WorkingWithPandas.ipynb

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      "name": "python3",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ICLUvBlvIEpj",
        "colab_type": "text"
      },
      "source": [
        "#Working with pandas"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LQDv-22JINOk",
        "colab_type": "text"
      },
      "source": [
        "**First things first, we need to import the pandas library**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FO3PieuRH3-2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NoMOJlElJCI-",
        "colab_type": "text"
      },
      "source": [
        "**[Pandas Documentation](https://pandas.pydata.org/docs/)**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ir9O5QaaJg5n",
        "colab_type": "text"
      },
      "source": [
        "#**Pandas Series**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4Dd3dtnnI8Zl",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "outputId": "95e51178-b0b2-4030-f6eb-6d3d5c114ce7"
      },
      "source": [
        "# creating a series from an array\n",
        "a = pd.Series([1, 2, 3], index=['a', 'b', 'c'])\n",
        "print(f'The pandas series with index a,b,c is \\n{a}')\n",
        "print(f'\\nJust for the peace of mind, type of the variable storing the series is:\\n{type(a)}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The pandas series with index a,b,c is \n",
            "a    1\n",
            "b    2\n",
            "c    3\n",
            "dtype: int64\n",
            "\n",
            "Just for the peace of mind, type of the variable storing the series is:\n",
            "<class 'pandas.core.series.Series'>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LlAkZwOJch5r",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "outputId": "38fe3668-658c-443f-cb8d-d84e54e0377e"
      },
      "source": [
        "# creating a series from a dictionary\n",
        "a = pd.Series({'a': 1, 'b': 2, 'c':3})\n",
        "print(f'The pandas series with index a,b,c is \\n{a}')\n",
        "print(f'\\nJust for the peace of mind, type of the variable storing the series is:\\n{type(a)}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The pandas series with index a,b,c is \n",
            "a    1\n",
            "b    2\n",
            "c    3\n",
            "dtype: int64\n",
            "\n",
            "Just for the peace of mind, type of the variable storing the series is:\n",
            "<class 'pandas.core.series.Series'>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "00OaER4-d97j",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "64228c1d-8523-49f6-8c13-39ebf994a531"
      },
      "source": [
        "# accessing the values in a series via index\n",
        "print(f'Value of 1st index = {a[\"a\"]}')\n",
        "print(f'Value of 2nd index = {a[\"b\"]}')\n",
        "print(f'Value of 3rd index = {a[\"c\"]}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Value of 1st index = 1\n",
            "Value of 2nd index = 2\n",
            "Value of 3rd index = 3\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ddPQdH9DX9LH",
        "colab_type": "text"
      },
      "source": [
        "#**Pandas Dataframe**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZZgQ2Hl-YcSO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "outputId": "bed1cdd5-007e-465c-c75a-bf7f458d643c"
      },
      "source": [
        "# creating a dataframe\n",
        "dictionary = {\n",
        "    'column1': [1,2,3],\n",
        "    'column2':[4,5,6],\n",
        "    'column3':[7,8,9],\n",
        "    'column4':[10,11,12]\n",
        "}\n",
        "our_df = pd.DataFrame(dictionary, index=[\"index1\", \"index2\", \"index3\"])\n",
        "print(f'The data frame we created :\\n{our_df}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The data frame we created :\n",
            "        column1  column2  column3  column4\n",
            "index1        1        4        7       10\n",
            "index2        2        5        8       11\n",
            "index3        3        6        9       12\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "opz7fpRYZWi0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "outputId": "8d30143f-d69b-4d05-aa7f-8fedc11e96d8"
      },
      "source": [
        "#playing with the above dataframe\n",
        "print(f'The first column: \\n{our_df.column1}')\n",
        "print(f'\\nThe second column: \\n{our_df.column2}')\n",
        "print(f'\\nThe third column: \\n{our_df.column3}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The first column: \n",
            "index1    1\n",
            "index2    2\n",
            "index3    3\n",
            "Name: column1, dtype: int64\n",
            "\n",
            "The second column: \n",
            "index1    4\n",
            "index2    5\n",
            "index3    6\n",
            "Name: column2, dtype: int64\n",
            "\n",
            "The third column: \n",
            "index1    7\n",
            "index2    8\n",
            "index3    9\n",
            "Name: column3, dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2roD8DdtlrQ_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        },
        "outputId": "1a467c50-742b-4983-9a4f-dbe4302ac34a"
      },
      "source": [
        "# find the details or information about the dataframe in hand\n",
        "print(f'The number of rows and columns (shape of the df) in this dataframe = {our_df.shape}')\n",
        "print(f'The number of rows in this dataframe = {our_df.shape[0]}')\n",
        "print(f'The number of columns in this dataframe = {our_df.shape[1]}')\n",
        "print(f'The number of elements in this dataframe = {our_df.size}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The number of rows and columns (shape of the df) in this dataframe = (3, 4)\n",
            "The number of rows in this dataframe = 3\n",
            "The number of columns in this dataframe = 4\n",
            "The number of elements in this dataframe = 12\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kA1KByhsnRHx",
        "colab_type": "text"
      },
      "source": [
        "**There are more exciting features to explore. For that, we would need a larger dataset.**<br>\n",
        "**Let us use this dataset available at** [https://api.covid19india.org/csv/latest/state_wise.csv](https://api.covid19india.org/csv/latest/state_wise.csv)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V9Koc8BnnQBW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "d415d5cd-1bd4-4954-a739-a9e8e0b59a8f"
      },
      "source": [
        "# importing a csv file from the mentioned source in form of dataframe\n",
        "df = pd.read_csv(\"https://api.covid19india.org/csv/latest/state_wise.csv\")\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>State</th>\n",
              "      <th>Confirmed</th>\n",
              "      <th>Recovered</th>\n",
              "      <th>Deaths</th>\n",
              "      <th>Active</th>\n",
              "      <th>Last_Updated_Time</th>\n",
              "      <th>Migrated_Other</th>\n",
              "      <th>State_code</th>\n",
              "      <th>Delta_Confirmed</th>\n",
              "      <th>Delta_Recovered</th>\n",
              "      <th>Delta_Deaths</th>\n",
              "      <th>State_Notes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Total</td>\n",
              "      <td>1693879</td>\n",
              "      <td>1093747</td>\n",
              "      <td>36548</td>\n",
              "      <td>563158</td>\n",
              "      <td>31/07/2020 22:08:29</td>\n",
              "      <td>426</td>\n",
              "      <td>TT</td>\n",
              "      <td>54311</td>\n",
              "      <td>34654</td>\n",
              "      <td>761</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Maharashtra</td>\n",
              "      <td>422118</td>\n",
              "      <td>256158</td>\n",
              "      <td>14994</td>\n",
              "      <td>150662</td>\n",
              "      <td>31/07/2020 20:43:39</td>\n",
              "      <td>304</td>\n",
              "      <td>MH</td>\n",
              "      <td>10320</td>\n",
              "      <td>7543</td>\n",
              "      <td>265</td>\n",
              "      <td>304 cases are marked as non-covid deaths in MH...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Tamil Nadu</td>\n",
              "      <td>245859</td>\n",
              "      <td>183956</td>\n",
              "      <td>3935</td>\n",
              "      <td>57968</td>\n",
              "      <td>31/07/2020 18:52:33</td>\n",
              "      <td>0</td>\n",
              "      <td>TN</td>\n",
              "      <td>5881</td>\n",
              "      <td>5778</td>\n",
              "      <td>94</td>\n",
              "      <td>[July 22]: 444 backdated deceased entries adde...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Delhi</td>\n",
              "      <td>135598</td>\n",
              "      <td>120930</td>\n",
              "      <td>3963</td>\n",
              "      <td>10705</td>\n",
              "      <td>31/07/2020 16:57:34</td>\n",
              "      <td>0</td>\n",
              "      <td>DL</td>\n",
              "      <td>1195</td>\n",
              "      <td>1206</td>\n",
              "      <td>27</td>\n",
              "      <td>[July 14]: Value for the total tests conducted...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Karnataka</td>\n",
              "      <td>124115</td>\n",
              "      <td>49788</td>\n",
              "      <td>2314</td>\n",
              "      <td>72004</td>\n",
              "      <td>31/07/2020 19:30:10</td>\n",
              "      <td>9</td>\n",
              "      <td>KA</td>\n",
              "      <td>5483</td>\n",
              "      <td>3094</td>\n",
              "      <td>84</td>\n",
              "      <td>9 cases are classified as non-covid related de...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Andhra Pradesh</td>\n",
              "      <td>140933</td>\n",
              "      <td>63864</td>\n",
              "      <td>1349</td>\n",
              "      <td>75720</td>\n",
              "      <td>31/07/2020 17:47:34</td>\n",
              "      <td>0</td>\n",
              "      <td>AP</td>\n",
              "      <td>10376</td>\n",
              "      <td>3840</td>\n",
              "      <td>68</td>\n",
              "      <td>Total includes patients from other states and ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Uttar Pradesh</td>\n",
              "      <td>85461</td>\n",
              "      <td>48863</td>\n",
              "      <td>1630</td>\n",
              "      <td>34968</td>\n",
              "      <td>31/07/2020 16:57:36</td>\n",
              "      <td>0</td>\n",
              "      <td>UP</td>\n",
              "      <td>4422</td>\n",
              "      <td>2060</td>\n",
              "      <td>43</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Gujarat</td>\n",
              "      <td>61438</td>\n",
              "      <td>45009</td>\n",
              "      <td>2436</td>\n",
              "      <td>13993</td>\n",
              "      <td>31/07/2020 20:35:11</td>\n",
              "      <td>0</td>\n",
              "      <td>GJ</td>\n",
              "      <td>1153</td>\n",
              "      <td>833</td>\n",
              "      <td>22</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>West Bengal</td>\n",
              "      <td>70188</td>\n",
              "      <td>48374</td>\n",
              "      <td>1581</td>\n",
              "      <td>20233</td>\n",
              "      <td>31/07/2020 22:08:31</td>\n",
              "      <td>0</td>\n",
              "      <td>WB</td>\n",
              "      <td>2496</td>\n",
              "      <td>2118</td>\n",
              "      <td>45</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Telangana</td>\n",
              "      <td>62703</td>\n",
              "      <td>45388</td>\n",
              "      <td>519</td>\n",
              "      <td>16796</td>\n",
              "      <td>31/07/2020 09:29:31</td>\n",
              "      <td>0</td>\n",
              "      <td>TG</td>\n",
              "      <td>1986</td>\n",
              "      <td>816</td>\n",
              "      <td>14</td>\n",
              "      <td>[July 27]\\nTelangana bulletin for the previous...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Rajasthan</td>\n",
              "      <td>42083</td>\n",
              "      <td>29845</td>\n",
              "      <td>680</td>\n",
              "      <td>11558</td>\n",
              "      <td>31/07/2020 22:08:33</td>\n",
              "      <td>0</td>\n",
              "      <td>RJ</td>\n",
              "      <td>1147</td>\n",
              "      <td>614</td>\n",
              "      <td>13</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Bihar</td>\n",
