "    Percentage of BMW treated to total quantity of BMW generated  \\\n",
       "0                                          100.000000              \n",
       "1                                          100.000000              \n",
       "2                                           75.048046              \n",
       "3                                           28.834587              \n",
       "4                                           28.559829              \n",
       "5                                          100.000000              \n",
       "6                                          100.000000              \n",
       "7                                          100.000000              \n",
       "8                                          100.000000              \n",
       "9                                           52.553291              \n",
       "10                                         100.000000              \n",
       "11                                          58.666386              \n",
       "12                                          91.800396              \n",
       "13                                          99.545003              \n",
       "15                                         100.000000              \n",
       "18                                         100.000000              \n",
       "19                                         100.000000              \n",
       "20                                          75.975543              \n",
       "22                                         100.000000              \n",
       "23                                         100.000000              \n",
       "25                                         100.000000              \n",
       "26                                          99.124384              \n",
       "27                                         100.000000              \n",
       "32                                         100.000000              \n",
       "\n",
       "    Installed capacity of grid interactive bio power per 10 lakh population (MW)  \n",
       "0                                            9.635735                             \n",
       "1                                            0.000000                             \n",
       "2                                            0.057483                             \n",
       "3                                            1.023012                             \n",
       "4                                            8.376372                             \n",
       "5                                            0.218931                             \n",
       "6                                            1.117520                             \n",
       "7                                            7.252251                             \n",
       "8                                            1.249660                             \n",
       "9                                            0.112816                             \n",
       "10                                          28.397197                             \n",
       "11                                           0.064182                             \n",
       "12                                           1.465584                             \n",
       "13                                          20.998334                             \n",
       "15                                           4.227941                             \n",
       "18                                           1.302540                             \n",
       "19                                          16.044269                             \n",
       "20                                           1.542444                             \n",
       "22                                          13.379154                             \n",
       "23                                           5.485401                             \n",
       "25                                           9.248464                             \n",
       "26                                          11.510651                             \n",
       "27                                           3.273877                             \n",
       "32                                           2.559181                             "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data5=data.dropna(subset=['Installed capacity of grid interactive bio power per 10 lakh population (MW)'])\n",
    "data5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "1c0c35f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Installed capacity of grid interactive bio power per 10 lakh population (MW)')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 842.4x624.24 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=data5['States/UTs']\n",
    "y=data5['Installed capacity of grid interactive bio power per 10 lakh population (MW)']\n",
    "plt.bar(x,y,align='edge',edgecolor='black',linewidth=\"2\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel(\"States & UTs\")\n",
    "plt.ylabel(\"Installed capacity of grid interactive bio power per 10 lakh population (MW)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c15036a7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}