work_3101.ipynb

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        "<a href=\"https://colab.research.google.com/github/coder-omer/Pandas/blob/main/work_3101.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "code",
      "source": [
        "import pandas as pd"
      ],
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        "id": "5Tl6EQ2uAMcf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "orders = pd.read_table('chipotle.tsv')"
      ],
      "metadata": {
        "id": "VTXYEjwCAMY0"
      },
      "execution_count": null,
      "outputs": []
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      "cell_type": "code",
      "source": [
        "orders.info()"
      ],
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 4622 entries, 0 to 4621\n",
            "Data columns (total 5 columns):\n",
            " #   Column              Non-Null Count  Dtype \n",
            "---  ------              --------------  ----- \n",
            " 0   order_id            4622 non-null   int64 \n",
            " 1   quantity            4622 non-null   int64 \n",
            " 2   item_name           4622 non-null   object\n",
            " 3   choice_description  3376 non-null   object\n",
            " 4   item_price          4622 non-null   object\n",
            "dtypes: int64(2), object(3)\n",
            "memory usage: 180.7+ KB\n"
          ]
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      ]
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    {
      "cell_type": "code",
      "source": [
        "orders.head()"
      ],
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              "      <th></th>\n",
              "      <th>order_id</th>\n",
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              "      <td>Chips and Fresh Tomato Salsa</td>\n",
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              "      <td>$2.39</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Izze</td>\n",
              "      <td>[Clementine]</td>\n",
              "      <td>$3.39</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Nantucket Nectar</td>\n",
              "      <td>[Apple]</td>\n",
              "      <td>$3.39</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Chips and Tomatillo-Green Chili Salsa</td>\n",
              "      <td>NaN</td>\n",
              "      <td>$2.39</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>Chicken Bowl</td>\n",
              "      <td>[Tomatillo-Red Chili Salsa (Hot), [Black Beans...</td>\n",
              "      <td>$16.98</td>\n",
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              "   order_id  ...  item_price\n",
              "0         1  ...      $2.39 \n",
              "1         1  ...      $3.39 \n",
              "2         1  ...      $3.39 \n",
              "3         1  ...      $2.39 \n",
              "4         2  ...     $16.98 \n",
              "\n",
              "[5 rows x 5 columns]"
            ]
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      "source": [
        "orders.item_name.str.upper()"
      ],
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          "data": {
            "text/plain": [
              "0                CHIPS AND FRESH TOMATO SALSA\n",
              "1                                        IZZE\n",
              "2                            NANTUCKET NECTAR\n",
              "3       CHIPS AND TOMATILLO-GREEN CHILI SALSA\n",
              "4                                CHICKEN BOWL\n",
              "                        ...                  \n",
              "4617                            STEAK BURRITO\n",
              "4618                            STEAK BURRITO\n",
              "4619                       CHICKEN SALAD BOWL\n",
              "4620                       CHICKEN SALAD BOWL\n",
              "4621                       CHICKEN SALAD BOWL\n",
              "Name: item_name, Length: 4622, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
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      "cell_type": "code",
      "source": [
        "orders.item_name.str.contains('Chicken')"
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          "data": {
            "text/plain": [
              "0       False\n",
              "1       False\n",
              "2       False\n",
              "3       False\n",
              "4        True\n",
              "        ...  \n",
              "4617    False\n",
              "4618    False\n",
              "4619     True\n",
              "4620     True\n",
              "4621     True\n",
              "Name: item_name, Length: 4622, dtype: bool"
            ]
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          "metadata": {},
          "execution_count": 10
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    {
      "cell_type": "code",
      "source": [
        "orders[orders.item_name.str.contains('Chicken')]"
      ],
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              "\n",
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              "      <td>2</td>\n",
              "      <td>Chicken Bowl</td>\n",
              "      <td>[Tomatillo-Red Chili Salsa (Hot), [Black Beans...</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Chicken Bowl</td>\n",
              "      <td>[Fresh Tomato Salsa (Mild), [Rice, Cheese, Sou...</td>\n",
              "      <td>$10.98</td>\n",
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              "      <th>11</th>\n",
              "      <td>6</td>\n",
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              "      <td>Chicken Crispy Tacos</td>\n",
              "      <td>[Roasted Chili Corn Salsa, [Fajita Vegetables,...</td>\n",
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              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>Chicken Soft Tacos</td>\n",