              "      <td>50987</td>\n",
              "      <td>33650</td>\n",
              "      <td>298</td>\n",
              "      <td>17038</td>\n",
              "      <td>31/07/2020 17:47:37</td>\n",
              "      <td>1</td>\n",
              "      <td>BR</td>\n",
              "      <td>2986</td>\n",
              "      <td>1977</td>\n",
              "      <td>13</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Haryana</td>\n",
              "      <td>34965</td>\n",
              "      <td>28227</td>\n",
              "      <td>421</td>\n",
              "      <td>6317</td>\n",
              "      <td>31/07/2020 20:00:13</td>\n",
              "      <td>0</td>\n",
              "      <td>HR</td>\n",
              "      <td>711</td>\n",
              "      <td>887</td>\n",
              "      <td>4</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Assam</td>\n",
              "      <td>38408</td>\n",
              "      <td>29081</td>\n",
              "      <td>98</td>\n",
              "      <td>9226</td>\n",
              "      <td>31/07/2020 19:51:54</td>\n",
              "      <td>3</td>\n",
              "      <td>AS</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>Includes one case from Nagaland.\\nTotal of 3 p...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Madhya Pradesh</td>\n",
              "      <td>31806</td>\n",
              "      <td>22271</td>\n",
              "      <td>867</td>\n",
              "      <td>8668</td>\n",
              "      <td>31/07/2020 19:31:22</td>\n",
              "      <td>0</td>\n",
              "      <td>MP</td>\n",
              "      <td>838</td>\n",
              "      <td>614</td>\n",
              "      <td>10</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Odisha</td>\n",
              "      <td>31877</td>\n",
              "      <td>20518</td>\n",
              "      <td>214</td>\n",
              "      <td>11145</td>\n",
              "      <td>31/07/2020 20:07:48</td>\n",
              "      <td>0</td>\n",
              "      <td>OR</td>\n",
              "      <td>1499</td>\n",
              "      <td>772</td>\n",
              "      <td>9</td>\n",
              "      <td>[July 12th] 20 non-covid deaths reported in st...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Jammu and Kashmir</td>\n",
              "      <td>20359</td>\n",
              "      <td>12217</td>\n",
              "      <td>377</td>\n",
              "      <td>7765</td>\n",
              "      <td>31/07/2020 18:08:34</td>\n",
              "      <td>0</td>\n",
              "      <td>JK</td>\n",
              "      <td>490</td>\n",
              "      <td>375</td>\n",
              "      <td>12</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Kerala</td>\n",
              "      <td>23614</td>\n",
              "      <td>13023</td>\n",
              "      <td>74</td>\n",
              "      <td>10495</td>\n",
              "      <td>31/07/2020 19:52:01</td>\n",
              "      <td>22</td>\n",
              "      <td>KL</td>\n",
              "      <td>1310</td>\n",
              "      <td>864</td>\n",
              "      <td>3</td>\n",
              "      <td>Mahe native who expired in Kannur included in ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Punjab</td>\n",
              "      <td>16119</td>\n",
              "      <td>10734</td>\n",
              "      <td>386</td>\n",
              "      <td>4999</td>\n",
              "      <td>31/07/2020 20:58:34</td>\n",
              "      <td>0</td>\n",
              "      <td>PB</td>\n",
              "      <td>663</td>\n",
              "      <td>225</td>\n",
              "      <td>16</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Jharkhand</td>\n",
              "      <td>10488</td>\n",
              "      <td>4176</td>\n",
              "      <td>104</td>\n",
              "      <td>6208</td>\n",
              "      <td>31/07/2020 13:42:33</td>\n",
              "      <td>0</td>\n",
              "      <td>JH</td>\n",
              "      <td>89</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Chhattisgarh</td>\n",
              "      <td>9086</td>\n",
              "      <td>6230</td>\n",
              "      <td>53</td>\n",
              "      <td>2803</td>\n",
              "      <td>31/07/2020 20:43:43</td>\n",
              "      <td>0</td>\n",
              "      <td>CT</td>\n",
              "      <td>230</td>\n",
              "      <td>309</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Uttarakhand</td>\n",
              "      <td>7183</td>\n",
              "      <td>4168</td>\n",
              "      <td>80</td>\n",
              "      <td>2897</td>\n",
              "      <td>31/07/2020 20:16:36</td>\n",
              "      <td>38</td>\n",
              "      <td>UT</td>\n",
              "      <td>118</td>\n",
              "      <td>172</td>\n",
              "      <td>4</td>\n",
              "      <td>38 Migrated cases reduced from Active count</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Goa</td>\n",
              "      <td>5913</td>\n",
              "      <td>4211</td>\n",
              "      <td>45</td>\n",
              "      <td>1657</td>\n",
              "      <td>31/07/2020 20:27:03</td>\n",
              "      <td>0</td>\n",
              "      <td>GA</td>\n",
              "      <td>209</td>\n",
              "      <td>206</td>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Tripura</td>\n",
              "      <td>4722</td>\n",
              "      <td>2962</td>\n",
              "      <td>21</td>\n",
              "      <td>1721</td>\n",
              "      <td>31/07/2020 08:59:30</td>\n",
              "      <td>18</td>\n",
              "      <td>TR</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Puducherry</td>\n",
              "      <td>3472</td>\n",
              "      <td>2100</td>\n",
              "      <td>49</td>\n",
              "      <td>1323</td>\n",
              "      <td>31/07/2020 18:49:37</td>\n",
              "      <td>0</td>\n",
              "      <td>PY</td>\n",
              "      <td>174</td>\n",
              "      <td>142</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Manipur</td>\n",
              "      <td>2621</td>\n",
              "      <td>1689</td>\n",
              "      <td>5</td>\n",
              "      <td>927</td>\n",
              "      <td>31/07/2020 19:52:10</td>\n",
              "      <td>0</td>\n",
              "      <td>MN</td>\n",
              "      <td>116</td>\n",
              "      <td>17</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Himachal Pradesh</td>\n",
              "      <td>2564</td>\n",
              "      <td>1459</td>\n",
              "      <td>13</td>\n",
              "      <td>1075</td>\n",
              "      <td>31/07/2020 21:54:37</td>\n",
              "      <td>17</td>\n",
              "      <td>HP</td>\n",
              "      <td>58</td>\n",
              "      <td>72</td>\n",
              "      <td>0</td>\n",
              "      <td>HP has 18 Migrated cases which are reduced fro...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>Ladakh</td>\n",
              "      <td>1404</td>\n",
              "      <td>1095</td>\n",
              "      <td>7</td>\n",
              "      <td>302</td>\n",
              "      <td>31/07/2020 20:00:19</td>\n",
              "      <td>0</td>\n",
              "      <td>LA</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Nagaland</td>\n",
              "      <td>1693</td>\n",
              "      <td>635</td>\n",
              "      <td>4</td>\n",
              "      <td>1052</td>\n",
              "      <td>31/07/2020 20:00:22</td>\n",
              "      <td>2</td>\n",
              "      <td>NL</td>\n",
              "      <td>127</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Arunachal Pradesh</td>\n",
              "      <td>1484</td>\n",
              "      <td>827</td>\n",
              "      <td>3</td>\n",
              "      <td>654</td>\n",
              "      <td>30/07/2020 23:37:39</td>\n",
              "      <td>0</td>\n",
              "      <td>AR</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>[July 25]: All numbers corresponding to Papum ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Chandigarh</td>\n",
              "      <td>1051</td>\n",
              "      <td>667</td>\n",
              "      <td>15</td>\n",
              "      <td>369</td>\n",
              "      <td>31/07/2020 18:32:35</td>\n",
              "      <td>0</td>\n",
              "      <td>CH</td>\n",
              "      <td>35</td>\n",
              "      <td>20</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>Dadra and Nagar Haveli and Daman and Diu</td>\n",
              "      <td>1149</td>\n",
              "      <td>725</td>\n",
              "      <td>2</td>\n",
              "      <td>412</td>\n",
              "      <td>31/07/2020 19:33:09</td>\n",
              "      <td>10</td>\n",
              "      <td>DN</td>\n",
              "      <td>46</td>\n",
              "      <td>41</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Meghalaya</td>\n",
              "      <td>823</td>\n",
              "      <td>215</td>\n",
              "      <td>5</td>\n",
              "      <td>603</td>\n",
              "      <td>31/07/2020 12:28:33</td>\n",
              "      <td>0</td>\n",
              "      <td>ML</td>\n",
              "      <td>20</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>[June 17]:\\nOne case was identified to be fals...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Sikkim</td>\n",
              "      <td>639</td>\n",
              "      <td>231</td>\n",
              "      <td>1</td>\n",
              "      <td>407</td>\n",
              "      <td>31/07/2020 19:30:18</td>\n",
              "      <td>0</td>\n",
              "      <td>SK</td>\n",
              "      <td>29</td>\n",
              "      <td>17</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Mizoram</td>\n",
              "      <td>408</td>\n",
              "      <td>247</td>\n",
              "      <td>0</td>\n",
              "      <td>160</td>\n",
              "      <td>31/07/2020 18:18:39</td>\n",
              "      <td>1</td>\n",
              "      <td>MZ</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>Andaman and Nicobar Islands</td>\n",
              "      <td>548</td>\n",
              "      <td>214</td>\n",
              "      <td>5</td>\n",
              "      <td>328</td>\n",
              "      <td>31/07/2020 20:00:25</td>\n",
              "      <td>1</td>\n",
              "      <td>AN</td>\n",
              "      <td>78</td>\n",
              "      <td>13</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>State Unassigned</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>19/07/2020 09:40:01</td>\n",
              "      <td>0</td>\n",
              "      <td>UN</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>MoHFW website reports that these are the 'case...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>Lakshadweep</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>26/03/2020 07:19:29</td>\n",
              "      <td>0</td>\n",
              "      <td>LD</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                       State  ...                                        State_Notes\n",
              "0                                      Total  ...                                                NaN\n",
              "1                                Maharashtra  ...  304 cases are marked as non-covid deaths in MH...\n",
              "2                                 Tamil Nadu  ...  [July 22]: 444 backdated deceased entries adde...\n",
              "3                                      Delhi  ...  [July 14]: Value for the total tests conducted...\n",
              "4                                  Karnataka  ...  9 cases are classified as non-covid related de...\n",
              "5                             Andhra Pradesh  ...  Total includes patients from other states and ...\n",
              "6                              Uttar Pradesh  ...                                                NaN\n",
              "7                                    Gujarat  ...                                                NaN\n",
              "8                                West Bengal  ...                                                NaN\n",
              "9                                  Telangana  ...  [July 27]\\nTelangana bulletin for the previous...\n",
              "10                                 Rajasthan  ...                                                NaN\n",
              "11                                     Bihar  ...                                                NaN\n",
