Death EDA.ipynb

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   "source": [
    "# Import the relevant libraries \n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cac54675",
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   "outputs": [],
   "source": [
    "# Load the Dataset \n",
    "df = pd.read_csv( 'C:\\\\Users\\\\Mahek Poddar\\\\OneDrive\\\\Desktop\\\\Python\\\\PROJECT_1\\\\number-of-deaths-by-risk-factor.csv')"
   ]
  },
  {
   "cell_type": "code",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Entity</th>\n",
       "      <th>Code</th>\n",
       "      <th>Year</th>\n",
       "      <th>Deaths - Unsafe water source - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Unsafe sanitation - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - No access to handwashing facility - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Household air pollution from solid fuels - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Non-exclusive breastfeeding - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Discontinued breastfeeding - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Child wasting - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>...</th>\n",
       "      <th>Deaths - High systolic blood pressure - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Smoking - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Iron deficiency - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Vitamin A deficiency - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Low bone mineral density - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Air pollution - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths – Outdoor air pollution (all ages) (IHME)</th>\n",
       "      <th>Deaths - Diet high in sodium - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Diet low in whole grains - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Diet low in nuts and seeds - Sex: Both - Age: All Ages (Number)</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1990</td>\n",
       "      <td>7554.049543</td>\n",
       "      <td>5887.747628</td>\n",
       "      <td>5412.314513</td>\n",
       "      <td>22388.49723</td>\n",
       "      <td>3221.138842</td>\n",
       "      <td>156.097553</td>\n",
       "      <td>22778.84925</td>\n",
       "      <td>...</td>\n",
       "      <td>28183.98335</td>\n",
       "      <td>6393.667372</td>\n",
       "      <td>726.431294</td>\n",
       "      <td>9344.131952</td>\n",
       "      <td>374.844056</td>\n",
       "      <td>26598.00673</td>\n",
       "      <td>4383.83</td>\n",
       "      <td>2737.197934</td>\n",
       "      <td>11381.37735</td>\n",
       "      <td>7299.867330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1991</td>\n",
       "      <td>7359.676749</td>\n",
       "      <td>5732.770160</td>\n",
       "      <td>5287.891103</td>\n",
       "      <td>22128.75821</td>\n",
       "      <td>3150.559597</td>\n",
       "      <td>151.539851</td>\n",
       "      <td>22292.69111</td>\n",
       "      <td>...</td>\n",
       "      <td>28435.39751</td>\n",
       "      <td>6429.253320</td>\n",
       "      <td>739.245799</td>\n",
       "      <td>9330.182378</td>\n",
       "      <td>379.854237</td>\n",
       "      <td>26379.53222</td>\n",
       "      <td>4426.36</td>\n",
       "      <td>2741.184956</td>\n",
       "      <td>11487.83239</td>\n",
       "      <td>7386.764303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1992</td>\n",
       "      <td>7650.437822</td>\n",
       "      <td>5954.804987</td>\n",
       "      <td>5506.657363</td>\n",
       "      <td>22873.76879</td>\n",
       "      <td>3331.349048</td>\n",
       "      <td>156.609194</td>\n",
       "      <td>23102.19794</td>\n",
       "      <td>...</td>\n",
       "      <td>29173.61120</td>\n",
       "      <td>6561.054957</td>\n",
       "      <td>873.485341</td>\n",
       "      <td>9769.844533</td>\n",
       "      <td>388.130434</td>\n",
       "      <td>27263.12791</td>\n",
       "      <td>4568.91</td>\n",
       "      <td>2798.560245</td>\n",
       "      <td>11866.23557</td>\n",
       "      <td>7640.628526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1993</td>\n",
       "      <td>10270.731380</td>\n",
       "      <td>7986.736613</td>\n",
       "      <td>7104.620351</td>\n",
       "      <td>25599.75628</td>\n",
       "      <td>4477.006100</td>\n",
       "      <td>206.834451</td>\n",
       "      <td>27902.66996</td>\n",
       "      <td>...</td>\n",
       "      <td>30074.76091</td>\n",
       "      <td>6731.972560</td>\n",
       "      <td>1040.047422</td>\n",
       "      <td>11433.769490</td>\n",
       "      <td>405.577931</td>\n",
       "      <td>30495.56150</td>\n",
       "      <td>5080.29</td>\n",
       "      <td>2853.301679</td>\n",
       "      <td>12335.96168</td>\n",
       "      <td>7968.311853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1994</td>\n",
       "      <td>11409.177110</td>\n",
       "      <td>8863.010065</td>\n",
       "      <td>8051.515953</td>\n",
       "      <td>28013.16720</td>\n",
       "      <td>5102.622054</td>\n",
       "      <td>233.930571</td>\n",
       "      <td>32929.00593</td>\n",
       "      <td>...</td>\n",
       "      <td>30809.49117</td>\n",
       "      <td>6889.328118</td>\n",
       "      <td>1101.764645</td>\n",
       "      <td>12936.955860</td>\n",
       "      <td>415.349195</td>\n",
       "      <td>33323.16140</td>\n",
       "      <td>5499.23</td>\n",
       "      <td>2880.025765</td>\n",
       "      <td>12672.95019</td>\n",
       "      <td>8244.368430</td>\n",
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       "        Entity Code  Year  \\\n",
       "0  Afghanistan  AFG  1990   \n",
       "1  Afghanistan  AFG  1991   \n",
       "2  Afghanistan  AFG  1992   \n",
       "3  Afghanistan  AFG  1993   \n",
       "4  Afghanistan  AFG  1994   \n",
       "\n",
       "   Deaths - Unsafe water source - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        7554.049543                   \n",
       "1                                        7359.676749                   \n",
       "2                                        7650.437822                   \n",
       "3                                       10270.731380                   \n",
       "4                                       11409.177110                   \n",
       "\n",
       "   Deaths - Unsafe sanitation - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        5887.747628                 \n",
       "1                                        5732.770160                 \n",
       "2                                        5954.804987                 \n",
       "3                                        7986.736613                 \n",
       "4                                        8863.010065                 \n",
       "\n",
       "   Deaths - No access to handwashing facility - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        5412.314513                                 \n",
       "1                                        5287.891103                                 \n",
       "2                                        5506.657363                                 \n",
       "3                                        7104.620351                                 \n",
       "4                                        8051.515953                                 \n",
       "\n",
       "   Deaths - Household air pollution from solid fuels - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        22388.49723                                        \n",
       "1                                        22128.75821                                        \n",
       "2                                        22873.76879                                        \n",
       "3                                        25599.75628                                        \n",
       "4                                        28013.16720                                        \n",
       "\n",
       "   Deaths - Non-exclusive breastfeeding - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        3221.138842                           \n",
       "1                                        3150.559597                           \n",
       "2                                        3331.349048                           \n",
       "3                                        4477.006100                           \n",
       "4                                        5102.622054                           \n",
       "\n",
       "   Deaths - Discontinued breastfeeding - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                         156.097553                          \n",
       "1                                         151.539851                          \n",
       "2                                         156.609194                          \n",
       "3                                         206.834451                          \n",
       "4                                         233.930571                          \n",
       "\n",
       "   Deaths - Child wasting - Sex: Both - Age: All Ages (Number)  ...  \\\n",
       "0                                        22778.84925            ...   \n",
       "1                                        22292.69111            ...   \n",
       "2                                        23102.19794            ...   \n",
       "3                                        27902.66996            ...   \n",
       "4                                        32929.00593            ...   \n",
       "\n",
       "   Deaths - High systolic blood pressure - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        28183.98335                            \n",
       "1                                        28435.39751                            \n",
       "2                                        29173.61120                            \n",
       "3                                        30074.76091                            \n",
       "4                                        30809.49117                            \n",
       "\n",
       "   Deaths - Smoking - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        6393.667372       \n",
       "1                                        6429.253320       \n",
       "2                                        6561.054957       \n",
       "3                                        6731.972560       \n",
       "4                                        6889.328118       \n",
       "\n",
       "   Deaths - Iron deficiency - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                         726.431294               \n",
       "1                                         739.245799               \n",
       "2                                         873.485341               \n",
       "3                                        1040.047422               \n",
       "4                                        1101.764645               \n",
       "\n",
       "   Deaths - Vitamin A deficiency - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        9344.131952                    \n",
       "1                                        9330.182378                    \n",
       "2                                        9769.844533                    \n",
       "3                                       11433.769490                    \n",
       "4                                       12936.955860                    \n",
       "\n",
       "   Deaths - Low bone mineral density - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                         374.844056                        \n",
       "1                                         379.854237                        \n",
       "2                                         388.130434                        \n",
       "3                                         405.577931                        \n",
       "4                                         415.349195                        \n",
       "\n",
       "   Deaths - Air pollution - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        26598.00673             \n",
       "1                                        26379.53222             \n",
       "2                                        27263.12791             \n",
       "3                                        30495.56150             \n",
       "4                                        33323.16140             \n",
       "\n",
       "   Deaths – Outdoor air pollution (all ages) (IHME)  \\\n",
       "0                                           4383.83   \n",
       "1                                           4426.36   \n",
       "2                                           4568.91   \n",
       "3                                           5080.29   \n",