              "      <td>[Roasted Chili Corn Salsa, [Rice, Black Beans,...</td>\n",
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              "      <th>13</th>\n",
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              "      <td>$11.25</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "      <th>4604</th>\n",
              "      <td>1828</td>\n",
              "      <td>1</td>\n",
              "      <td>Chicken Bowl</td>\n",
              "      <td>[Fresh Tomato Salsa, [Rice, Black Beans, Chees...</td>\n",
              "      <td>$8.75</td>\n",
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              "    <tr>\n",
              "      <th>4615</th>\n",
              "      <td>1832</td>\n",
              "      <td>1</td>\n",
              "      <td>Chicken Soft Tacos</td>\n",
              "      <td>[Fresh Tomato Salsa, [Rice, Cheese, Sour Cream]]</td>\n",
              "      <td>$8.75</td>\n",
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              "      <th>4619</th>\n",
              "      <td>1834</td>\n",
              "      <td>1</td>\n",
              "      <td>Chicken Salad Bowl</td>\n",
              "      <td>[Fresh Tomato Salsa, [Fajita Vegetables, Pinto...</td>\n",
              "      <td>$11.25</td>\n",
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              "    <tr>\n",
              "      <th>4620</th>\n",
              "      <td>1834</td>\n",
              "      <td>1</td>\n",
              "      <td>Chicken Salad Bowl</td>\n",
              "      <td>[Fresh Tomato Salsa, [Fajita Vegetables, Lettu...</td>\n",
              "      <td>$8.75</td>\n",
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              "    <tr>\n",
              "      <th>4621</th>\n",
              "      <td>1834</td>\n",
              "      <td>1</td>\n",
              "      <td>Chicken Salad Bowl</td>\n",
              "      <td>[Fresh Tomato Salsa, [Fajita Vegetables, Pinto...</td>\n",
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              "<p>1560 rows × 5 columns</p>\n",
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              "                                                     [key], {});\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            "text/plain": [
              "      order_id  ...  item_price\n",
              "4            2  ...     $16.98 \n",
              "5            3  ...     $10.98 \n",
              "11           6  ...      $8.75 \n",
              "12           6  ...      $8.75 \n",
              "13           7  ...     $11.25 \n",
              "...        ...  ...         ...\n",
              "4604      1828  ...      $8.75 \n",
              "4615      1832  ...      $8.75 \n",
              "4619      1834  ...     $11.25 \n",
              "4620      1834  ...      $8.75 \n",
              "4621      1834  ...      $8.75 \n",
              "\n",
              "[1560 rows x 5 columns]"
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          "metadata": {},
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      "cell_type": "code",
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        "orders.head()"
      ],
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        "outputId": "55a39548-0e41-4f2a-eee8-1331e6c1a928"
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      "execution_count": null,
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        {
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              "\n",
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              "      <th></th>\n",
              "      <th>order_id</th>\n",
              "      <th>quantity</th>\n",
              "      <th>item_name</th>\n",
              "      <th>choice_description</th>\n",
              "      <th>item_price</th>\n",
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              "      <td>Nantucket Nectar</td>\n",
              "      <td>[Apple]</td>\n",
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              "      <td>Chicken Bowl</td>\n",
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              "  "
            ],
            "text/plain": [
              "   order_id  ...  item_price\n",
              "0         1  ...      $2.39 \n",
              "1         1  ...      $3.39 \n",
              "2         1  ...      $3.39 \n",
              "3         1  ...      $2.39 \n",
              "4         2  ...     $16.98 \n",
              "\n",
              "[5 rows x 5 columns]"
            ]
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          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "orders.choice_description.str.replace('[','').str.replace(']','')\n",
        "# orders.choice_description.str.replace('[\\[\\]]','') aynısını yapar"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "21N5zbu6AMFN",
        "outputId": "5da70d4b-6775-4ffa-c223-39f6bcdc14c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0                                                     NaN\n",
              "1                                              Clementine\n",
              "2                                                   Apple\n",
              "3                                                     NaN\n",
              "4       Tomatillo-Red Chili Salsa (Hot), Black Beans, ...\n",
              "                              ...                        \n",
              "4617    Fresh Tomato Salsa, Rice, Black Beans, Sour Cr...\n",
              "4618    Fresh Tomato Salsa, Rice, Sour Cream, Cheese, ...\n",
              "4619    Fresh Tomato Salsa, Fajita Vegetables, Pinto B...\n",
              "4620       Fresh Tomato Salsa, Fajita Vegetables, Lettuce\n",
              "4621    Fresh Tomato Salsa, Fajita Vegetables, Pinto B...\n",
              "Name: choice_description, Length: 4622, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "drinks = pd.read_csv('http://bit.ly/drinksbycountry')"