              "12                                   Haryana  ...                                                NaN\n",
              "13                                     Assam  ...  Includes one case from Nagaland.\\nTotal of 3 p...\n",
              "14                            Madhya Pradesh  ...                                                NaN\n",
              "15                                    Odisha  ...  [July 12th] 20 non-covid deaths reported in st...\n",
              "16                         Jammu and Kashmir  ...                                                NaN\n",
              "17                                    Kerala  ...  Mahe native who expired in Kannur included in ...\n",
              "18                                    Punjab  ...                                                NaN\n",
              "19                                 Jharkhand  ...                                                NaN\n",
              "20                              Chhattisgarh  ...                                                NaN\n",
              "21                               Uttarakhand  ...        38 Migrated cases reduced from Active count\n",
              "22                                       Goa  ...                                                NaN\n",
              "23                                   Tripura  ...                                                NaN\n",
              "24                                Puducherry  ...                                                NaN\n",
              "25                                   Manipur  ...                                                NaN\n",
              "26                          Himachal Pradesh  ...  HP has 18 Migrated cases which are reduced fro...\n",
              "27                                    Ladakh  ...                                                NaN\n",
              "28                                  Nagaland  ...                                                NaN\n",
              "29                         Arunachal Pradesh  ...  [July 25]: All numbers corresponding to Papum ...\n",
              "30                                Chandigarh  ...                                                NaN\n",
              "31  Dadra and Nagar Haveli and Daman and Diu  ...                                                NaN\n",
              "32                                 Meghalaya  ...  [June 17]:\\nOne case was identified to be fals...\n",
              "33                                    Sikkim  ...                                                NaN\n",
              "34                                   Mizoram  ...                                                NaN\n",
              "35               Andaman and Nicobar Islands  ...                                                NaN\n",
              "36                          State Unassigned  ...  MoHFW website reports that these are the 'case...\n",
              "37                               Lakshadweep  ...                                                NaN\n",
              "\n",
              "[38 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HcU_-idXjMJZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "ca6f5258-dc66-4c82-c709-b6520ba73bc9"
      },
      "source": [
        "# see the index colun above? Here is a way to avoid that!\n",
        "df= pd.read_csv(\"https://api.covid19india.org/csv/latest/state_wise.csv\", index_col = 0)\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Confirmed</th>\n",
              "      <th>Recovered</th>\n",
              "      <th>Deaths</th>\n",
              "      <th>Active</th>\n",
              "      <th>Last_Updated_Time</th>\n",
              "      <th>Migrated_Other</th>\n",
              "      <th>State_code</th>\n",
              "      <th>Delta_Confirmed</th>\n",
              "      <th>Delta_Recovered</th>\n",
              "      <th>Delta_Deaths</th>\n",
              "      <th>State_Notes</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>State</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Total</th>\n",
              "      <td>1693879</td>\n",
              "      <td>1093747</td>\n",
              "      <td>36548</td>\n",
              "      <td>563158</td>\n",
              "      <td>31/07/2020 22:08:29</td>\n",
              "      <td>426</td>\n",
              "      <td>TT</td>\n",
              "      <td>54311</td>\n",
              "      <td>34654</td>\n",
              "      <td>761</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Maharashtra</th>\n",
              "      <td>422118</td>\n",
              "      <td>256158</td>\n",
              "      <td>14994</td>\n",
              "      <td>150662</td>\n",
              "      <td>31/07/2020 20:43:39</td>\n",
              "      <td>304</td>\n",
              "      <td>MH</td>\n",
              "      <td>10320</td>\n",
              "      <td>7543</td>\n",
              "      <td>265</td>\n",
              "      <td>304 cases are marked as non-covid deaths in MH...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tamil Nadu</th>\n",
              "      <td>245859</td>\n",
              "      <td>183956</td>\n",
              "      <td>3935</td>\n",
              "      <td>57968</td>\n",
              "      <td>31/07/2020 18:52:33</td>\n",
              "      <td>0</td>\n",
              "      <td>TN</td>\n",
              "      <td>5881</td>\n",
              "      <td>5778</td>\n",
              "      <td>94</td>\n",
              "      <td>[July 22]: 444 backdated deceased entries adde...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Delhi</th>\n",
              "      <td>135598</td>\n",
              "      <td>120930</td>\n",
              "      <td>3963</td>\n",
              "      <td>10705</td>\n",
              "      <td>31/07/2020 16:57:34</td>\n",
              "      <td>0</td>\n",
              "      <td>DL</td>\n",
              "      <td>1195</td>\n",
              "      <td>1206</td>\n",
              "      <td>27</td>\n",
              "      <td>[July 14]: Value for the total tests conducted...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Karnataka</th>\n",
              "      <td>124115</td>\n",
              "      <td>49788</td>\n",
              "      <td>2314</td>\n",
              "      <td>72004</td>\n",
              "      <td>31/07/2020 19:30:10</td>\n",
              "      <td>9</td>\n",
              "      <td>KA</td>\n",
              "      <td>5483</td>\n",
              "      <td>3094</td>\n",
              "      <td>84</td>\n",
              "      <td>9 cases are classified as non-covid related de...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andhra Pradesh</th>\n",
              "      <td>140933</td>\n",
              "      <td>63864</td>\n",
              "      <td>1349</td>\n",
              "      <td>75720</td>\n",
              "      <td>31/07/2020 17:47:34</td>\n",
              "      <td>0</td>\n",
              "      <td>AP</td>\n",
              "      <td>10376</td>\n",
              "      <td>3840</td>\n",
              "      <td>68</td>\n",
              "      <td>Total includes patients from other states and ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Uttar Pradesh</th>\n",
              "      <td>85461</td>\n",
              "      <td>48863</td>\n",
              "      <td>1630</td>\n",
              "      <td>34968</td>\n",
              "      <td>31/07/2020 16:57:36</td>\n",
              "      <td>0</td>\n",
              "      <td>UP</td>\n",
              "      <td>4422</td>\n",
              "      <td>2060</td>\n",
              "      <td>43</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Gujarat</th>\n",
              "      <td>61438</td>\n",
              "      <td>45009</td>\n",
              "      <td>2436</td>\n",
              "      <td>13993</td>\n",
              "      <td>31/07/2020 20:35:11</td>\n",
              "      <td>0</td>\n",
              "      <td>GJ</td>\n",
              "      <td>1153</td>\n",
              "      <td>833</td>\n",
              "      <td>22</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>West Bengal</th>\n",
              "      <td>70188</td>\n",
              "      <td>48374</td>\n",
              "      <td>1581</td>\n",
              "      <td>20233</td>\n",
              "      <td>31/07/2020 22:08:31</td>\n",
              "      <td>0</td>\n",
              "      <td>WB</td>\n",
              "      <td>2496</td>\n",
              "      <td>2118</td>\n",
              "      <td>45</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Telangana</th>\n",
              "      <td>62703</td>\n",
              "      <td>45388</td>\n",
              "      <td>519</td>\n",
              "      <td>16796</td>\n",
              "      <td>31/07/2020 09:29:31</td>\n",
              "      <td>0</td>\n",
              "      <td>TG</td>\n",
              "      <td>1986</td>\n",
              "      <td>816</td>\n",
              "      <td>14</td>\n",
              "      <td>[July 27]\\nTelangana bulletin for the previous...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Rajasthan</th>\n",
              "      <td>42083</td>\n",
              "      <td>29845</td>\n",
              "      <td>680</td>\n",
              "      <td>11558</td>\n",
              "      <td>31/07/2020 22:08:33</td>\n",
              "      <td>0</td>\n",
              "      <td>RJ</td>\n",
              "      <td>1147</td>\n",
              "      <td>614</td>\n",
              "      <td>13</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bihar</th>\n",
              "      <td>50987</td>\n",
              "      <td>33650</td>\n",
              "      <td>298</td>\n",
              "      <td>17038</td>\n",
              "      <td>31/07/2020 17:47:37</td>\n",
              "      <td>1</td>\n",
              "      <td>BR</td>\n",
              "      <td>2986</td>\n",
              "      <td>1977</td>\n",
              "      <td>13</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Haryana</th>\n",
              "      <td>34965</td>\n",
              "      <td>28227</td>\n",
              "      <td>421</td>\n",
              "      <td>6317</td>\n",
              "      <td>31/07/2020 20:00:13</td>\n",
              "      <td>0</td>\n",
              "      <td>HR</td>\n",
              "      <td>711</td>\n",
              "      <td>887</td>\n",
              "      <td>4</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Assam</th>\n",
              "      <td>38408</td>\n",
              "      <td>29081</td>\n",
              "      <td>98</td>\n",
              "      <td>9226</td>\n",
              "      <td>31/07/2020 19:51:54</td>\n",
              "      <td>3</td>\n",
              "      <td>AS</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>Includes one case from Nagaland.\\nTotal of 3 p...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Madhya Pradesh</th>\n",
              "      <td>31806</td>\n",
              "      <td>22271</td>\n",
              "      <td>867</td>\n",
              "      <td>8668</td>\n",
              "      <td>31/07/2020 19:31:22</td>\n",
              "      <td>0</td>\n",
              "      <td>MP</td>\n",
              "      <td>838</td>\n",
              "      <td>614</td>\n",
              "      <td>10</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Odisha</th>\n",
              "      <td>31877</td>\n",
              "      <td>20518</td>\n",
              "      <td>214</td>\n",
              "      <td>11145</td>\n",
              "      <td>31/07/2020 20:07:48</td>\n",
              "      <td>0</td>\n",
              "      <td>OR</td>\n",
              "      <td>1499</td>\n",
              "      <td>772</td>\n",
              "      <td>9</td>\n",
              "      <td>[July 12th] 20 non-covid deaths reported in st...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Jammu and Kashmir</th>\n",
              "      <td>20359</td>\n",
              "      <td>12217</td>\n",
              "      <td>377</td>\n",
              "      <td>7765</td>\n",
              "      <td>31/07/2020 18:08:34</td>\n",
              "      <td>0</td>\n",
              "      <td>JK</td>\n",
              "      <td>490</td>\n",
              "      <td>375</td>\n",
              "      <td>12</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kerala</th>\n",
              "      <td>23614</td>\n",
              "      <td>13023</td>\n",
              "      <td>74</td>\n",
              "      <td>10495</td>\n",
              "      <td>31/07/2020 19:52:01</td>\n",
              "      <td>22</td>\n",
              "      <td>KL</td>\n",
              "      <td>1310</td>\n",
              "      <td>864</td>\n",
              "      <td>3</td>\n",