       "4                                           5499.23   \n",
       "\n",
       "   Deaths - Diet high in sodium - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        2737.197934                   \n",
       "1                                        2741.184956                   \n",
       "2                                        2798.560245                   \n",
       "3                                        2853.301679                   \n",
       "4                                        2880.025765                   \n",
       "\n",
       "   Deaths - Diet low in whole grains - Sex: Both - Age: All Ages (Number)  \\\n",
       "0                                        11381.37735                        \n",
       "1                                        11487.83239                        \n",
       "2                                        11866.23557                        \n",
       "3                                        12335.96168                        \n",
       "4                                        12672.95019                        \n",
       "\n",
       "   Deaths - Diet low in nuts and seeds - Sex: Both - Age: All Ages (Number)  \n",
       "0                                        7299.867330                         \n",
       "1                                        7386.764303                         \n",
       "2                                        7640.628526                         \n",
       "3                                        7968.311853                         \n",
       "4                                        8244.368430                         \n",
       "\n",
       "[5 rows x 32 columns]"
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     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
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      "RangeIndex: 6468 entries, 0 to 6467\n",
      "Data columns (total 32 columns):\n",
      " #   Column                                                                                  Non-Null Count  Dtype  \n",
      "---  ------                                                                                  --------------  -----  \n",
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      " 1   Code                                                                                    5488 non-null   object \n",
      " 2   Year                                                                                    6468 non-null   int64  \n",
      " 3   Deaths - Unsafe water source - Sex: Both - Age: All Ages (Number)                       6468 non-null   float64\n",
      " 4   Deaths - Unsafe sanitation - Sex: Both - Age: All Ages (Number)                         6468 non-null   float64\n",
      " 5   Deaths - No access to handwashing facility - Sex: Both - Age: All Ages (Number)         6468 non-null   float64\n",
      " 6   Deaths - Household air pollution from solid fuels - Sex: Both - Age: All Ages (Number)  6468 non-null   float64\n",
      " 7   Deaths - Non-exclusive breastfeeding - Sex: Both - Age: All Ages (Number)               6468 non-null   float64\n",
      " 8   Deaths - Discontinued breastfeeding - Sex: Both - Age: All Ages (Number)                6468 non-null   float64\n",
      " 9   Deaths - Child wasting - Sex: Both - Age: All Ages (Number)                             6468 non-null   float64\n",
      " 10  Deaths - Child stunting - Sex: Both - Age: All Ages (Number)                            6468 non-null   float64\n",
      " 11  Deaths - Low birth weight for gestation - Sex: Both - Age: All Ages (Number)            6468 non-null   float64\n",
      " 12  Deaths - Secondhand smoke - Sex: Both - Age: All Ages (Number)                          6468 non-null   float64\n",
      " 13  Deaths - Alcohol use - Sex: Both - Age: All Ages (Number)                               6468 non-null   float64\n",
      " 14  Deaths - Drug use - Sex: Both - Age: All Ages (Number)                                  6468 non-null   float64\n",
      " 15  Deaths - Diet low in fruits - Sex: Both - Age: All Ages (Number)                        6468 non-null   float64\n",
      " 16  Deaths - Diet low in vegetables - Sex: Both - Age: All Ages (Number)                    6468 non-null   float64\n",
      " 17  Deaths - Unsafe sex - Sex: Both - Age: All Ages (Number)                                6468 non-null   float64\n",
      " 18  Deaths - Low physical activity - Sex: Both - Age: All Ages (Number)                     6468 non-null   float64\n",
      " 19  Deaths - High fasting plasma glucose - Sex: Both - Age: All Ages (Number)               6468 non-null   float64\n",
      " 20  Deaths - High total cholesterol - Sex: Both - Age: All Ages (Number)                    1561 non-null   float64\n",
      " 21  Deaths - High body-mass index - Sex: Both - Age: All Ages (Number)                      6468 non-null   float64\n",
      " 22  Deaths - High systolic blood pressure - Sex: Both - Age: All Ages (Number)              6468 non-null   float64\n",
      " 23  Deaths - Smoking - Sex: Both - Age: All Ages (Number)                                   6468 non-null   float64\n",
      " 24  Deaths - Iron deficiency - Sex: Both - Age: All Ages (Number)                           6468 non-null   float64\n",
      " 25  Deaths - Vitamin A deficiency - Sex: Both - Age: All Ages (Number)                      6468 non-null   float64\n",
      " 26  Deaths - Low bone mineral density - Sex: Both - Age: All Ages (Number)                  6468 non-null   float64\n",
      " 27  Deaths - Air pollution - Sex: Both - Age: All Ages (Number)                             6468 non-null   float64\n",
      " 28  Deaths – Outdoor air pollution (all ages) (IHME)                                        6467 non-null   float64\n",
      " 29  Deaths - Diet high in sodium - Sex: Both - Age: All Ages (Number)                       6468 non-null   float64\n",
      " 30  Deaths - Diet low in whole grains - Sex: Both - Age: All Ages (Number)                  6468 non-null   float64\n",
      " 31  Deaths - Diet low in nuts and seeds - Sex: Both - Age: All Ages (Number)                6468 non-null   float64\n",
      "dtypes: float64(29), int64(1), object(2)\n",
      "memory usage: 1.6+ MB\n"
     ]
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   "source": [
    "df.info()"
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  },
  {
   "cell_type": "markdown",
   "id": "ec52d795",
   "metadata": {},
   "source": [
    "## India Analysis "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "813831e1",
   "metadata": {},
   "source": [
    "## Linear Regression "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42fa9fc6",
   "metadata": {},
   "source": [
    "## Analyzing Deaths due to Alcohol use in India "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8697435a",
   "metadata": {
    "scrolled": true
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       "      <th>Entity</th>\n",
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       "      <th>Year</th>\n",
       "      <th>Deaths - Unsafe water source - Sex: Both - Age: All Ages (Number)</th>\n",
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       "      <th>Deaths - Child wasting - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>...</th>\n",
       "      <th>Deaths - High systolic blood pressure - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Smoking - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Iron deficiency - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Vitamin A deficiency - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Low bone mineral density - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Air pollution - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths – Outdoor air pollution (all ages) (IHME)</th>\n",
       "      <th>Deaths - Diet high in sodium - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Diet low in whole grains - Sex: Both - Age: All Ages (Number)</th>\n",
       "      <th>Deaths - Diet low in nuts and seeds - Sex: Both - Age: All Ages (Number)</th>\n",
       "    </tr>\n",
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       "    <tr>\n",
       "      <th>2688</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1990</td>\n",
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       "      <td>6598.317849</td>\n",
       "      <td>861136.0094</td>\n",
       "      <td>...</td>\n",
       "      <td>7.057237e+05</td>\n",
       "      <td>650770.8855</td>\n",
       "      <td>49941.85417</td>\n",
       "      <td>253043.67290</td>\n",
       "      <td>34791.15994</td>\n",
       "      <td>1.018676e+06</td>\n",
       "      <td>368426.57</td>\n",
       "      <td>121322.6628</td>\n",
       "      <td>258537.1347</td>\n",
       "      <td>189694.8574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2689</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1991</td>\n",
       "      <td>811265.9069</td>\n",
       "      <td>638456.6346</td>\n",
       "      <td>430207.6328</td>\n",
       "      <td>693852.4155</td>\n",
       "      <td>120834.70210</td>\n",
       "      <td>6663.946536</td>\n",
       "      <td>847509.4954</td>\n",
       "      <td>...</td>\n",
       "      <td>7.254338e+05</td>\n",
       "      <td>668334.5010</td>\n",
       "      <td>49908.32147</td>\n",
       "      <td>252792.19330</td>\n",
       "      <td>36044.47147</td>\n",
       "      <td>1.031706e+06</td>\n",
       "      <td>380247.34</td>\n",
       "      <td>118245.1045</td>\n",
       "      <td>265011.9789</td>\n",
       "      <td>194587.5535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2690</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1992</td>\n",
       "      <td>809832.0949</td>\n",
       "      <td>636020.6287</td>\n",
       "      <td>428346.3225</td>\n",
       "      <td>693823.3194</td>\n",
       "      <td>118244.39090</td>\n",
       "      <td>6512.996663</td>\n",
       "      <td>832721.1036</td>\n",
       "      <td>...</td>\n",
       "      <td>7.496105e+05</td>\n",
       "      <td>680410.7270</td>\n",
       "      <td>50191.13541</td>\n",
       "      <td>251328.07890</td>\n",
       "      <td>37571.27674</td>\n",
       "      <td>1.043889e+06</td>\n",
       "      <td>393196.00</td>\n",
       "      <td>119220.2441</td>\n",
       "      <td>272938.8341</td>\n",
       "      <td>200209.6412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2691</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1993</td>\n",
       "      <td>798193.5484</td>\n",
       "      <td>625142.5128</td>\n",
       "      <td>421085.3844</td>\n",
       "      <td>680356.2421</td>\n",
       "      <td>113499.59350</td>\n",
       "      <td>6086.902085</td>\n",
       "      <td>810052.0576</td>\n",
       "      <td>...</td>\n",
       "      <td>7.549949e+05</td>\n",
       "      <td>686448.7975</td>\n",
       "      <td>47460.49254</td>\n",
       "      <td>247549.77450</td>\n",
       "      <td>38435.52799</td>\n",
       "      <td>1.034363e+06</td>\n",
       "      <td>397038.19</td>\n",
       "      <td>116822.2834</td>\n",
       "      <td>273679.4193</td>\n",
       "      <td>200934.5163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2692</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1994</td>\n",
       "      <td>782064.1082</td>\n",
       "      <td>611345.7080</td>\n",
       "      <td>411623.0162</td>\n",
       "      <td>670049.3665</td>\n",
       "      <td>108452.87970</td>\n",
       "      <td>5617.580276</td>\n",
       "      <td>791943.3607</td>\n",
       "      <td>...</td>\n",
       "      <td>7.657926e+05</td>\n",
       "      <td>694103.4948</td>\n",
       "      <td>45612.41468</td>\n",
       "      <td>243826.81340</td>\n",
       "      <td>39453.15908</td>\n",
       "      <td>1.030297e+06</td>\n",
       "      <td>403537.63</td>\n",
       "      <td>114689.8091</td>\n",
       "      <td>277353.3215</td>\n",
       "      <td>203215.7012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2693</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1995</td>\n",
       "      <td>770997.9855</td>\n",
       "      <td>601637.2419</td>\n",
       "      <td>404314.4473</td>\n",
       "      <td>659136.6390</td>\n",
       "      <td>103304.98030</td>\n",
       "      <td>5169.259357</td>\n",
       "      <td>774324.8941</td>\n",
       "      <td>...</td>\n",
       "      <td>7.736066e+05</td>\n",
       "      <td>694732.7861</td>\n",
       "      <td>44383.51234</td>\n",
       "      <td>239076.35610</td>\n",
       "      <td>40524.97750</td>\n",
       "      <td>1.025386e+06</td>\n",
       "      <td>409781.43</td>\n",
       "      <td>111905.6330</td>\n",
       "      <td>279371.4593</td>\n",