      ],
      "metadata": {
        "id": "wlmCPdg_AMB6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "drinks.head()"
      ],
      "metadata": {
        "colab": {
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        "id": "XNzQTaEYAL-i",
        "outputId": "7af51182-0960-41e3-f1c1-406b1129bbf6"
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      "execution_count": null,
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        {
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              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "          const element = document.querySelector('#df-3fc5bbf5-9aeb-4524-b480-206e46df68cd');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            ],
            "text/plain": [
              "       country  beer_servings  ...  total_litres_of_pure_alcohol  continent\n",
              "0  Afghanistan              0  ...                           0.0       Asia\n",
              "1      Albania             89  ...                           4.9     Europe\n",
              "2      Algeria             25  ...                           0.7     Africa\n",
              "3      Andorra            245  ...                          12.4     Europe\n",
              "4       Angola            217  ...                           5.9     Africa\n",
              "\n",
              "[5 rows x 6 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "drinks.beer_servings.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yXUo04wabmxI",
        "outputId": "2a58069e-708d-46f5-bcb3-9b295af2241a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "106.16062176165804"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "drinks.groupby('continent').beer_servings.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7rgC8pUzbmtd",
        "outputId": "d360914c-47cc-4984-82f9-03d423d4fd34"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "continent\n",
              "Africa            61.471698\n",
              "Asia              37.045455\n",
              "Europe           193.777778\n",
              "North America    145.434783\n",
              "Oceania           89.687500\n",
              "South America    175.083333\n",
              "Name: beer_servings, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "drinks[drinks.continent=='Africa']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Bq1UXGjqbmqA",
        "outputId": "777b3d11-f917-459c-ed05-c349398273b4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "\n",
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              "      <th>2</th>\n",
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              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Benin</td>\n",
              "      <td>34</td>\n",
              "      <td>4</td>\n",
              "      <td>13</td>\n",
              "      <td>1.1</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Botswana</td>\n",
              "      <td>173</td>\n",
              "      <td>35</td>\n",
              "      <td>35</td>\n",
              "      <td>5.4</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Burkina Faso</td>\n",
              "      <td>25</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>4.3</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>Burundi</td>\n",
              "      <td>88</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>6.3</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Cote d'Ivoire</td>\n",
              "      <td>37</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Cabo Verde</td>\n",
              "      <td>144</td>\n",
              "      <td>56</td>\n",
              "      <td>16</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>Cameroon</td>\n",
              "      <td>147</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>5.8</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Central African Republic</td>\n",
              "      <td>17</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1.8</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Chad</td>\n",
              "      <td>15</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.4</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>Comoros</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Congo</td>\n",
              "      <td>76</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>1.7</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>DR Congo</td>\n",
              "      <td>32</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>2.3</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>Djibouti</td>\n",
              "      <td>15</td>\n",
              "      <td>44</td>\n",
              "      <td>3</td>\n",
              "      <td>1.1</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>Egypt</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>Equatorial Guinea</td>\n",
              "      <td>92</td>\n",
              "      <td>0</td>\n",
              "      <td>233</td>\n",
              "      <td>5.8</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>Eritrea</td>\n",
              "      <td>18</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>Ethiopia</td>\n",
              "      <td>20</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.7</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>Gabon</td>\n",
              "      <td>347</td>\n",
              "      <td>98</td>\n",
              "      <td>59</td>\n",
              "      <td>8.9</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>Gambia</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2.4</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>66</th>\n",
              "      <td>Ghana</td>\n",
              "      <td>31</td>\n",
              "      <td>3</td>\n",
              "      <td>10</td>\n",
              "      <td>1.8</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70</th>\n",