              "      <td>Mahe native who expired in Kannur included in ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Punjab</th>\n",
              "      <td>16119</td>\n",
              "      <td>10734</td>\n",
              "      <td>386</td>\n",
              "      <td>4999</td>\n",
              "      <td>31/07/2020 20:58:34</td>\n",
              "      <td>0</td>\n",
              "      <td>PB</td>\n",
              "      <td>663</td>\n",
              "      <td>225</td>\n",
              "      <td>16</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Jharkhand</th>\n",
              "      <td>10488</td>\n",
              "      <td>4176</td>\n",
              "      <td>104</td>\n",
              "      <td>6208</td>\n",
              "      <td>31/07/2020 13:42:33</td>\n",
              "      <td>0</td>\n",
              "      <td>JH</td>\n",
              "      <td>89</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Chhattisgarh</th>\n",
              "      <td>9086</td>\n",
              "      <td>6230</td>\n",
              "      <td>53</td>\n",
              "      <td>2803</td>\n",
              "      <td>31/07/2020 20:43:43</td>\n",
              "      <td>0</td>\n",
              "      <td>CT</td>\n",
              "      <td>230</td>\n",
              "      <td>309</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Uttarakhand</th>\n",
              "      <td>7183</td>\n",
              "      <td>4168</td>\n",
              "      <td>80</td>\n",
              "      <td>2897</td>\n",
              "      <td>31/07/2020 20:16:36</td>\n",
              "      <td>38</td>\n",
              "      <td>UT</td>\n",
              "      <td>118</td>\n",
              "      <td>172</td>\n",
              "      <td>4</td>\n",
              "      <td>38 Migrated cases reduced from Active count</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Goa</th>\n",
              "      <td>5913</td>\n",
              "      <td>4211</td>\n",
              "      <td>45</td>\n",
              "      <td>1657</td>\n",
              "      <td>31/07/2020 20:27:03</td>\n",
              "      <td>0</td>\n",
              "      <td>GA</td>\n",
              "      <td>209</td>\n",
              "      <td>206</td>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tripura</th>\n",
              "      <td>4722</td>\n",
              "      <td>2962</td>\n",
              "      <td>21</td>\n",
              "      <td>1721</td>\n",
              "      <td>31/07/2020 08:59:30</td>\n",
              "      <td>18</td>\n",
              "      <td>TR</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Puducherry</th>\n",
              "      <td>3472</td>\n",
              "      <td>2100</td>\n",
              "      <td>49</td>\n",
              "      <td>1323</td>\n",
              "      <td>31/07/2020 18:49:37</td>\n",
              "      <td>0</td>\n",
              "      <td>PY</td>\n",
              "      <td>174</td>\n",
              "      <td>142</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Manipur</th>\n",
              "      <td>2621</td>\n",
              "      <td>1689</td>\n",
              "      <td>5</td>\n",
              "      <td>927</td>\n",
              "      <td>31/07/2020 19:52:10</td>\n",
              "      <td>0</td>\n",
              "      <td>MN</td>\n",
              "      <td>116</td>\n",
              "      <td>17</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Himachal Pradesh</th>\n",
              "      <td>2564</td>\n",
              "      <td>1459</td>\n",
              "      <td>13</td>\n",
              "      <td>1075</td>\n",
              "      <td>31/07/2020 21:54:37</td>\n",
              "      <td>17</td>\n",
              "      <td>HP</td>\n",
              "      <td>58</td>\n",
              "      <td>72</td>\n",
              "      <td>0</td>\n",
              "      <td>HP has 18 Migrated cases which are reduced fro...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ladakh</th>\n",
              "      <td>1404</td>\n",
              "      <td>1095</td>\n",
              "      <td>7</td>\n",
              "      <td>302</td>\n",
              "      <td>31/07/2020 20:00:19</td>\n",
              "      <td>0</td>\n",
              "      <td>LA</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Nagaland</th>\n",
              "      <td>1693</td>\n",
              "      <td>635</td>\n",
              "      <td>4</td>\n",
              "      <td>1052</td>\n",
              "      <td>31/07/2020 20:00:22</td>\n",
              "      <td>2</td>\n",
              "      <td>NL</td>\n",
              "      <td>127</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Arunachal Pradesh</th>\n",
              "      <td>1484</td>\n",
              "      <td>827</td>\n",
              "      <td>3</td>\n",
              "      <td>654</td>\n",
              "      <td>30/07/2020 23:37:39</td>\n",
              "      <td>0</td>\n",
              "      <td>AR</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>[July 25]: All numbers corresponding to Papum ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Chandigarh</th>\n",
              "      <td>1051</td>\n",
              "      <td>667</td>\n",
              "      <td>15</td>\n",
              "      <td>369</td>\n",
              "      <td>31/07/2020 18:32:35</td>\n",
              "      <td>0</td>\n",
              "      <td>CH</td>\n",
              "      <td>35</td>\n",
              "      <td>20</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dadra and Nagar Haveli and Daman and Diu</th>\n",
              "      <td>1149</td>\n",
              "      <td>725</td>\n",
              "      <td>2</td>\n",
              "      <td>412</td>\n",
              "      <td>31/07/2020 19:33:09</td>\n",
              "      <td>10</td>\n",
              "      <td>DN</td>\n",
              "      <td>46</td>\n",
              "      <td>41</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Meghalaya</th>\n",
              "      <td>823</td>\n",
              "      <td>215</td>\n",
              "      <td>5</td>\n",
              "      <td>603</td>\n",
              "      <td>31/07/2020 12:28:33</td>\n",
              "      <td>0</td>\n",
              "      <td>ML</td>\n",
              "      <td>20</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>[June 17]:\\nOne case was identified to be fals...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sikkim</th>\n",
              "      <td>639</td>\n",
              "      <td>231</td>\n",
              "      <td>1</td>\n",
              "      <td>407</td>\n",
              "      <td>31/07/2020 19:30:18</td>\n",
              "      <td>0</td>\n",
              "      <td>SK</td>\n",
              "      <td>29</td>\n",
              "      <td>17</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mizoram</th>\n",
              "      <td>408</td>\n",
              "      <td>247</td>\n",
              "      <td>0</td>\n",
              "      <td>160</td>\n",
              "      <td>31/07/2020 18:18:39</td>\n",
              "      <td>1</td>\n",
              "      <td>MZ</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andaman and Nicobar Islands</th>\n",
              "      <td>548</td>\n",
              "      <td>214</td>\n",
              "      <td>5</td>\n",
              "      <td>328</td>\n",
              "      <td>31/07/2020 20:00:25</td>\n",
              "      <td>1</td>\n",
              "      <td>AN</td>\n",
              "      <td>78</td>\n",
              "      <td>13</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>State Unassigned</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>19/07/2020 09:40:01</td>\n",
              "      <td>0</td>\n",
              "      <td>UN</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>MoHFW website reports that these are the 'case...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Lakshadweep</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>26/03/2020 07:19:29</td>\n",
              "      <td>0</td>\n",
              "      <td>LD</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                          Confirmed  ...                                        State_Notes\n",
              "State                                                ...                                                   \n",
              "Total                                       1693879  ...                                                NaN\n",
              "Maharashtra                                  422118  ...  304 cases are marked as non-covid deaths in MH...\n",
              "Tamil Nadu                                   245859  ...  [July 22]: 444 backdated deceased entries adde...\n",
              "Delhi                                        135598  ...  [July 14]: Value for the total tests conducted...\n",
              "Karnataka                                    124115  ...  9 cases are classified as non-covid related de...\n",
              "Andhra Pradesh                               140933  ...  Total includes patients from other states and ...\n",
              "Uttar Pradesh                                 85461  ...                                                NaN\n",
              "Gujarat                                       61438  ...                                                NaN\n",
              "West Bengal                                   70188  ...                                                NaN\n",
              "Telangana                                     62703  ...  [July 27]\\nTelangana bulletin for the previous...\n",
              "Rajasthan                                     42083  ...                                                NaN\n",
              "Bihar                                         50987  ...                                                NaN\n",
              "Haryana                                       34965  ...                                                NaN\n",
              "Assam                                         38408  ...  Includes one case from Nagaland.\\nTotal of 3 p...\n",
              "Madhya Pradesh                                31806  ...                                                NaN\n",
              "Odisha                                        31877  ...  [July 12th] 20 non-covid deaths reported in st...\n",
              "Jammu and Kashmir                             20359  ...                                                NaN\n",
              "Kerala                                        23614  ...  Mahe native who expired in Kannur included in ...\n",
              "Punjab                                        16119  ...                                                NaN\n",
              "Jharkhand                                     10488  ...                                                NaN\n",
              "Chhattisgarh                                   9086  ...                                                NaN\n",
              "Uttarakhand                                    7183  ...        38 Migrated cases reduced from Active count\n",
              "Goa                                            5913  ...                                                NaN\n",
              "Tripura                                        4722  ...                                                NaN\n",
              "Puducherry                                     3472  ...                                                NaN\n",
              "Manipur                                        2621  ...                                                NaN\n",
              "Himachal Pradesh                               2564  ...  HP has 18 Migrated cases which are reduced fro...\n",
              "Ladakh                                         1404  ...                                                NaN\n",
              "Nagaland                                       1693  ...                                                NaN\n",
              "Arunachal Pradesh                              1484  ...  [July 25]: All numbers corresponding to Papum ...\n",
              "Chandigarh                                     1051  ...                                                NaN\n",
              "Dadra and Nagar Haveli and Daman and Diu       1149  ...                                                NaN\n",
              "Meghalaya                                       823  ...  [June 17]:\\nOne case was identified to be fals...\n",
              "Sikkim                                          639  ...                                                NaN\n",
              "Mizoram                                         408  ...                                                NaN\n",
              "Andaman and Nicobar Islands                     548  ...                                                NaN\n",