       "      <td>204875.6441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2694</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1996</td>\n",
       "      <td>757174.1992</td>\n",
       "      <td>590231.3711</td>\n",
       "      <td>395475.5173</td>\n",
       "      <td>653262.9633</td>\n",
       "      <td>97235.34133</td>\n",
       "      <td>4726.993619</td>\n",
       "      <td>748657.0839</td>\n",
       "      <td>...</td>\n",
       "      <td>7.988543e+05</td>\n",
       "      <td>711212.5966</td>\n",
       "      <td>43974.78331</td>\n",
       "      <td>231963.91960</td>\n",
       "      <td>42058.46214</td>\n",
       "      <td>1.032461e+06</td>\n",
       "      <td>423644.74</td>\n",
       "      <td>111637.1275</td>\n",
       "      <td>287693.3351</td>\n",
       "      <td>211073.8619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2695</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1997</td>\n",
       "      <td>756259.4763</td>\n",
       "      <td>589696.9919</td>\n",
       "      <td>393456.1289</td>\n",
       "      <td>671861.3869</td>\n",
       "      <td>92509.35738</td>\n",
       "      <td>4401.078820</td>\n",
       "      <td>721795.7415</td>\n",
       "      <td>...</td>\n",
       "      <td>8.571761e+05</td>\n",
       "      <td>753639.8494</td>\n",
       "      <td>45966.20078</td>\n",
       "      <td>224598.07790</td>\n",
       "      <td>44881.27474</td>\n",
       "      <td>1.072920e+06</td>\n",
       "      <td>448222.13</td>\n",
       "      <td>116289.6916</td>\n",
       "      <td>307558.7470</td>\n",
       "      <td>225505.5379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2696</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1998</td>\n",
       "      <td>750757.1052</td>\n",
       "      <td>585826.0562</td>\n",
       "      <td>388720.2580</td>\n",
       "      <td>668996.9391</td>\n",
       "      <td>88892.96233</td>\n",
       "      <td>4253.957251</td>\n",
       "      <td>691683.7054</td>\n",
       "      <td>...</td>\n",
       "      <td>8.769377e+05</td>\n",
       "      <td>758057.4011</td>\n",
       "      <td>46972.57088</td>\n",
       "      <td>215951.78770</td>\n",
       "      <td>46683.37833</td>\n",
       "      <td>1.079257e+06</td>\n",
       "      <td>458498.80</td>\n",
       "      <td>114924.0190</td>\n",
       "      <td>312893.0540</td>\n",
       "      <td>229424.0735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2697</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>1999</td>\n",
       "      <td>741045.3527</td>\n",
       "      <td>577967.4818</td>\n",
       "      <td>381265.1672</td>\n",
       "      <td>642748.1845</td>\n",
       "      <td>86196.15713</td>\n",
       "      <td>4293.700457</td>\n",
       "      <td>661414.8974</td>\n",
       "      <td>...</td>\n",
       "      <td>8.708083e+05</td>\n",
       "      <td>733003.1458</td>\n",
       "      <td>47894.25870</td>\n",
       "      <td>206307.93220</td>\n",
       "      <td>47501.37330</td>\n",
       "      <td>1.050957e+06</td>\n",
       "      <td>454968.32</td>\n",
       "      <td>113160.8656</td>\n",
       "      <td>310588.1466</td>\n",
       "      <td>227622.5576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2698</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2000</td>\n",
       "      <td>734455.8641</td>\n",
       "      <td>572125.8089</td>\n",
       "      <td>376339.0291</td>\n",
       "      <td>629573.6696</td>\n",
       "      <td>84637.39936</td>\n",
       "      <td>4258.705212</td>\n",
       "      <td>639991.2898</td>\n",
       "      <td>...</td>\n",
       "      <td>8.894235e+05</td>\n",
       "      <td>736787.6271</td>\n",
       "      <td>47540.14351</td>\n",
       "      <td>198694.17610</td>\n",
       "      <td>48970.26101</td>\n",
       "      <td>1.047632e+06</td>\n",
       "      <td>464607.76</td>\n",
       "      <td>114766.9769</td>\n",
       "      <td>316220.0598</td>\n",
       "      <td>232242.4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2699</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2001</td>\n",
       "      <td>718835.9458</td>\n",
       "      <td>559478.1710</td>\n",
       "      <td>367703.6314</td>\n",
       "      <td>619160.9953</td>\n",
       "      <td>80677.91805</td>\n",
       "      <td>3782.868914</td>\n",
       "      <td>606418.2663</td>\n",
       "      <td>...</td>\n",
       "      <td>9.141248e+05</td>\n",
       "      <td>741364.9802</td>\n",
       "      <td>45033.90235</td>\n",
       "      <td>187569.87050</td>\n",
       "      <td>50923.80029</td>\n",
       "      <td>1.049419e+06</td>\n",
       "      <td>476874.46</td>\n",
       "      <td>117109.7757</td>\n",
       "      <td>323172.5877</td>\n",
       "      <td>237393.0253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2700</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2002</td>\n",
       "      <td>700750.5468</td>\n",
       "      <td>544821.6410</td>\n",
       "      <td>357291.2530</td>\n",
       "      <td>604227.0178</td>\n",
       "      <td>76002.36876</td>\n",
       "      <td>3273.233842</td>\n",
       "      <td>572178.5584</td>\n",
       "      <td>...</td>\n",
       "      <td>9.310060e+05</td>\n",
       "      <td>734441.5011</td>\n",
       "      <td>41161.84474</td>\n",
       "      <td>176344.88780</td>\n",
       "      <td>52807.18820</td>\n",
       "      <td>1.041326e+06</td>\n",
       "      <td>483299.09</td>\n",
       "      <td>118626.6221</td>\n",
       "      <td>327982.2248</td>\n",
       "      <td>241053.3118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2701</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2003</td>\n",
       "      <td>683466.4598</td>\n",
       "      <td>529869.4559</td>\n",
       "      <td>346840.4285</td>\n",
       "      <td>582220.5003</td>\n",
       "      <td>71788.54824</td>\n",
       "      <td>2924.532955</td>\n",
       "      <td>536602.1188</td>\n",
       "      <td>...</td>\n",
       "      <td>9.399477e+05</td>\n",
       "      <td>721521.8294</td>\n",
       "      <td>36941.75275</td>\n",
       "      <td>164694.90790</td>\n",
       "      <td>54279.50702</td>\n",
       "      <td>1.025085e+06</td>\n",
       "      <td>488115.61</td>\n",
       "      <td>119314.5784</td>\n",
       "      <td>329645.9070</td>\n",
       "      <td>242400.5076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2702</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2004</td>\n",
       "      <td>668881.3042</td>\n",
       "      <td>515958.8538</td>\n",
       "      <td>338033.9666</td>\n",
       "      <td>552103.8981</td>\n",
       "      <td>68158.89792</td>\n",
       "      <td>2658.520948</td>\n",
       "      <td>506246.0389</td>\n",
       "      <td>...</td>\n",
       "      <td>9.230185e+05</td>\n",
       "      <td>694001.9989</td>\n",
       "      <td>34952.58572</td>\n",
       "      <td>154567.67950</td>\n",
       "      <td>55141.12121</td>\n",
       "      <td>9.923972e+05</td>\n",
       "      <td>483544.98</td>\n",
       "      <td>117644.1149</td>\n",
       "      <td>322323.8113</td>\n",
       "      <td>236836.1144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2703</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2005</td>\n",
       "      <td>660257.8942</td>\n",
       "      <td>505825.6925</td>\n",
       "      <td>333250.2428</td>\n",
       "      <td>545624.6479</td>\n",
       "      <td>64578.38255</td>\n",
       "      <td>2344.104524</td>\n",
       "      <td>479780.2725</td>\n",
       "      <td>...</td>\n",
       "      <td>9.582993e+05</td>\n",
       "      <td>704923.0376</td>\n",
       "      <td>34468.62146</td>\n",
       "      <td>145607.63660</td>\n",
       "      <td>58213.90014</td>\n",
       "      <td>1.000266e+06</td>\n",
       "      <td>497827.70</td>\n",
       "      <td>122747.8664</td>\n",
       "      <td>333472.4122</td>\n",
       "      <td>245328.2079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2704</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2006</td>\n",
       "      <td>654674.2677</td>\n",
       "      <td>497423.0770</td>\n",
       "      <td>329214.6801</td>\n",
       "      <td>546837.6094</td>\n",
       "      <td>61488.86631</td>\n",
       "      <td>1990.621725</td>\n",
       "      <td>454782.7761</td>\n",
       "      <td>...</td>\n",
       "      <td>1.006446e+06</td>\n",
       "      <td>725157.8233</td>\n",
       "      <td>32632.88811</td>\n",
       "      <td>136778.75180</td>\n",
       "      <td>60977.12326</td>\n",
       "      <td>1.025865e+06</td>\n",
       "      <td>523756.73</td>\n",
       "      <td>129760.8544</td>\n",
       "      <td>349981.6007</td>\n",
       "      <td>259156.0488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2705</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2007</td>\n",
       "      <td>650617.7678</td>\n",
       "      <td>489606.9735</td>\n",
       "      <td>325868.8083</td>\n",
       "      <td>549219.8389</td>\n",
       "      <td>58591.64913</td>\n",
       "      <td>1731.429866</td>\n",
       "      <td>433088.7519</td>\n",
       "      <td>...</td>\n",
       "      <td>1.057809e+06</td>\n",
       "      <td>750616.2341</td>\n",
       "      <td>30334.46550</td>\n",
       "      <td>127828.95750</td>\n",
       "      <td>63859.66456</td>\n",
       "      <td>1.053544e+06</td>\n",
       "      <td>550599.52</td>\n",
       "      <td>138649.2548</td>\n",
       "      <td>368051.3207</td>\n",
       "      <td>273716.7962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2706</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2008</td>\n",
       "      <td>648163.4067</td>\n",
       "      <td>481544.8127</td>\n",
       "      <td>322651.3581</td>\n",
       "      <td>548852.7310</td>\n",
       "      <td>56138.69294</td>\n",
       "      <td>1664.637589</td>\n",
       "      <td>413313.9589</td>\n",
       "      <td>...</td>\n",
       "      <td>1.111001e+06</td>\n",
       "      <td>776942.1913</td>\n",
       "      <td>28775.27875</td>\n",
       "      <td>119474.61940</td>\n",
       "      <td>67150.55317</td>\n",
       "      <td>1.079995e+06</td>\n",
       "      <td>578836.16</td>\n",
       "      <td>147710.1806</td>\n",
       "      <td>386311.3236</td>\n",
       "      <td>287718.9510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2707</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2009</td>\n",
       "      <td>651194.0599</td>\n",
       "      <td>476656.9839</td>\n",
       "      <td>321282.3525</td>\n",
       "      <td>547817.3069</td>\n",
       "      <td>54242.15683</td>\n",
       "      <td>1707.458900</td>\n",
       "      <td>393356.2292</td>\n",
       "      <td>...</td>\n",
       "      <td>1.161158e+06</td>\n",
       "      <td>797954.8122</td>\n",
       "      <td>27732.34968</td>\n",
       "      <td>111923.57690</td>\n",
       "      <td>68789.46175</td>\n",
       "      <td>1.102675e+06</td>\n",
       "      <td>603864.16</td>\n",
       "      <td>156656.8226</td>\n",
       "      <td>402808.6552</td>\n",
       "      <td>299888.0526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2708</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2010</td>\n",
       "      <td>656580.0425</td>\n",
       "      <td>473093.9055</td>\n",
       "      <td>321058.2874</td>\n",
       "      <td>550363.8975</td>\n",
       "      <td>53166.66832</td>\n",
       "      <td>1817.688552</td>\n",
       "      <td>376323.4114</td>\n",
       "      <td>...</td>\n",
       "      <td>1.216791e+06</td>\n",
       "      <td>818069.5945</td>\n",
       "      <td>27034.61918</td>\n",
       "      <td>106245.18840</td>\n",
       "      <td>70901.62204</td>\n",
       "      <td>1.132044e+06</td>\n",
       "      <td>632171.65</td>\n",
       "      <td>166710.2691</td>\n",
       "      <td>422411.7303</td>\n",
       "      <td>315693.0215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2709</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2011</td>\n",
       "      <td>645210.7307</td>\n",
       "      <td>457656.6462</td>\n",
       "      <td>313755.1790</td>\n",
       "      <td>551432.3215</td>\n",
       "      <td>52162.27505</td>\n",
       "      <td>1916.172493</td>\n",
       "      <td>356571.0368</td>\n",
       "      <td>...</td>\n",
       "      <td>1.273710e+06</td>\n",
       "      <td>841311.0006</td>\n",
       "      <td>25420.47521</td>\n",
       "      <td>97490.90476</td>\n",
       "      <td>73106.41928</td>\n",
       "      <td>1.164663e+06</td>\n",
       "      <td>665088.69</td>\n",
       "      <td>173133.2539</td>\n",
       "      <td>443517.2863</td>\n",