              "      <td>Guinea</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>71</th>\n",
              "      <td>Guinea-Bissau</td>\n",
              "      <td>28</td>\n",
              "      <td>31</td>\n",
              "      <td>21</td>\n",
              "      <td>2.5</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>Kenya</td>\n",
              "      <td>58</td>\n",
              "      <td>22</td>\n",
              "      <td>2</td>\n",
              "      <td>1.8</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>Lesotho</td>\n",
              "      <td>82</td>\n",
              "      <td>29</td>\n",
              "      <td>0</td>\n",
              "      <td>2.8</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>Liberia</td>\n",
              "      <td>19</td>\n",
              "      <td>152</td>\n",
              "      <td>2</td>\n",
              "      <td>3.1</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>Libya</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>100</th>\n",
              "      <td>Madagascar</td>\n",
              "      <td>26</td>\n",
              "      <td>15</td>\n",
              "      <td>4</td>\n",
              "      <td>0.8</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101</th>\n",
              "      <td>Malawi</td>\n",
              "      <td>8</td>\n",
              "      <td>11</td>\n",
              "      <td>1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>104</th>\n",
              "      <td>Mali</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.6</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>Mauritania</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>Mauritius</td>\n",
              "      <td>98</td>\n",
              "      <td>31</td>\n",
              "      <td>18</td>\n",
              "      <td>2.6</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>Morocco</td>\n",
              "      <td>12</td>\n",
              "      <td>6</td>\n",
              "      <td>10</td>\n",
              "      <td>0.5</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>115</th>\n",
              "      <td>Mozambique</td>\n",
              "      <td>47</td>\n",
              "      <td>18</td>\n",
              "      <td>5</td>\n",
              "      <td>1.3</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>Namibia</td>\n",
              "      <td>376</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>6.8</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>Niger</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>124</th>\n",
              "      <td>Nigeria</td>\n",
              "      <td>42</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>9.1</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142</th>\n",
              "      <td>Rwanda</td>\n",
              "      <td>43</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>6.8</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>Sao Tome &amp; Principe</td>\n",
              "      <td>56</td>\n",
              "      <td>38</td>\n",
              "      <td>140</td>\n",
              "      <td>4.2</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>150</th>\n",
              "      <td>Senegal</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>0.3</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>152</th>\n",
              "      <td>Seychelles</td>\n",
              "      <td>157</td>\n",
              "      <td>25</td>\n",
              "      <td>51</td>\n",
              "      <td>4.1</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>153</th>\n",
              "      <td>Sierra Leone</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>6.7</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>158</th>\n",
              "      <td>Somalia</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>159</th>\n",
              "      <td>South Africa</td>\n",
              "      <td>225</td>\n",
              "      <td>76</td>\n",
              "      <td>81</td>\n",
              "      <td>8.2</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>Sudan</td>\n",
              "      <td>8</td>\n",
              "      <td>13</td>\n",
              "      <td>0</td>\n",
              "      <td>1.7</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>164</th>\n",
              "      <td>Swaziland</td>\n",
              "      <td>90</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4.7</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>172</th>\n",
              "      <td>Togo</td>\n",
              "      <td>36</td>\n",
              "      <td>2</td>\n",
              "      <td>19</td>\n",
              "      <td>1.3</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>175</th>\n",
              "      <td>Tunisia</td>\n",
              "      <td>51</td>\n",
              "      <td>3</td>\n",
              "      <td>20</td>\n",
              "      <td>1.3</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>179</th>\n",
              "      <td>Uganda</td>\n",
              "      <td>45</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "      <td>8.3</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183</th>\n",
              "      <td>Tanzania</td>\n",
              "      <td>36</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>5.7</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>191</th>\n",
              "      <td>Zambia</td>\n",
              "      <td>32</td>\n",
              "      <td>19</td>\n",
              "      <td>4</td>\n",
              "      <td>2.5</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>192</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>64</td>\n",
              "      <td>18</td>\n",
              "      <td>4</td>\n",
              "      <td>4.7</td>\n",
              "      <td>Africa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-86213cbf-c3a6-4804-8c0d-5a340fc08ded')\"\n",