              "State Unassigned                                  0  ...  MoHFW website reports that these are the 'case...\n",
              "Lakshadweep                                       0  ...                                                NaN\n",
              "\n",
              "[38 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9ITFWgOK69UN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        },
        "outputId": "d0273912-dbf2-4bb3-a313-d1f7dfb070a4"
      },
      "source": [
        "# find the details or information about the dataframe in hand\n",
        "print(f'The number of rows and columns (shape of the df) in this dataframe = {df.shape}')\n",
        "print(f'The number of rows in this dataframe = {df.shape[0]}')\n",
        "print(f'The number of columns in this dataframe = {df.shape[1]}')\n",
        "print(f'The number of elements in this dataframe = {df.size}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The number of rows and columns (shape of the df) in this dataframe = (38, 11)\n",
            "The number of rows in this dataframe = 38\n",
            "The number of columns in this dataframe = 11\n",
            "The number of elements in this dataframe = 418\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-LaJk1nx82o-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 510
        },
        "outputId": "68169007-ccd6-4668-a600-e789dc72bb15"
      },
      "source": [
        "# first five rows of the dataframe\n",
        "df.head() # by default it prints first five rows\n",
        "# we can state the number of rows we want in the paranthesis like - head.df(2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Confirmed</th>\n",
              "      <th>Recovered</th>\n",
              "      <th>Deaths</th>\n",
              "      <th>Active</th>\n",
              "      <th>Last_Updated_Time</th>\n",
              "      <th>Migrated_Other</th>\n",
              "      <th>State_code</th>\n",
              "      <th>Delta_Confirmed</th>\n",
              "      <th>Delta_Recovered</th>\n",
              "      <th>Delta_Deaths</th>\n",
              "      <th>State_Notes</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>State</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Total</th>\n",
              "      <td>1693879</td>\n",
              "      <td>1093747</td>\n",
              "      <td>36548</td>\n",
              "      <td>563158</td>\n",
              "      <td>31/07/2020 22:08:29</td>\n",
              "      <td>426</td>\n",
              "      <td>TT</td>\n",
              "      <td>54311</td>\n",
              "      <td>34654</td>\n",
              "      <td>761</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Maharashtra</th>\n",
              "      <td>422118</td>\n",
              "      <td>256158</td>\n",
              "      <td>14994</td>\n",
              "      <td>150662</td>\n",
              "      <td>31/07/2020 20:43:39</td>\n",
              "      <td>304</td>\n",
              "      <td>MH</td>\n",
              "      <td>10320</td>\n",
              "      <td>7543</td>\n",
              "      <td>265</td>\n",
              "      <td>304 cases are marked as non-covid deaths in MH...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tamil Nadu</th>\n",
              "      <td>245859</td>\n",
              "      <td>183956</td>\n",
              "      <td>3935</td>\n",
              "      <td>57968</td>\n",
              "      <td>31/07/2020 18:52:33</td>\n",
              "      <td>0</td>\n",
              "      <td>TN</td>\n",
              "      <td>5881</td>\n",
              "      <td>5778</td>\n",
              "      <td>94</td>\n",
              "      <td>[July 22]: 444 backdated deceased entries adde...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Delhi</th>\n",
              "      <td>135598</td>\n",
              "      <td>120930</td>\n",
              "      <td>3963</td>\n",
              "      <td>10705</td>\n",
              "      <td>31/07/2020 16:57:34</td>\n",
              "      <td>0</td>\n",
              "      <td>DL</td>\n",
              "      <td>1195</td>\n",
              "      <td>1206</td>\n",
              "      <td>27</td>\n",
              "      <td>[July 14]: Value for the total tests conducted...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Karnataka</th>\n",
              "      <td>124115</td>\n",
              "      <td>49788</td>\n",
              "      <td>2314</td>\n",
              "      <td>72004</td>\n",
              "      <td>31/07/2020 19:30:10</td>\n",
              "      <td>9</td>\n",
              "      <td>KA</td>\n",
              "      <td>5483</td>\n",
              "      <td>3094</td>\n",
              "      <td>84</td>\n",
              "      <td>9 cases are classified as non-covid related de...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             Confirmed  ...                                        State_Notes\n",
              "State                   ...                                                   \n",
              "Total          1693879  ...                                                NaN\n",
              "Maharashtra     422118  ...  304 cases are marked as non-covid deaths in MH...\n",
              "Tamil Nadu      245859  ...  [July 22]: 444 backdated deceased entries adde...\n",
              "Delhi           135598  ...  [July 14]: Value for the total tests conducted...\n",
              "Karnataka       124115  ...  9 cases are classified as non-covid related de...\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 93
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uNAlZiQp9KTD",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 408
        },
        "outputId": "2a8d501b-1c38-4184-cb3e-965647d04770"
      },
      "source": [
        "#last five rows of the dataframe\n",
        "df.tail() # by default it returns the last 5 rows\n",
        "# we can state the number of rows we want in the paranthesis like - tail.df(2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Confirmed</th>\n",
              "      <th>Recovered</th>\n",
              "      <th>Deaths</th>\n",
              "      <th>Active</th>\n",
              "      <th>Last_Updated_Time</th>\n",
              "      <th>Migrated_Other</th>\n",
              "      <th>State_code</th>\n",
              "      <th>Delta_Confirmed</th>\n",
              "      <th>Delta_Recovered</th>\n",
              "      <th>Delta_Deaths</th>\n",
              "      <th>State_Notes</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>State</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Sikkim</th>\n",
              "      <td>639</td>\n",
              "      <td>231</td>\n",
              "      <td>1</td>\n",
              "      <td>407</td>\n",
              "      <td>31/07/2020 19:30:18</td>\n",
              "      <td>0</td>\n",
              "      <td>SK</td>\n",
              "      <td>29</td>\n",
              "      <td>17</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mizoram</th>\n",
              "      <td>408</td>\n",
              "      <td>247</td>\n",
              "      <td>0</td>\n",
              "      <td>160</td>\n",
              "      <td>31/07/2020 18:18:39</td>\n",
              "      <td>1</td>\n",
              "      <td>MZ</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andaman and Nicobar Islands</th>\n",
              "      <td>548</td>\n",
              "      <td>214</td>\n",
              "      <td>5</td>\n",
              "      <td>328</td>\n",
              "      <td>31/07/2020 20:00:25</td>\n",
              "      <td>1</td>\n",
              "      <td>AN</td>\n",
              "      <td>78</td>\n",
              "      <td>13</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>State Unassigned</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>19/07/2020 09:40:01</td>\n",
              "      <td>0</td>\n",
              "      <td>UN</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>MoHFW website reports that these are the 'case...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Lakshadweep</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>26/03/2020 07:19:29</td>\n",
              "      <td>0</td>\n",
              "      <td>LD</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                             Confirmed  ...                                        State_Notes\n",
              "State                                   ...                                                   \n",
              "Sikkim                             639  ...                                                NaN\n",
              "Mizoram                            408  ...                                                NaN\n",
              "Andaman and Nicobar Islands        548  ...                                                NaN\n",
              "State Unassigned                     0  ...  MoHFW website reports that these are the 'case...\n",
              "Lakshadweep                          0  ...                                                NaN\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eO1V6Pb8ZyMA",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "outputId": "3c93415a-a1c1-46e5-b84c-98035c38885a"
      },
      "source": [
        "# information for column names and data types of the dataframe at hand\n",
        "df.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Index: 38 entries, Total to Lakshadweep\n",
            "Data columns (total 11 columns):\n",
            " #   Column             Non-Null Count  Dtype \n",
            "---  ------             --------------  ----- \n",
            " 0   Confirmed          38 non-null     int64 \n",
            " 1   Recovered          38 non-null     int64 \n",
            " 2   Deaths             38 non-null     int64 \n",
            " 3   Active             38 non-null     int64 \n",
            " 4   Last_Updated_Time  38 non-null     object\n",
            " 5   Migrated_Other     38 non-null     int64 \n",
            " 6   State_code         38 non-null     object\n",
            " 7   Delta_Confirmed    38 non-null     int64 \n",
            " 8   Delta_Recovered    38 non-null     int64 \n",
            " 9   Delta_Deaths       38 non-null     int64 \n",
            " 10  State_Notes        14 non-null     object\n",
            "dtypes: int64(8), object(3)\n",
            "memory usage: 4.8+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "drR_l8JtrT5U",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        },
        "outputId": "1a45fb5d-d9fb-4348-e9ec-f8cf5c20c644"
      },
      "source": [
        "#get the column names\n",
        "df.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Confirmed', 'Recovered', 'Deaths', 'Active', 'Last_Updated_Time',\n",
              "       'Migrated_Other', 'State_code', 'Delta_Confirmed', 'Delta_Recovered',\n",
              "       'Delta_Deaths', 'State_Notes'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "paVMNMCTrhPy",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 697
        },
        "outputId": "5c69eaa4-77e4-4283-d582-aec6b6241ac6"
      },
      "source": [
        "# get all data from a column\n",
        "df['Confirmed']\n",
        "# the above output was in form of a Series"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "State\n",
              "Total                                       1690546\n",
              "Maharashtra                                  422118\n",
              "Tamil Nadu                                   245859\n",
              "Delhi                                        135598\n",
              "Karnataka                                    124115\n",
              "Andhra Pradesh                               140933\n",
              "Uttar Pradesh                                 85461\n",
              "Gujarat                                       61438\n",
              "West Bengal                                   67692\n",
              "Telangana                                     62703\n",
              "Rajasthan                                     41298\n",
              "Bihar                                         50987\n",
              "Haryana                                       34965\n",
              "Assam                                         38408\n",
              "Madhya Pradesh                                31806\n",
              "Odisha                                        31877\n",
              "Jammu and Kashmir                             20359\n",
              "Kerala                                        23614\n",
              "Punjab                                        16119\n",
              "Jharkhand                                     10488\n",
              "Chhattisgarh                                   9086\n",
              "Uttarakhand                                    7183\n",