       "      <td>332605.2509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2710</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2012</td>\n",
       "      <td>625665.6091</td>\n",
       "      <td>434398.4699</td>\n",
       "      <td>302658.0757</td>\n",
       "      <td>563339.6875</td>\n",
       "      <td>51151.27414</td>\n",
       "      <td>2037.333723</td>\n",
       "      <td>339512.2694</td>\n",
       "      <td>...</td>\n",
       "      <td>1.325460e+06</td>\n",
       "      <td>861356.2188</td>\n",
       "      <td>21812.92281</td>\n",
       "      <td>90792.89781</td>\n",
       "      <td>74944.12125</td>\n",
       "      <td>1.175901e+06</td>\n",
       "      <td>664794.19</td>\n",
       "      <td>177471.1165</td>\n",
       "      <td>461985.7724</td>\n",
       "      <td>346950.2751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2711</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2013</td>\n",
       "      <td>604731.7691</td>\n",
       "      <td>405370.4932</td>\n",
       "      <td>289350.1457</td>\n",
       "      <td>542067.3894</td>\n",
       "      <td>48605.79226</td>\n",
       "      <td>2097.360537</td>\n",
       "      <td>313727.0655</td>\n",
       "      <td>...</td>\n",
       "      <td>1.367356e+06</td>\n",
       "      <td>868037.6879</td>\n",
       "      <td>19605.28876</td>\n",
       "      <td>81789.54226</td>\n",
       "      <td>78916.48045</td>\n",
       "      <td>1.193266e+06</td>\n",
       "      <td>704898.66</td>\n",
       "      <td>177919.7431</td>\n",
       "      <td>473939.7497</td>\n",
       "      <td>354705.1026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2712</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2014</td>\n",
       "      <td>588806.9726</td>\n",
       "      <td>377367.6562</td>\n",
       "      <td>276761.9034</td>\n",
       "      <td>525296.8903</td>\n",
       "      <td>44444.69785</td>\n",
       "      <td>2044.993931</td>\n",
       "      <td>278530.0649</td>\n",
       "      <td>...</td>\n",
       "      <td>1.410190e+06</td>\n",
       "      <td>866247.8497</td>\n",
       "      <td>18139.91231</td>\n",
       "      <td>71404.44134</td>\n",
       "      <td>82747.63362</td>\n",
       "      <td>1.199985e+06</td>\n",
       "      <td>729767.92</td>\n",
       "      <td>178016.7166</td>\n",
       "      <td>485016.7867</td>\n",
       "      <td>359987.3913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2713</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2015</td>\n",
       "      <td>573767.0403</td>\n",
       "      <td>352445.5677</td>\n",
       "      <td>267021.0850</td>\n",
       "      <td>511055.8769</td>\n",
       "      <td>41402.48083</td>\n",
       "      <td>1969.301334</td>\n",
       "      <td>254844.6087</td>\n",
       "      <td>...</td>\n",
       "      <td>1.457131e+06</td>\n",
       "      <td>871785.3241</td>\n",
       "      <td>16280.00593</td>\n",
       "      <td>65148.85365</td>\n",
       "      <td>86650.51768</td>\n",
       "      <td>1.217471e+06</td>\n",
       "      <td>763356.15</td>\n",
       "      <td>184779.8277</td>\n",
       "      <td>497697.1613</td>\n",
       "      <td>368661.5536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2714</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2016</td>\n",
       "      <td>560745.6633</td>\n",
       "      <td>332744.6846</td>\n",
       "      <td>258164.9075</td>\n",
       "      <td>500517.1481</td>\n",
       "      <td>36956.76102</td>\n",
       "      <td>1758.432018</td>\n",
       "      <td>227107.4988</td>\n",
       "      <td>...</td>\n",
       "      <td>1.514945e+06</td>\n",
       "      <td>889962.3527</td>\n",
       "      <td>15710.33819</td>\n",
       "      <td>58793.05777</td>\n",
       "      <td>90630.25327</td>\n",
       "      <td>1.233018e+06</td>\n",
       "      <td>791135.91</td>\n",
       "      <td>193511.6603</td>\n",
       "      <td>514427.8262</td>\n",
       "      <td>380657.6447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2715</th>\n",
       "      <td>India</td>\n",
       "      <td>IND</td>\n",
       "      <td>2017</td>\n",
       "      <td>569679.1687</td>\n",
       "      <td>328719.9721</td>\n",
       "      <td>257783.8570</td>\n",
       "      <td>481737.8380</td>\n",
       "      <td>33415.29006</td>\n",
       "      <td>1611.151610</td>\n",
       "      <td>207270.6260</td>\n",
       "      <td>...</td>\n",
       "      <td>1.544920e+06</td>\n",
       "      <td>894371.5186</td>\n",
       "      <td>15245.43143</td>\n",
       "      <td>54836.04043</td>\n",
       "      <td>93208.78874</td>\n",
       "      <td>1.240529e+06</td>\n",
       "      <td>818803.38</td>\n",
       "      <td>198708.3990</td>\n",
       "      <td>521311.6220</td>\n",
       "      <td>385013.2656</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>28 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Entity Code  Year  \\\n",
       "2688  India  IND  1990   \n",
       "2689  India  IND  1991   \n",
       "2690  India  IND  1992   \n",
       "2691  India  IND  1993   \n",
       "2692  India  IND  1994   \n",
       "2693  India  IND  1995   \n",
       "2694  India  IND  1996   \n",
       "2695  India  IND  1997   \n",
       "2696  India  IND  1998   \n",
       "2697  India  IND  1999   \n",
       "2698  India  IND  2000   \n",
       "2699  India  IND  2001   \n",
       "2700  India  IND  2002   \n",
       "2701  India  IND  2003   \n",
       "2702  India  IND  2004   \n",
       "2703  India  IND  2005   \n",
       "2704  India  IND  2006   \n",
       "2705  India  IND  2007   \n",
       "2706  India  IND  2008   \n",
       "2707  India  IND  2009   \n",
       "2708  India  IND  2010   \n",
       "2709  India  IND  2011   \n",
       "2710  India  IND  2012   \n",
       "2711  India  IND  2013   \n",
       "2712  India  IND  2014   \n",
       "2713  India  IND  2015   \n",
       "2714  India  IND  2016   \n",
       "2715  India  IND  2017   \n",
       "\n",
       "      Deaths - Unsafe water source - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        807723.2259                   \n",
       "2689                                        811265.9069                   \n",
       "2690                                        809832.0949                   \n",
       "2691                                        798193.5484                   \n",
       "2692                                        782064.1082                   \n",
       "2693                                        770997.9855                   \n",
       "2694                                        757174.1992                   \n",
       "2695                                        756259.4763                   \n",
       "2696                                        750757.1052                   \n",
       "2697                                        741045.3527                   \n",
       "2698                                        734455.8641                   \n",
       "2699                                        718835.9458                   \n",
       "2700                                        700750.5468                   \n",
       "2701                                        683466.4598                   \n",
       "2702                                        668881.3042                   \n",
       "2703                                        660257.8942                   \n",
       "2704                                        654674.2677                   \n",
       "2705                                        650617.7678                   \n",
       "2706                                        648163.4067                   \n",
       "2707                                        651194.0599                   \n",
       "2708                                        656580.0425                   \n",
       "2709                                        645210.7307                   \n",
       "2710                                        625665.6091                   \n",
       "2711                                        604731.7691                   \n",
       "2712                                        588806.9726                   \n",
       "2713                                        573767.0403                   \n",
       "2714                                        560745.6633                   \n",
       "2715                                        569679.1687                   \n",
       "\n",
       "      Deaths - Unsafe sanitation - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        636517.8157                 \n",
       "2689                                        638456.6346                 \n",
       "2690                                        636020.6287                 \n",
       "2691                                        625142.5128                 \n",
       "2692                                        611345.7080                 \n",
       "2693                                        601637.2419                 \n",
       "2694                                        590231.3711                 \n",
       "2695                                        589696.9919                 \n",
       "2696                                        585826.0562                 \n",
       "2697                                        577967.4818                 \n",
       "2698                                        572125.8089                 \n",
       "2699                                        559478.1710                 \n",
       "2700                                        544821.6410                 \n",
       "2701                                        529869.4559                 \n",
       "2702                                        515958.8538                 \n",
       "2703                                        505825.6925                 \n",
       "2704                                        497423.0770                 \n",
       "2705                                        489606.9735                 \n",
       "2706                                        481544.8127                 \n",
       "2707                                        476656.9839                 \n",
       "2708                                        473093.9055                 \n",
       "2709                                        457656.6462                 \n",
       "2710                                        434398.4699                 \n",
       "2711                                        405370.4932                 \n",
       "2712                                        377367.6562                 \n",
       "2713                                        352445.5677                 \n",
       "2714                                        332744.6846                 \n",
       "2715                                        328719.9721                 \n",
       "\n",
       "      Deaths - No access to handwashing facility - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        430219.2519                                 \n",
       "2689                                        430207.6328                                 \n",
       "2690                                        428346.3225                                 \n",
       "2691                                        421085.3844                                 \n",
       "2692                                        411623.0162                                 \n",
       "2693                                        404314.4473                                 \n",
       "2694                                        395475.5173                                 \n",
       "2695                                        393456.1289                                 \n",
       "2696                                        388720.2580                                 \n",
       "2697                                        381265.1672                                 \n",
       "2698                                        376339.0291                                 \n",
       "2699                                        367703.6314                                 \n",
       "2700                                        357291.2530                                 \n",
       "2701                                        346840.4285                                 \n",
       "2702                                        338033.9666                                 \n",
       "2703                                        333250.2428                                 \n",
       "2704                                        329214.6801                                 \n",
       "2705                                        325868.8083                                 \n",