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              "    .colab-df-convert {\n",
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            ],
            "text/plain": [
              "                      country  ...  continent\n",
              "2                     Algeria  ...     Africa\n",
              "4                      Angola  ...     Africa\n",
              "18                      Benin  ...     Africa\n",
              "22                   Botswana  ...     Africa\n",
              "26               Burkina Faso  ...     Africa\n",
              "27                    Burundi  ...     Africa\n",
              "28              Cote d'Ivoire  ...     Africa\n",
              "29                 Cabo Verde  ...     Africa\n",
              "31                   Cameroon  ...     Africa\n",
              "33   Central African Republic  ...     Africa\n",
              "34                       Chad  ...     Africa\n",
              "38                    Comoros  ...     Africa\n",
              "39                      Congo  ...     Africa\n",
              "47                   DR Congo  ...     Africa\n",
              "49                   Djibouti  ...     Africa\n",
              "53                      Egypt  ...     Africa\n",
              "55          Equatorial Guinea  ...     Africa\n",
              "56                    Eritrea  ...     Africa\n",
              "58                   Ethiopia  ...     Africa\n",
              "62                      Gabon  ...     Africa\n",
              "63                     Gambia  ...     Africa\n",
              "66                      Ghana  ...     Africa\n",
              "70                     Guinea  ...     Africa\n",
              "71              Guinea-Bissau  ...     Africa\n",
              "88                      Kenya  ...     Africa\n",
              "95                    Lesotho  ...     Africa\n",
              "96                    Liberia  ...     Africa\n",
              "97                      Libya  ...     Africa\n",
              "100                Madagascar  ...     Africa\n",
              "101                    Malawi  ...     Africa\n",
              "104                      Mali  ...     Africa\n",
              "107                Mauritania  ...     Africa\n",
              "108                 Mauritius  ...     Africa\n",
              "114                   Morocco  ...     Africa\n",
              "115                Mozambique  ...     Africa\n",
              "117                   Namibia  ...     Africa\n",
              "123                     Niger  ...     Africa\n",
              "124                   Nigeria  ...     Africa\n",
              "142                    Rwanda  ...     Africa\n",
              "148       Sao Tome & Principe  ...     Africa\n",
              "150                   Senegal  ...     Africa\n",
              "152                Seychelles  ...     Africa\n",
              "153              Sierra Leone  ...     Africa\n",
              "158                   Somalia  ...     Africa\n",
              "159              South Africa  ...     Africa\n",
              "162                     Sudan  ...     Africa\n",
              "164                 Swaziland  ...     Africa\n",
              "172                      Togo  ...     Africa\n",
              "175                   Tunisia  ...     Africa\n",
              "179                    Uganda  ...     Africa\n",
              "183                  Tanzania  ...     Africa\n",
              "191                    Zambia  ...     Africa\n",
              "192                  Zimbabwe  ...     Africa\n",
              "\n",
              "[53 rows x 6 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
      "metadata": {
        "id": "s6biULd9QF8g"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "rng = np.random.RandomState(0)"
      ],
      "metadata": {
        "id": "6VCZ7bOhP-YY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({'key':['A','B','C','A','B','C'],\n",
        "                   'data1': range(6),\n",
        "                   'data2': rng.randint(0,10,6)},\n",
        "                   columns = ['key','data1','data2'])"
      ],
      "metadata": {
        "id": "-UAtE-pQbmm5"
      },
      "execution_count": null,
      "outputs": []
    },
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        "df"
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              "                                                     [key], {});\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  key  data1  data2\n",
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              "                                                     [key], {});\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "   data1  data2\n",
              "0   -1.5    1.0\n",
              "1   -1.5   -3.5\n",
              "2   -1.5   -3.0\n",
              "3    1.5   -1.0\n",
              "4    1.5    3.5\n",
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              "\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e046f556-56ef-4b87-a761-3bd87cbe5b86 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e046f556-56ef-4b87-a761-3bd87cbe5b86');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  key  data1  data2\n",
              "0   A      0      5\n",
              "1   B      1      0\n",
              "2   C      2      3\n",
              "3   A      3      3\n",
              "4   B      4      7\n",
              "5   C      5      9"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def norm_by_data2(x):\n",
        "  x['data1'] /= x['data2'].sum()\n",
        "  return x"
      ],
      "metadata": {
        "id": "YbNxkbJmRqjJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby('key').apply(norm_by_data2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "EiJ4HfBERqfY",