              "Goa                                            5913\n",
              "Tripura                                        4722\n",
              "Puducherry                                     3472\n",
              "Manipur                                        2621\n",
              "Himachal Pradesh                               2512\n",
              "Ladakh                                         1404\n",
              "Nagaland                                       1693\n",
              "Arunachal Pradesh                              1484\n",
              "Chandigarh                                     1051\n",
              "Dadra and Nagar Haveli and Daman and Diu       1149\n",
              "Meghalaya                                       823\n",
              "Sikkim                                          639\n",
              "Mizoram                                         408\n",
              "Andaman and Nicobar Islands                     548\n",
              "State Unassigned                                  0\n",
              "Lakshadweep                                       0\n",
              "Name: Confirmed, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0wdWUKcNsK-m",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "3ae87547-0f61-40f3-ef55-04e35314b651"
      },
      "source": [
        "# get all data from a column - another example\n",
        "df[['Confirmed','Active']]\n",
        "# the above output was in form of a dataframe"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Confirmed</th>\n",
              "      <th>Active</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>State</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Total</th>\n",
              "      <td>1693879</td>\n",
              "      <td>563158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Maharashtra</th>\n",
              "      <td>422118</td>\n",
              "      <td>150662</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tamil Nadu</th>\n",
              "      <td>245859</td>\n",
              "      <td>57968</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Delhi</th>\n",
              "      <td>135598</td>\n",
              "      <td>10705</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Karnataka</th>\n",
              "      <td>124115</td>\n",
              "      <td>72004</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andhra Pradesh</th>\n",
              "      <td>140933</td>\n",
              "      <td>75720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Uttar Pradesh</th>\n",
              "      <td>85461</td>\n",
              "      <td>34968</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Gujarat</th>\n",
              "      <td>61438</td>\n",
              "      <td>13993</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>West Bengal</th>\n",
              "      <td>70188</td>\n",
              "      <td>20233</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Telangana</th>\n",
              "      <td>62703</td>\n",
              "      <td>16796</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Rajasthan</th>\n",
              "      <td>42083</td>\n",
              "      <td>11558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bihar</th>\n",
              "      <td>50987</td>\n",
              "      <td>17038</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Haryana</th>\n",
              "      <td>34965</td>\n",
              "      <td>6317</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Assam</th>\n",
              "      <td>38408</td>\n",
              "      <td>9226</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Madhya Pradesh</th>\n",
              "      <td>31806</td>\n",
              "      <td>8668</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Odisha</th>\n",
              "      <td>31877</td>\n",
              "      <td>11145</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Jammu and Kashmir</th>\n",
              "      <td>20359</td>\n",
              "      <td>7765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kerala</th>\n",
              "      <td>23614</td>\n",
              "      <td>10495</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Punjab</th>\n",
              "      <td>16119</td>\n",
              "      <td>4999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Jharkhand</th>\n",
              "      <td>10488</td>\n",
              "      <td>6208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Chhattisgarh</th>\n",
              "      <td>9086</td>\n",
              "      <td>2803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Uttarakhand</th>\n",
              "      <td>7183</td>\n",
              "      <td>2897</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Goa</th>\n",
              "      <td>5913</td>\n",
              "      <td>1657</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tripura</th>\n",
              "      <td>4722</td>\n",
              "      <td>1721</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Puducherry</th>\n",
              "      <td>3472</td>\n",
              "      <td>1323</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Manipur</th>\n",
              "      <td>2621</td>\n",
              "      <td>927</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Himachal Pradesh</th>\n",
              "      <td>2564</td>\n",
              "      <td>1075</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ladakh</th>\n",
              "      <td>1404</td>\n",
              "      <td>302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Nagaland</th>\n",
              "      <td>1693</td>\n",
              "      <td>1052</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Arunachal Pradesh</th>\n",
              "      <td>1484</td>\n",
              "      <td>654</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Chandigarh</th>\n",
              "      <td>1051</td>\n",
              "      <td>369</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dadra and Nagar Haveli and Daman and Diu</th>\n",
              "      <td>1149</td>\n",
              "      <td>412</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Meghalaya</th>\n",
              "      <td>823</td>\n",
              "      <td>603</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sikkim</th>\n",
              "      <td>639</td>\n",
              "      <td>407</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mizoram</th>\n",
              "      <td>408</td>\n",
              "      <td>160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andaman and Nicobar Islands</th>\n",
              "      <td>548</td>\n",
              "      <td>328</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>State Unassigned</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Lakshadweep</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                          Confirmed  Active\n",
              "State                                                      \n",
              "Total                                       1693879  563158\n",
              "Maharashtra                                  422118  150662\n",
              "Tamil Nadu                                   245859   57968\n",
              "Delhi                                        135598   10705\n",
              "Karnataka                                    124115   72004\n",
              "Andhra Pradesh                               140933   75720\n",
              "Uttar Pradesh                                 85461   34968\n",
              "Gujarat                                       61438   13993\n",
              "West Bengal                                   70188   20233\n",
              "Telangana                                     62703   16796\n",
              "Rajasthan                                     42083   11558\n",
              "Bihar                                         50987   17038\n",
              "Haryana                                       34965    6317\n",
              "Assam                                         38408    9226\n",
              "Madhya Pradesh                                31806    8668\n",
              "Odisha                                        31877   11145\n",
              "Jammu and Kashmir                             20359    7765\n",
              "Kerala                                        23614   10495\n",
              "Punjab                                        16119    4999\n",
              "Jharkhand                                     10488    6208\n",
              "Chhattisgarh                                   9086    2803\n",
              "Uttarakhand                                    7183    2897\n",
              "Goa                                            5913    1657\n",
              "Tripura                                        4722    1721\n",
              "Puducherry                                     3472    1323\n",
              "Manipur                                        2621     927\n",
              "Himachal Pradesh                               2564    1075\n",
              "Ladakh                                         1404     302\n",
              "Nagaland                                       1693    1052\n",
              "Arunachal Pradesh                              1484     654\n",
              "Chandigarh                                     1051     369\n",
              "Dadra and Nagar Haveli and Daman and Diu       1149     412\n",
              "Meghalaya                                       823     603\n",
              "Sikkim                                          639     407\n",
              "Mizoram                                         408     160\n",
              "Andaman and Nicobar Islands                     548     328\n",
              "State Unassigned                                  0       0\n",
              "Lakshadweep                                       0       0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "922uWsa5au9p",
        "colab_type": "text"
      },
      "source": [
        "#**loc and iloc** <br>\n",
        "**Accessing data from the dataframe - Indexing and selecting data**\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nDh8a8BraZny",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "outputId": "7992cfbe-ac15-4c89-afdc-d70d0fa707b9"
      },
      "source": [
        "#loc = label based index, i.e, we can access the column and its whole row using the text present in it\n",
        "print(f'This will give output in form of a Series \\n\\n{df.loc[\"Delhi\"]}')\n",
        "print(f'\\nDatatype of above output \\n{type(df.loc[\"Delhi\"])}') #just for the peace of mind :p"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "This will give output in form of a Series \n",
            "\n",
            "Confirmed                                                       135598\n",
            "Recovered                                                       120930\n",
            "Deaths                                                            3963\n",
            "Active                                                           10705\n",
            "Last_Updated_Time                                  31/07/2020 16:57:34\n",
            "Migrated_Other                                                       0\n",
            "State_code                                                          DL\n",
            "Delta_Confirmed                                                   1195\n",
            "Delta_Recovered                                                   1206\n",
            "Delta_Deaths                                                        27\n",
            "State_Notes          [July 14]: Value for the total tests conducted...\n",
            "Name: Delhi, dtype: object\n",
            "\n",
            "Datatype of above output \n",
            "<class 'pandas.core.series.Series'>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w4eZb3vjeqsX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "outputId": "3ae24353-0c12-442b-c909-29d680e9b66d"
      },
      "source": [
        "#loc = label based index, i.e, we can access the column and its whole row using the text present in it\n",
        "print(f'This will give output in form of a DataFrame \\n\\n{df.loc[[\"Delhi\"]]}')\n",
        "print(f'\\nDatatype of above output \\n{type(df.loc[[\"Delhi\"]])}') #just for the peace of mind :p"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "This will give output in form of a DataFrame \n",
            "\n",
            "       Confirmed  ...                                        State_Notes\n",
            "State             ...                                                   \n",
            "Delhi     135598  ...  [July 14]: Value for the total tests conducted...\n",
            "\n",