       "2706                                        322651.3581                                 \n",
       "2707                                        321282.3525                                 \n",
       "2708                                        321058.2874                                 \n",
       "2709                                        313755.1790                                 \n",
       "2710                                        302658.0757                                 \n",
       "2711                                        289350.1457                                 \n",
       "2712                                        276761.9034                                 \n",
       "2713                                        267021.0850                                 \n",
       "2714                                        258164.9075                                 \n",
       "2715                                        257783.8570                                 \n",
       "\n",
       "      Deaths - Household air pollution from solid fuels - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        691699.0043                                        \n",
       "2689                                        693852.4155                                        \n",
       "2690                                        693823.3194                                        \n",
       "2691                                        680356.2421                                        \n",
       "2692                                        670049.3665                                        \n",
       "2693                                        659136.6390                                        \n",
       "2694                                        653262.9633                                        \n",
       "2695                                        671861.3869                                        \n",
       "2696                                        668996.9391                                        \n",
       "2697                                        642748.1845                                        \n",
       "2698                                        629573.6696                                        \n",
       "2699                                        619160.9953                                        \n",
       "2700                                        604227.0178                                        \n",
       "2701                                        582220.5003                                        \n",
       "2702                                        552103.8981                                        \n",
       "2703                                        545624.6479                                        \n",
       "2704                                        546837.6094                                        \n",
       "2705                                        549219.8389                                        \n",
       "2706                                        548852.7310                                        \n",
       "2707                                        547817.3069                                        \n",
       "2708                                        550363.8975                                        \n",
       "2709                                        551432.3215                                        \n",
       "2710                                        563339.6875                                        \n",
       "2711                                        542067.3894                                        \n",
       "2712                                        525296.8903                                        \n",
       "2713                                        511055.8769                                        \n",
       "2714                                        500517.1481                                        \n",
       "2715                                        481737.8380                                        \n",
       "\n",
       "      Deaths - Non-exclusive breastfeeding - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                       122801.68150                           \n",
       "2689                                       120834.70210                           \n",
       "2690                                       118244.39090                           \n",
       "2691                                       113499.59350                           \n",
       "2692                                       108452.87970                           \n",
       "2693                                       103304.98030                           \n",
       "2694                                        97235.34133                           \n",
       "2695                                        92509.35738                           \n",
       "2696                                        88892.96233                           \n",
       "2697                                        86196.15713                           \n",
       "2698                                        84637.39936                           \n",
       "2699                                        80677.91805                           \n",
       "2700                                        76002.36876                           \n",
       "2701                                        71788.54824                           \n",
       "2702                                        68158.89792                           \n",
       "2703                                        64578.38255                           \n",
       "2704                                        61488.86631                           \n",
       "2705                                        58591.64913                           \n",
       "2706                                        56138.69294                           \n",
       "2707                                        54242.15683                           \n",
       "2708                                        53166.66832                           \n",
       "2709                                        52162.27505                           \n",
       "2710                                        51151.27414                           \n",
       "2711                                        48605.79226                           \n",
       "2712                                        44444.69785                           \n",
       "2713                                        41402.48083                           \n",
       "2714                                        36956.76102                           \n",
       "2715                                        33415.29006                           \n",
       "\n",
       "      Deaths - Discontinued breastfeeding - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        6598.317849                          \n",
       "2689                                        6663.946536                          \n",
       "2690                                        6512.996663                          \n",
       "2691                                        6086.902085                          \n",
       "2692                                        5617.580276                          \n",
       "2693                                        5169.259357                          \n",
       "2694                                        4726.993619                          \n",
       "2695                                        4401.078820                          \n",
       "2696                                        4253.957251                          \n",
       "2697                                        4293.700457                          \n",
       "2698                                        4258.705212                          \n",
       "2699                                        3782.868914                          \n",
       "2700                                        3273.233842                          \n",
       "2701                                        2924.532955                          \n",
       "2702                                        2658.520948                          \n",
       "2703                                        2344.104524                          \n",
       "2704                                        1990.621725                          \n",
       "2705                                        1731.429866                          \n",
       "2706                                        1664.637589                          \n",
       "2707                                        1707.458900                          \n",
       "2708                                        1817.688552                          \n",
       "2709                                        1916.172493                          \n",
       "2710                                        2037.333723                          \n",
       "2711                                        2097.360537                          \n",
       "2712                                        2044.993931                          \n",
       "2713                                        1969.301334                          \n",
       "2714                                        1758.432018                          \n",
       "2715                                        1611.151610                          \n",
       "\n",
       "      Deaths - Child wasting - Sex: Both - Age: All Ages (Number)  ...  \\\n",
       "2688                                        861136.0094            ...   \n",
       "2689                                        847509.4954            ...   \n",
       "2690                                        832721.1036            ...   \n",
       "2691                                        810052.0576            ...   \n",
       "2692                                        791943.3607            ...   \n",
       "2693                                        774324.8941            ...   \n",
       "2694                                        748657.0839            ...   \n",
       "2695                                        721795.7415            ...   \n",
       "2696                                        691683.7054            ...   \n",
       "2697                                        661414.8974            ...   \n",
       "2698                                        639991.2898            ...   \n",
       "2699                                        606418.2663            ...   \n",
       "2700                                        572178.5584            ...   \n",
       "2701                                        536602.1188            ...   \n",
       "2702                                        506246.0389            ...   \n",
       "2703                                        479780.2725            ...   \n",
       "2704                                        454782.7761            ...   \n",
       "2705                                        433088.7519            ...   \n",
       "2706                                        413313.9589            ...   \n",
       "2707                                        393356.2292            ...   \n",
       "2708                                        376323.4114            ...   \n",
       "2709                                        356571.0368            ...   \n",
       "2710                                        339512.2694            ...   \n",
       "2711                                        313727.0655            ...   \n",
       "2712                                        278530.0649            ...   \n",
       "2713                                        254844.6087            ...   \n",
       "2714                                        227107.4988            ...   \n",
       "2715                                        207270.6260            ...   \n",
       "\n",
       "      Deaths - High systolic blood pressure - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                       7.057237e+05                            \n",
       "2689                                       7.254338e+05                            \n",
       "2690                                       7.496105e+05                            \n",
       "2691                                       7.549949e+05                            \n",
       "2692                                       7.657926e+05                            \n",
       "2693                                       7.736066e+05                            \n",
       "2694                                       7.988543e+05                            \n",
       "2695                                       8.571761e+05                            \n",