            "[1 rows x 11 columns]\n",
            "\n",
            "Datatype of above output \n",
            "<class 'pandas.core.frame.DataFrame'>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LZ7PmMCAoHL7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "outputId": "2c4badc5-8481-44cf-cf33-a76b0f56efc5"
      },
      "source": [
        "#iloc = integer based index, i.e, we can access the column and its whole row using it's number or position\n",
        "print(f'This will give output in form of a Series \\n\\n{df.iloc[3]}')\n",
        "print(f'\\nDatatype of above output \\n{type(df.iloc[3])}') #just for the peace of mind :p"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "This will give output in form of a Series \n",
            "\n",
            "Confirmed                                                       135598\n",
            "Recovered                                                       120930\n",
            "Deaths                                                            3963\n",
            "Active                                                           10705\n",
            "Last_Updated_Time                                  31/07/2020 16:57:34\n",
            "Migrated_Other                                                       0\n",
            "State_code                                                          DL\n",
            "Delta_Confirmed                                                   1195\n",
            "Delta_Recovered                                                   1206\n",
            "Delta_Deaths                                                        27\n",
            "State_Notes          [July 14]: Value for the total tests conducted...\n",
            "Name: Delhi, dtype: object\n",
            "\n",
            "Datatype of above output \n",
            "<class 'pandas.core.series.Series'>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0eVSVW2romn7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "outputId": "40a98433-c787-4fc0-f86d-fb8e27e3a2aa"
      },
      "source": [
        "#iloc = integer based index, i.e, we can access the column and its whole row using it's number or position\n",
        "print(f'This will give output in form of a Dataframe \\n\\n{df.iloc[[3]]}')\n",
        "print(f'\\nDatatype of above output \\n{type(df.iloc[[3]])}') #just for the peace of mind :p"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "This will give output in form of a Dataframe \n",
            "\n",
            "       Confirmed  ...                                        State_Notes\n",
            "State             ...                                                   \n",
            "Delhi     135598  ...  [July 14]: Value for the total tests conducted...\n",
            "\n",
            "[1 rows x 11 columns]\n",
            "\n",
            "Datatype of above output \n",
            "<class 'pandas.core.frame.DataFrame'>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rcPMhT_U0t6Z",
        "colab_type": "text"
      },
      "source": [
        "#Some statistics and other mathematical features that pandas can help with"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nq_kOG2n1Ndx",
        "colab_type": "text"
      },
      "source": [
        "**Maximum, Minimum**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SZ2Lle6w0eA7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 561
        },
        "outputId": "aadb1496-96d2-475a-fade-5fed26a7398a"
      },
      "source": [
        "print(f'Maximum : \\n\\n{df.max()} \\n\\n')\n",
        "print(f'Minimum : \\n\\n{df.min()}\\n\\n')\n",
        "print(\"Since the datraframe in hand has several types of values, the max and min values are not necessarily from one single row.\\nWe need to be careful about this!\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Maximum : \n",
            "\n",
            "Confirmed                        1693879\n",
            "Recovered                        1093747\n",
            "Deaths                             36548\n",
            "Active                            563158\n",
            "Last_Updated_Time    31/07/2020 22:08:33\n",
            "Migrated_Other                       426\n",
            "State_code                            WB\n",
            "Delta_Confirmed                    54311\n",
            "Delta_Recovered                    34654\n",
            "Delta_Deaths                         761\n",
            "dtype: object \n",
            "\n",
            "\n",
            "Minimum : \n",
            "\n",
            "Confirmed                              0\n",
            "Recovered                              0\n",
            "Deaths                                 0\n",
            "Active                                 0\n",
            "Last_Updated_Time    19/07/2020 09:40:01\n",
            "Migrated_Other                         0\n",
            "State_code                            AN\n",
            "Delta_Confirmed                        0\n",
            "Delta_Recovered                        0\n",
            "Delta_Deaths                           0\n",
            "dtype: object\n",
            "\n",
            "\n",
            "Since the datraframe in hand has several types of values, the max and min values are not necessarily from one single row.\n",
            "We need to be careful about this!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q_a7TEsiQgqx",
        "colab_type": "text"
      },
      "source": [
        "**Mean, Median**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qLhhTAPDQf2n",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 459
        },
        "outputId": "556c09a3-07b7-4d13-b750-79cd94d83ddc"
      },
      "source": [
        "print(f'Mean : \\n\\n{df.mean()} \\n\\n')\n",
        "print(f'Median : \\n\\n{df.median()} \\n\\n')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mean : \n",
            "\n",
            "Confirmed          89151.526316\n",
            "Recovered          57565.631579\n",
            "Deaths              1923.578947\n",
            "Active             29639.894737\n",
            "Migrated_Other        22.421053\n",
            "Delta_Confirmed     2858.473684\n",
            "Delta_Recovered     1823.894737\n",
            "Delta_Deaths          40.052632\n",
            "dtype: float64 \n",
            "\n",
            "\n",
            "Median : \n",
            "\n",
            "Confirmed          13303.5\n",
            "Recovered           8482.0\n",
            "Deaths                89.0\n",
            "Active              5603.5\n",
            "Migrated_Other         0.0\n",
            "Delta_Confirmed      219.5\n",
            "Delta_Recovered      215.5\n",
            "Delta_Deaths           3.5\n",
            "dtype: float64 \n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7Guok7Hl40rl",
        "colab_type": "text"
      },
      "source": [
        "**Variance, Standard Deviation**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i65iXC224zjw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 459
        },
        "outputId": "01911a17-114d-4237-fcaa-5c5f4f443db2"
      },
      "source": [
        "print(f'Standard Deviation : \\n\\n{df.std()} \\n\\n')\n",
        "print(f'Variance : \\n\\n{df.var()} \\n\\n')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Standard Deviation : \n",
            "\n",
            "Confirmed          279482.543964\n",
            "Recovered          180460.323717\n",
            "Deaths               6306.478645\n",
            "Active              93574.026812\n",
            "Migrated_Other         83.427791\n",
            "Delta_Confirmed      8954.488353\n",
            "Delta_Recovered      5713.456107\n",
            "Delta_Deaths          128.943932\n",
            "dtype: float64 \n",
            "\n",
            "\n",
            "Variance : \n",
            "\n",
            "Confirmed          7.811049e+10\n",
            "Recovered          3.256593e+10\n",
            "Deaths             3.977167e+07\n",
            "Active             8.756098e+09\n",
            "Migrated_Other     6.960196e+03\n",
            "Delta_Confirmed    8.018286e+07\n",
            "Delta_Recovered    3.264358e+07\n",
            "Delta_Deaths       1.662654e+04\n",
            "dtype: float64 \n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YLgKhHXrRek_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "outputId": "4053a837-9f1b-4caf-d1be-1187ee7b9bd4"
      },
      "source": [
        "# everything in a nutshell - .describe()\n",
        "df.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Confirmed</th>\n",
              "      <th>Recovered</th>\n",
              "      <th>Deaths</th>\n",
              "      <th>Active</th>\n",
              "      <th>Migrated_Other</th>\n",
              "      <th>Delta_Confirmed</th>\n",
              "      <th>Delta_Recovered</th>\n",
              "      <th>Delta_Deaths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>3.800000e+01</td>\n",
              "      <td>3.800000e+01</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>38.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>8.915153e+04</td>\n",
              "      <td>5.756563e+04</td>\n",
              "      <td>1923.578947</td>\n",
              "      <td>29639.894737</td>\n",
              "      <td>22.421053</td>\n",
              "      <td>2858.473684</td>\n",
              "      <td>1823.894737</td>\n",
              "      <td>40.052632</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.794825e+05</td>\n",
              "      <td>1.804603e+05</td>\n",
              "      <td>6306.478645</td>\n",
              "      <td>93574.026812</td>\n",
              "      <td>83.427791</td>\n",
              "      <td>8954.488353</td>\n",
              "      <td>5713.456107</td>\n",
              "      <td>128.943932</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.536250e+03</td>\n",
              "      <td>8.940000e+02</td>\n",
              "      <td>5.500000</td>\n",
              "      <td>722.250000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>37.750000</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.330350e+04</td>\n",
              "      <td>8.482000e+03</td>\n",
              "      <td>89.000000</td>\n",
              "      <td>5603.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>219.500000</td>\n",
              "      <td>215.500000</td>\n",
              "      <td>3.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>5.882525e+04</td>\n",
              "      <td>4.216925e+04</td>\n",
              "      <td>820.250000</td>\n",
              "      <td>13384.250000</td>\n",
              "      <td>1.750000</td>\n",
              "      <td>1451.750000</td>\n",
              "      <td>881.250000</td>\n",
              "      <td>15.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.693879e+06</td>\n",
              "      <td>1.093747e+06</td>\n",
              "      <td>36548.000000</td>\n",
              "      <td>563158.000000</td>\n",
              "      <td>426.000000</td>\n",
              "      <td>54311.000000</td>\n",
              "      <td>34654.000000</td>\n",
              "      <td>761.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Confirmed     Recovered  ...  Delta_Recovered  Delta_Deaths\n",
              "count  3.800000e+01  3.800000e+01  ...        38.000000     38.000000\n",
              "mean   8.915153e+04  5.756563e+04  ...      1823.894737     40.052632\n",
              "std    2.794825e+05  1.804603e+05  ...      5713.456107    128.943932\n",
              "min    0.000000e+00  0.000000e+00  ...         0.000000      0.000000\n",
              "25%    1.536250e+03  8.940000e+02  ...        13.000000      0.000000\n",
              "50%    1.330350e+04  8.482000e+03  ...       215.500000      3.500000\n",
              "75%    5.882525e+04  4.216925e+04  ...       881.250000     15.500000\n",
              "max    1.693879e+06  1.093747e+06  ...     34654.000000    761.000000\n",
              "\n",
              "[8 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 109
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z7HlcsnQRrdX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "1235e38b-0cda-4a3b-fadb-b43de6829f1a"
      },
      "source": [
        "# finding the statistics using groupby() in dataframe \n",
        "print(f'Mean for all columns w.r.t to the \"Acive\" column \\n\\n')\n",
        "df.groupby(\"Active\").mean()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mean for all columns w.r.t to the \"Acive\" column \n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Confirmed</th>\n",
              "      <th>Recovered</th>\n",
              "      <th>Deaths</th>\n",
              "      <th>Migrated_Other</th>\n",
              "      <th>Delta_Confirmed</th>\n",
              "      <th>Delta_Recovered</th>\n",