       "2696                                       8.769377e+05                            \n",
       "2697                                       8.708083e+05                            \n",
       "2698                                       8.894235e+05                            \n",
       "2699                                       9.141248e+05                            \n",
       "2700                                       9.310060e+05                            \n",
       "2701                                       9.399477e+05                            \n",
       "2702                                       9.230185e+05                            \n",
       "2703                                       9.582993e+05                            \n",
       "2704                                       1.006446e+06                            \n",
       "2705                                       1.057809e+06                            \n",
       "2706                                       1.111001e+06                            \n",
       "2707                                       1.161158e+06                            \n",
       "2708                                       1.216791e+06                            \n",
       "2709                                       1.273710e+06                            \n",
       "2710                                       1.325460e+06                            \n",
       "2711                                       1.367356e+06                            \n",
       "2712                                       1.410190e+06                            \n",
       "2713                                       1.457131e+06                            \n",
       "2714                                       1.514945e+06                            \n",
       "2715                                       1.544920e+06                            \n",
       "\n",
       "      Deaths - Smoking - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        650770.8855       \n",
       "2689                                        668334.5010       \n",
       "2690                                        680410.7270       \n",
       "2691                                        686448.7975       \n",
       "2692                                        694103.4948       \n",
       "2693                                        694732.7861       \n",
       "2694                                        711212.5966       \n",
       "2695                                        753639.8494       \n",
       "2696                                        758057.4011       \n",
       "2697                                        733003.1458       \n",
       "2698                                        736787.6271       \n",
       "2699                                        741364.9802       \n",
       "2700                                        734441.5011       \n",
       "2701                                        721521.8294       \n",
       "2702                                        694001.9989       \n",
       "2703                                        704923.0376       \n",
       "2704                                        725157.8233       \n",
       "2705                                        750616.2341       \n",
       "2706                                        776942.1913       \n",
       "2707                                        797954.8122       \n",
       "2708                                        818069.5945       \n",
       "2709                                        841311.0006       \n",
       "2710                                        861356.2188       \n",
       "2711                                        868037.6879       \n",
       "2712                                        866247.8497       \n",
       "2713                                        871785.3241       \n",
       "2714                                        889962.3527       \n",
       "2715                                        894371.5186       \n",
       "\n",
       "      Deaths - Iron deficiency - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        49941.85417               \n",
       "2689                                        49908.32147               \n",
       "2690                                        50191.13541               \n",
       "2691                                        47460.49254               \n",
       "2692                                        45612.41468               \n",
       "2693                                        44383.51234               \n",
       "2694                                        43974.78331               \n",
       "2695                                        45966.20078               \n",
       "2696                                        46972.57088               \n",
       "2697                                        47894.25870               \n",
       "2698                                        47540.14351               \n",
       "2699                                        45033.90235               \n",
       "2700                                        41161.84474               \n",
       "2701                                        36941.75275               \n",
       "2702                                        34952.58572               \n",
       "2703                                        34468.62146               \n",
       "2704                                        32632.88811               \n",
       "2705                                        30334.46550               \n",
       "2706                                        28775.27875               \n",
       "2707                                        27732.34968               \n",
       "2708                                        27034.61918               \n",
       "2709                                        25420.47521               \n",
       "2710                                        21812.92281               \n",
       "2711                                        19605.28876               \n",
       "2712                                        18139.91231               \n",
       "2713                                        16280.00593               \n",
       "2714                                        15710.33819               \n",
       "2715                                        15245.43143               \n",
       "\n",
       "      Deaths - Vitamin A deficiency - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                       253043.67290                    \n",
       "2689                                       252792.19330                    \n",
       "2690                                       251328.07890                    \n",
       "2691                                       247549.77450                    \n",
       "2692                                       243826.81340                    \n",
       "2693                                       239076.35610                    \n",
       "2694                                       231963.91960                    \n",
       "2695                                       224598.07790                    \n",
       "2696                                       215951.78770                    \n",
       "2697                                       206307.93220                    \n",
       "2698                                       198694.17610                    \n",
       "2699                                       187569.87050                    \n",
       "2700                                       176344.88780                    \n",
       "2701                                       164694.90790                    \n",
       "2702                                       154567.67950                    \n",
       "2703                                       145607.63660                    \n",
       "2704                                       136778.75180                    \n",
       "2705                                       127828.95750                    \n",
       "2706                                       119474.61940                    \n",
       "2707                                       111923.57690                    \n",
       "2708                                       106245.18840                    \n",
       "2709                                        97490.90476                    \n",
       "2710                                        90792.89781                    \n",
       "2711                                        81789.54226                    \n",
       "2712                                        71404.44134                    \n",
       "2713                                        65148.85365                    \n",
       "2714                                        58793.05777                    \n",
       "2715                                        54836.04043                    \n",
       "\n",
       "      Deaths - Low bone mineral density - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        34791.15994                        \n",
       "2689                                        36044.47147                        \n",
       "2690                                        37571.27674                        \n",
       "2691                                        38435.52799                        \n",
       "2692                                        39453.15908                        \n",
       "2693                                        40524.97750                        \n",
       "2694                                        42058.46214                        \n",
       "2695                                        44881.27474                        \n",
       "2696                                        46683.37833                        \n",
       "2697                                        47501.37330                        \n",
       "2698                                        48970.26101                        \n",
       "2699                                        50923.80029                        \n",
       "2700                                        52807.18820                        \n",
       "2701                                        54279.50702                        \n",
       "2702                                        55141.12121                        \n",
       "2703                                        58213.90014                        \n",
       "2704                                        60977.12326                        \n",
       "2705                                        63859.66456                        \n",
       "2706                                        67150.55317                        \n",
       "2707                                        68789.46175                        \n",
       "2708                                        70901.62204                        \n",
       "2709                                        73106.41928                        \n",
       "2710                                        74944.12125                        \n",
       "2711                                        78916.48045                        \n",
       "2712                                        82747.63362                        \n",
       "2713                                        86650.51768                        \n",
       "2714                                        90630.25327                        \n",
       "2715                                        93208.78874                        \n",
       "\n",
       "      Deaths - Air pollution - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                       1.018676e+06             \n",
       "2689                                       1.031706e+06             \n",
       "2690                                       1.043889e+06             \n",
       "2691                                       1.034363e+06             \n",
       "2692                                       1.030297e+06             \n",
       "2693                                       1.025386e+06             \n",
       "2694                                       1.032461e+06             \n",
       "2695                                       1.072920e+06             \n",
       "2696                                       1.079257e+06             \n",
       "2697                                       1.050957e+06             \n",
       "2698                                       1.047632e+06             \n",
       "2699                                       1.049419e+06             \n",
       "2700                                       1.041326e+06             \n",
       "2701                                       1.025085e+06             \n",
       "2702                                       9.923972e+05             \n",
       "2703                                       1.000266e+06             \n",
       "2704                                       1.025865e+06             \n",
       "2705                                       1.053544e+06             \n",
       "2706                                       1.079995e+06             \n",
       "2707                                       1.102675e+06             \n",
       "2708                                       1.132044e+06             \n",
       "2709                                       1.164663e+06             \n",
       "2710                                       1.175901e+06             \n",
       "2711                                       1.193266e+06             \n",
       "2712                                       1.199985e+06             \n",
       "2713                                       1.217471e+06             \n",
       "2714                                       1.233018e+06             \n",
       "2715                                       1.240529e+06             \n",
       "\n",
       "      Deaths – Outdoor air pollution (all ages) (IHME)  \\\n",
       "2688                                         368426.57   \n",
       "2689                                         380247.34   \n",
       "2690                                         393196.00   \n",
       "2691                                         397038.19   \n",
       "2692                                         403537.63   \n",
       "2693                                         409781.43   \n",
       "2694                                         423644.74   \n",
       "2695                                         448222.13   \n",
       "2696                                         458498.80   \n",
       "2697                                         454968.32   \n",
       "2698                                         464607.76   \n",
       "2699                                         476874.46   \n",
       "2700                                         483299.09   \n",
       "2701                                         488115.61   \n",
       "2702                                         483544.98   \n",
       "2703                                         497827.70   \n",
       "2704                                         523756.73   \n",
       "2705                                         550599.52   \n",
       "2706                                         578836.16   \n",
       "2707                                         603864.16   \n",
       "2708                                         632171.65   \n",
       "2709                                         665088.69   \n",
       "2710                                         664794.19   \n",
       "2711                                         704898.66   \n",
       "2712                                         729767.92   \n",
       "2713                                         763356.15   \n",
       "2714                                         791135.91   \n",
       "2715                                         818803.38   \n",
       "\n",
       "      Deaths - Diet high in sodium - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        121322.6628                   \n",
       "2689                                        118245.1045                   \n",
       "2690                                        119220.2441                   \n",
       "2691                                        116822.2834                   \n",
       "2692                                        114689.8091                   \n",
       "2693                                        111905.6330                   \n",
       "2694                                        111637.1275                   \n",
       "2695                                        116289.6916                   \n",
       "2696                                        114924.0190                   \n",
       "2697                                        113160.8656                   \n",
       "2698                                        114766.9769                   \n",
       "2699                                        117109.7757                   \n",
       "2700                                        118626.6221                   \n",
       "2701                                        119314.5784                   \n",
       "2702                                        117644.1149                   \n",
       "2703                                        122747.8664                   \n",
       "2704                                        129760.8544                   \n",
       "2705                                        138649.2548                   \n",
       "2706                                        147710.1806                   \n",
       "2707                                        156656.8226                   \n",
       "2708                                        166710.2691                   \n",
       "2709                                        173133.2539                   \n",
       "2710                                        177471.1165                   \n",
       "2711                                        177919.7431                   \n",
       "2712                                        178016.7166                   \n",
       "2713                                        184779.8277                   \n",
       "2714                                        193511.6603                   \n",
       "2715                                        198708.3990                   \n",
       "\n",
       "      Deaths - Diet low in whole grains - Sex: Both - Age: All Ages (Number)  \\\n",
       "2688                                        258537.1347                        \n",
       "2689                                        265011.9789                        \n",
       "2690                                        272938.8341                        \n",
       "2691                                        273679.4193                        \n",
       "2692                                        277353.3215                        \n",
       "2693                                        279371.4593                        \n",
       "2694                                        287693.3351                        \n",
       "2695                                        307558.7470                        \n",
       "2696                                        312893.0540                        \n",
       "2697                                        310588.1466                        \n",
       "2698                                        316220.0598                        \n",
       "2699                                        323172.5877                        \n",
       "2700                                        327982.2248                        \n",
       "2701                                        329645.9070                        \n",
       "2702                                        322323.8113                        \n",
       "2703                                        333472.4122                        \n",
       "2704                                        349981.6007                        \n",
       "2705                                        368051.3207                        \n",
       "2706                                        386311.3236                        \n",
       "2707                                        402808.6552                        \n",
       "2708                                        422411.7303                        \n",
       "2709                                        443517.2863                        \n",
       "2710                                        461985.7724                        \n",
       "2711                                        473939.7497                        \n",
       "2712                                        485016.7867                        \n",
       "2713                                        497697.1613                        \n",
       "2714                                        514427.8262                        \n",
       "2715                                        521311.6220                        \n",
       "\n",
       "      Deaths - Diet low in nuts and seeds - Sex: Both - Age: All Ages (Number)  \n",
       "2688                                        189694.8574                         \n",
       "2689                                        194587.5535                         \n",
       "2690                                        200209.6412                         \n",
       "2691                                        200934.5163                         \n",
       "2692                                        203215.7012                         \n",
       "2693                                        204875.6441                         \n",
       "2694                                        211073.8619                         \n",
       "2695                                        225505.5379                         \n",
       "2696                                        229424.0735                         \n",
       "2697                                        227622.5576                         \n",
       "2698                                        232242.4000                         \n",
       "2699                                        237393.0253                         \n",
       "2700                                        241053.3118                         \n",
       "2701                                        242400.5076                         \n",
       "2702                                        236836.1144                         \n",
       "2703                                        245328.2079                         \n",
       "2704                                        259156.0488                         \n",
       "2705                                        273716.7962                         \n",
       "2706                                        287718.9510                         \n",
       "2707                                        299888.0526                         \n",
       "2708                                        315693.0215                         \n",
       "2709                                        332605.2509                         \n",
       "2710                                        346950.2751                         \n",
       "2711                                        354705.1026                         \n",
       "2712                                        359987.3913                         \n",
       "2713                                        368661.5536                         \n",
       "2714                                        380657.6447                         \n",
       "2715                                        385013.2656                         \n",
       "\n",
       "[28 rows x 32 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_Ind = df[df['Entity']=='India']\n",
    "df_Ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9c7300c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Entity', 'Code', 'Year',\n",
       "       'Deaths - Unsafe water source - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Unsafe sanitation - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - No access to handwashing facility - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Household air pollution from solid fuels - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Non-exclusive breastfeeding - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Discontinued breastfeeding - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Child wasting - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Child stunting - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Low birth weight for gestation - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Secondhand smoke - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Alcohol use - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Drug use - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Diet low in fruits - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Diet low in vegetables - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Unsafe sex - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Low physical activity - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - High fasting plasma glucose - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - High total cholesterol - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - High body-mass index - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - High systolic blood pressure - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Smoking - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Iron deficiency - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Vitamin A deficiency - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Low bone mineral density - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Air pollution - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths – Outdoor air pollution (all ages) (IHME)',\n",