              "      <th>Delta_Deaths</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Active</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>160</th>\n",
              "      <td>408</td>\n",
              "      <td>247</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>302</th>\n",
              "      <td>1404</td>\n",
              "      <td>1095</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>328</th>\n",
              "      <td>548</td>\n",
              "      <td>214</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>78</td>\n",
              "      <td>13</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>369</th>\n",
              "      <td>1051</td>\n",
              "      <td>667</td>\n",
              "      <td>15</td>\n",
              "      <td>0</td>\n",
              "      <td>35</td>\n",
              "      <td>20</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>407</th>\n",
              "      <td>639</td>\n",
              "      <td>231</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>29</td>\n",
              "      <td>17</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>412</th>\n",
              "      <td>1149</td>\n",
              "      <td>725</td>\n",
              "      <td>2</td>\n",
              "      <td>10</td>\n",
              "      <td>46</td>\n",
              "      <td>41</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>603</th>\n",
              "      <td>823</td>\n",
              "      <td>215</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>654</th>\n",
              "      <td>1484</td>\n",
              "      <td>827</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>927</th>\n",
              "      <td>2621</td>\n",
              "      <td>1689</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>116</td>\n",
              "      <td>17</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1052</th>\n",
              "      <td>1693</td>\n",
              "      <td>635</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>127</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1075</th>\n",
              "      <td>2564</td>\n",
              "      <td>1459</td>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "      <td>58</td>\n",
              "      <td>72</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1323</th>\n",
              "      <td>3472</td>\n",
              "      <td>2100</td>\n",
              "      <td>49</td>\n",
              "      <td>0</td>\n",
              "      <td>174</td>\n",
              "      <td>142</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1657</th>\n",
              "      <td>5913</td>\n",
              "      <td>4211</td>\n",
              "      <td>45</td>\n",
              "      <td>0</td>\n",
              "      <td>209</td>\n",
              "      <td>206</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1721</th>\n",
              "      <td>4722</td>\n",
              "      <td>2962</td>\n",
              "      <td>21</td>\n",
              "      <td>18</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2803</th>\n",
              "      <td>9086</td>\n",
              "      <td>6230</td>\n",
              "      <td>53</td>\n",
              "      <td>0</td>\n",
              "      <td>230</td>\n",
              "      <td>309</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2897</th>\n",
              "      <td>7183</td>\n",
              "      <td>4168</td>\n",
              "      <td>80</td>\n",
              "      <td>38</td>\n",
              "      <td>118</td>\n",
              "      <td>172</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4999</th>\n",
              "      <td>16119</td>\n",
              "      <td>10734</td>\n",
              "      <td>386</td>\n",
              "      <td>0</td>\n",
              "      <td>663</td>\n",
              "      <td>225</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6208</th>\n",
              "      <td>10488</td>\n",
              "      <td>4176</td>\n",
              "      <td>104</td>\n",
              "      <td>0</td>\n",
              "      <td>89</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6317</th>\n",
              "      <td>34965</td>\n",
              "      <td>28227</td>\n",
              "      <td>421</td>\n",
              "      <td>0</td>\n",
              "      <td>711</td>\n",
              "      <td>887</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7765</th>\n",
              "      <td>20359</td>\n",
              "      <td>12217</td>\n",
              "      <td>377</td>\n",
              "      <td>0</td>\n",
              "      <td>490</td>\n",
              "      <td>375</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8668</th>\n",
              "      <td>31806</td>\n",
              "      <td>22271</td>\n",
              "      <td>867</td>\n",
              "      <td>0</td>\n",
              "      <td>838</td>\n",
              "      <td>614</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9226</th>\n",
              "      <td>38408</td>\n",
              "      <td>29081</td>\n",
              "      <td>98</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10495</th>\n",
              "      <td>23614</td>\n",
              "      <td>13023</td>\n",
              "      <td>74</td>\n",
              "      <td>22</td>\n",
              "      <td>1310</td>\n",
              "      <td>864</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10705</th>\n",
              "      <td>135598</td>\n",
              "      <td>120930</td>\n",
              "      <td>3963</td>\n",
              "      <td>0</td>\n",
              "      <td>1195</td>\n",
              "      <td>1206</td>\n",
              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11145</th>\n",
              "      <td>31877</td>\n",
              "      <td>20518</td>\n",
              "      <td>214</td>\n",
              "      <td>0</td>\n",
              "      <td>1499</td>\n",
              "      <td>772</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11558</th>\n",
              "      <td>42083</td>\n",
              "      <td>29845</td>\n",
              "      <td>680</td>\n",
              "      <td>0</td>\n",
              "      <td>1147</td>\n",
              "      <td>614</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13993</th>\n",
              "      <td>61438</td>\n",
              "      <td>45009</td>\n",
              "      <td>2436</td>\n",
              "      <td>0</td>\n",
              "      <td>1153</td>\n",
              "      <td>833</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16796</th>\n",
              "      <td>62703</td>\n",
              "      <td>45388</td>\n",
              "      <td>519</td>\n",
              "      <td>0</td>\n",
              "      <td>1986</td>\n",
              "      <td>816</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17038</th>\n",
              "      <td>50987</td>\n",
              "      <td>33650</td>\n",
              "      <td>298</td>\n",
              "      <td>1</td>\n",
              "      <td>2986</td>\n",
              "      <td>1977</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20233</th>\n",
              "      <td>70188</td>\n",
              "      <td>48374</td>\n",
              "      <td>1581</td>\n",
              "      <td>0</td>\n",
              "      <td>2496</td>\n",
              "      <td>2118</td>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34968</th>\n",
              "      <td>85461</td>\n",
              "      <td>48863</td>\n",
              "      <td>1630</td>\n",
              "      <td>0</td>\n",
              "      <td>4422</td>\n",
              "      <td>2060</td>\n",
              "      <td>43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57968</th>\n",
              "      <td>245859</td>\n",
              "      <td>183956</td>\n",
              "      <td>3935</td>\n",
              "      <td>0</td>\n",
              "      <td>5881</td>\n",
              "      <td>5778</td>\n",
              "      <td>94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72004</th>\n",
              "      <td>124115</td>\n",
              "      <td>49788</td>\n",
              "      <td>2314</td>\n",
              "      <td>9</td>\n",
              "      <td>5483</td>\n",
              "      <td>3094</td>\n",
              "      <td>84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75720</th>\n",
              "      <td>140933</td>\n",
              "      <td>63864</td>\n",
              "      <td>1349</td>\n",
              "      <td>0</td>\n",
              "      <td>10376</td>\n",
              "      <td>3840</td>\n",
              "      <td>68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>150662</th>\n",
              "      <td>422118</td>\n",
              "      <td>256158</td>\n",
              "      <td>14994</td>\n",
              "      <td>304</td>\n",
              "      <td>10320</td>\n",
              "      <td>7543</td>\n",
              "      <td>265</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>563158</th>\n",
              "      <td>1693879</td>\n",
              "      <td>1093747</td>\n",
              "      <td>36548</td>\n",
              "      <td>426</td>\n",
              "      <td>54311</td>\n",
              "      <td>34654</td>\n",
              "      <td>761</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Confirmed  Recovered  ...  Delta_Recovered  Delta_Deaths\n",
              "Active                        ...                               \n",
              "0               0          0  ...                0             0\n",
              "160           408        247  ...               13             0\n",
              "302          1404       1095  ...                1             0\n",
              "328           548        214  ...               13             2\n",
              "369          1051        667  ...               20             1\n",
              "407           639        231  ...               17             0\n",
              "412          1149        725  ...               41             0\n",
              "603           823        215  ...                5             0\n",
              "654          1484        827  ...                0             0\n",
              "927          2621       1689  ...               17             1\n",
              "1052         1693        635  ...               10             0\n",
              "1075         2564       1459  ...               72             0\n",
              "1323         3472       2100  ...              142             1\n",
              "1657         5913       4211  ...              206             3\n",
              "1721         4722       2962  ...                0             0\n",
              "2803         9086       6230  ...              309             2\n",
              "2897         7183       4168  ...              172             4\n",
              "4999        16119      10734  ...              225            16\n",
              "6208        10488       4176  ...                0             1\n",
              "6317        34965      28227  ...              887             4\n",
              "7765        20359      12217  ...              375            12\n",
              "8668        31806      22271  ...              614            10\n",
              "9226        38408      29081  ...                0             4\n",
              "10495       23614      13023  ...              864             3\n",
              "10705      135598     120930  ...             1206            27\n",
              "11145       31877      20518  ...              772             9\n",
              "11558       42083      29845  ...              614            13\n",
              "13993       61438      45009  ...              833            22\n",
              "16796       62703      45388  ...              816            14\n",
              "17038       50987      33650  ...             1977            13\n",
              "20233       70188      48374  ...             2118            45\n",
              "34968       85461      48863  ...             2060            43\n",
              "57968      245859     183956  ...             5778            94\n",
              "72004      124115      49788  ...             3094            84\n",
              "75720      140933      63864  ...             3840            68\n",
              "150662     422118     256158  ...             7543           265\n",
              "563158    1693879    1093747  ...            34654           761\n",
              "\n",
              "[37 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 115
        }
      ]
    }
  ]
}