       "       'Deaths - Diet high in sodium - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Diet low in whole grains - Sex: Both - Age: All Ages (Number)',\n",
       "       'Deaths - Diet low in nuts and seeds - Sex: Both - Age: All Ages (Number)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_Ind.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "82e08b02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Entity                                                                                       0\n",
       "Code                                                                                       980\n",
       "Year                                                                                         0\n",
       "Deaths - Unsafe water source - Sex: Both - Age: All Ages (Number)                            0\n",
       "Deaths - Unsafe sanitation - Sex: Both - Age: All Ages (Number)                              0\n",
       "Deaths - No access to handwashing facility - Sex: Both - Age: All Ages (Number)              0\n",
       "Deaths - Household air pollution from solid fuels - Sex: Both - Age: All Ages (Number)       0\n",
       "Deaths - Non-exclusive breastfeeding - Sex: Both - Age: All Ages (Number)                    0\n",
       "Deaths - Discontinued breastfeeding - Sex: Both - Age: All Ages (Number)                     0\n",
       "Deaths - Child wasting - Sex: Both - Age: All Ages (Number)                                  0\n",
       "Deaths - Child stunting - Sex: Both - Age: All Ages (Number)                                 0\n",
       "Deaths - Low birth weight for gestation - Sex: Both - Age: All Ages (Number)                 0\n",
       "Deaths - Secondhand smoke - Sex: Both - Age: All Ages (Number)                               0\n",
       "Deaths - Alcohol use - Sex: Both - Age: All Ages (Number)                                    0\n",
       "Deaths - Drug use - Sex: Both - Age: All Ages (Number)                                       0\n",
       "Deaths - Diet low in fruits - Sex: Both - Age: All Ages (Number)                             0\n",
       "Deaths - Diet low in vegetables - Sex: Both - Age: All Ages (Number)                         0\n",
       "Deaths - Unsafe sex - Sex: Both - Age: All Ages (Number)                                     0\n",
       "Deaths - Low physical activity - Sex: Both - Age: All Ages (Number)                          0\n",
       "Deaths - High fasting plasma glucose - Sex: Both - Age: All Ages (Number)                    0\n",
       "Deaths - High total cholesterol - Sex: Both - Age: All Ages (Number)                      4907\n",
       "Deaths - High body-mass index - Sex: Both - Age: All Ages (Number)                           0\n",
       "Deaths - High systolic blood pressure - Sex: Both - Age: All Ages (Number)                   0\n",
       "Deaths - Smoking - Sex: Both - Age: All Ages (Number)                                        0\n",
       "Deaths - Iron deficiency - Sex: Both - Age: All Ages (Number)                                0\n",
       "Deaths - Vitamin A deficiency - Sex: Both - Age: All Ages (Number)                           0\n",
       "Deaths - Low bone mineral density - Sex: Both - Age: All Ages (Number)                       0\n",
       "Deaths - Air pollution - Sex: Both - Age: All Ages (Number)                                  0\n",
       "Deaths – Outdoor air pollution (all ages) (IHME)                                             1\n",
       "Deaths - Diet high in sodium - Sex: Both - Age: All Ages (Number)                            0\n",
       "Deaths - Diet low in whole grains - Sex: Both - Age: All Ages (Number)                       0\n",
       "Deaths - Diet low in nuts and seeds - Sex: Both - Age: All Ages (Number)                     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Understand the null values \n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fd4cdaf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create X and Y and split the dataset into train and test sets \n",
    "from sklearn.model_selection import train_test_split\n",
    "X = df_Ind.iloc[:,2].values \n",
    "y = df_Ind.iloc[:,14].values\n",
    "X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.2, random_state = 1 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e8abce20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training the Simple Linear Regression model on the Training set\n",
    "from sklearn.linear_model import LinearRegression\n",
    "regressor = LinearRegression()\n",
    "regressor.fit(X_train.reshape(-1, 1), y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "dde2c19a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Predict the values \n",
    "y_pred = regressor.predict(X_test.reshape(-1,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2a2b44de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualising the Training set results\n",
    "plt.scatter(X_train, y_train, color = 'red')\n",
    "plt.plot(X_train, regressor.predict(X_train.reshape(-1,1)), color = 'blue')\n",
    "plt.title('Linear Regression (Training set)',fontdict ={'fontsize':20})\n",
    "plt.xlabel('Year',fontdict ={'fontsize':20})\n",
    "plt.ylabel('Deaths',fontdict ={'fontsize':20})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "171ee9a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualising the Test set results\n",
    "plt.scatter(X_test, y_test, color = 'red')\n",
    "plt.plot(X_test, regressor.predict(X_test.reshape(-1,1)), color = 'blue')\n",
    "plt.title('Linear Regression(Test set)',fontdict ={'fontsize':20})\n",
    "plt.xlabel('Year',fontdict ={'fontsize':20})\n",
    "plt.ylabel('Deaths',fontdict ={'fontsize':20})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e83dbce7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# As seen from the above, it's quite clear that deaths due to alcohol use in India have risen with time\n",
    "# and Linear Regression comes close to predicting acurate results. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f501e89a",
   "metadata": {},
   "source": [
    "## Polynomial Regression "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "214e6604",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training the Polynomial Regression model on the whole dataset\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "poly_reg = PolynomialFeatures(degree = 3)\n",
    "X_poly = poly_reg.fit_transform(X.reshape(-1, 1))\n",
    "lin_reg_2 = LinearRegression()\n",
    "lin_reg_2.fit(X_poly, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c9f84a05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualising the Polynomial Regression results (for higher resolution and smoother curve)\n",
    "X_grid = np.arange(min(X.reshape(-1, 1)), max(X.reshape(-1, 1)), 0.1)\n",
    "X_grid = X_grid.reshape((len(X_grid), 1))\n",
    "plt.scatter(X.reshape(-1, 1), y, color = 'red')\n",
    "plt.plot(X_grid, lin_reg_2.predict(poly_reg.fit_transform(X_grid)), color = 'blue')\n",
    "plt.title('Polynomial Regression',fontdict ={'fontsize':20})\n",
    "plt.xlabel('Year',fontdict ={'fontsize':20})\n",
    "plt.ylabel('Deaths',fontdict ={'fontsize':20})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec888046",
   "metadata": {},
   "source": [
    "## Multiple Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1bb94c0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Predicting lower Birth weights due to diet low in nuts, seeds, wholegrains and sodium "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2fc9c76d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Analyzing the contribution of Alchohol, Drugs and Cigarettes in total deaths \n",
    "from sklearn.model_selection import train_test_split\n",
    "X_m = df_Ind.iloc[:,31:34].values \n",
    "Y_m = df_Ind.iloc[:,12].values\n",
    "X_train_m, X_test_m, y_train_m, y_test_m = train_test_split(X_m,Y_m, test_size = 0.2, random_state = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2aaa2669",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training the Multiple Linear Regression model on the Training set\n",
    "from sklearn.linear_model import LinearRegression\n",
    "regressor_m = LinearRegression()\n",
    "regressor_m.fit(X_train_m.reshape(-1,1), y_train_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d6a07427",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Predicting the Test set results\n",
    "y_pred_m = regressor_m.predict(X_test_m.reshape(-1,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "14d31afa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualising the Training set results\n",
    "plt.scatter(X_train_m, y_train_m, color = 'red')\n",
    "plt.plot(X_train_m, regressor_m.predict(X_train_m.reshape(-1,1)), color = 'blue')\n",
    "plt.title('Multiple Linear Regression (Training set)',fontdict ={'fontsize':20})\n",
    "plt.xlabel('Year',fontdict ={'fontsize':20})\n",
    "plt.ylabel('Deaths',fontdict ={'fontsize':20})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "36d0ea9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualising the Test set results\n",
    "plt.scatter(X_test_m, y_test_m, color = 'red')\n",
    "plt.plot(X_test_m,y_pred_m , color = 'blue')\n",
    "plt.title('Multiple Linear Regression(Test set)',fontdict ={'fontsize':20})\n",
    "plt.xlabel('Year',fontdict ={'fontsize':20})\n",
    "plt.ylabel('Deaths',fontdict ={'fontsize':20})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cda54774",
   "metadata": {},
   "source": [
    "## Decision Tree Regression "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1316d13d",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_d = df_Ind.iloc[:,31:34].values \n",
    "y_d = df_Ind.iloc[:,12].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "aa87d498",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor(random_state=0)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training the Decision Tree Regression model on the whole dataset\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "regressor = DecisionTreeRegressor(random_state = 0)\n",
    "regressor.fit(X_d, y_d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7754141f",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'X_grid_d' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32mC:\\Users\\MAHEKP~1\\AppData\\Local\\Temp/ipykernel_18652/3495296358.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0my_pred_d\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mregressor\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_grid_d\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'X_grid_d' is not defined"
     ]
    }
   ],
   "source": [
    "y_pred_d = regressor.predict(X_grid_d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ccce747a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Visualising the Decision Tree Regression results (higher resolution)\n",
    "plt.scatter(X_d, y_d, color = 'red')\n",
    "plt.plot(X_test_m,y_pred_m , color = 'blue')\n",
    "plt.title('Decesion Tree (Test set)',fontdict ={'fontsize':20})\n",
    "plt.xlabel('Year',fontdict ={'fontsize':20})\n",
    "plt.ylabel('Deaths',fontdict ={'fontsize':20})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13ec9ea8",
   "metadata": {},
   "source": [
    "## SVR "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2fe08892",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_s = df_Ind.iloc[:,31:34].values.astype(float) \n",
    "y_s = df_Ind.iloc[:,12:13].values.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3be74f07",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature Scaling\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "sc_X = StandardScaler()\n",
    "sc_y = StandardScaler()\n",
    "X_s = sc_X.fit_transform(X_s)\n",
    "y_s = sc_y.fit_transform(y_s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed1b3379",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Training the SVR model on the whole dataset\n",
    "from sklearn.svm import SVR\n",
    "regressor = SVR(kernel = 'rbf')\n",
    "regressor.fit(X_s, y_s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "de044e82",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plotting the output \n",
    "X_grid = np.arange(min(X_s), max(X_s), 0.1)\n",
    "X_grid = X_grid.reshape((len(X_grid), 1))\n",
    "plt.scatter(X_s, y_s, color = 'green')\n",
    "plt.plot(X_grid, regressor.predict(X_grid), color = 'orange')\n",
    "plt.title('Support Vector Regression Model(High Resolution)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9ab3d4c4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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