        "outputId": "4a570a81-8e11-4466-ab35-d91ef8fb2edf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "</style>\n",
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              "      <th></th>\n",
              "      <th>key</th>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>C</td>\n",
              "      <td>0.166667</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A</td>\n",
              "      <td>0.375000</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
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              "      <td>0.571429</td>\n",
              "      <td>7</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>C</td>\n",
              "      <td>0.416667</td>\n",
              "      <td>9</td>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-96afa796-02fe-4383-a5e4-8f17bfbbbd20 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-96afa796-02fe-4383-a5e4-8f17bfbbbd20');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  key     data1  data2\n",
              "0   A  0.000000      5\n",
              "1   B  0.142857      0\n",
              "2   C  0.166667      3\n",
              "3   A  0.375000      3\n",
              "4   B  0.571429      7\n",
              "5   C  0.416667      9"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "from IPython.display import display"
      ],
      "metadata": {
        "id": "xPwUBQgRTtbz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.core.display import display"
      ],
      "metadata": {
        "id": "jZptTV61UneL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "display('df',\"df.groupby('key').apply(norm_by_data2)\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "HetGkDn6RqbN",
        "outputId": "4017e3d2-d706-4aca-de02-569c2d5878d7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'df'"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "\"df.groupby('key').apply(norm_by_data2)\""
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "display(df, df.groupby('key').apply(norm_by_data2))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "9PDXjc0_RqXq",
        "outputId": "630248ea-8ffd-41eb-97dc-a9a818c8b648"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-81f605a1-7245-4314-9901-e8aa1d59e754\">\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
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              "\n",
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              "          const element = document.querySelector('#df-81f605a1-7245-4314-9901-e8aa1d59e754');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "        }\n",
              "      </script>\n",
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              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  key  data1  data2\n",
              "0   A      0      5\n",
              "1   B      1      0\n",
              "2   C      2      3\n",
              "3   A      3      3\n",
              "4   B      4      7\n",
              "5   C      5      9"
            ]
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              "\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
              "    }\n",
              "\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-d45d33d9-d59d-4ee8-809c-39ab797d3a0d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d45d33d9-d59d-4ee8-809c-39ab797d3a0d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  key     data1  data2\n",
              "0   A  0.000000      5\n",
              "1   B  0.142857      0\n",
              "2   C  0.166667      3\n",
              "3   A  0.375000      3\n",
              "4   B  0.571429      7\n",
              "5   C  0.416667      9"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "L =[0, 1, 0, 1, 2, 0]"
      ],
      "metadata": {
        "id": "NeRO0kOYRqUz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "display('df',\"df.groupby(L).sum()\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "AVozhAWsRqRe",
        "outputId": "c96bf088-a052-494a-c825-a57b0dd44a36"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'df'"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'df.groupby(L).sum()'"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = pd.DataFrame([('bird', 389.0),\n",
        "                     ('bird', 40.0), ('bird', 405.0),\n",
        "                     ('mammal', 80.2),\n",
        "                     ('mammal', 12.0),('mammal', 58)],\n",
        "                     index=['falcon', 'parrot', 'eagle', 'lion', 'monkey', 'leopard'],\n",
        "                    columns=('class', 'speed'))\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "EbgaiIMzRqOp",
        "outputId": "f8984f02-26ed-44d3-f7eb-fee7f425853e"
      },
      "execution_count": null,
      "outputs": [
        {
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          "data": {
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              "      <th>falcon</th>\n",
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              "      <th>leopard</th>\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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            "text/plain": [
              "          class  speed\n",
              "falcon     bird  389.0\n",
              "parrot     bird   40.0\n",
              "eagle      bird  405.0\n",
              "lion     mammal   80.2\n",
              "monkey   mammal   12.0\n",
              "leopard  mammal   58.0"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
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        "data.groupby(\"class\").max()"
      ],
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          "height": 143
        },
        "id": "4aJQ4kxXdTsN",
        "outputId": "605a59e4-594d-4e20-e957-9f210d5fb70b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "    <tr>\n",
              "      <th>mammal</th>\n",
              "      <td>80.2</td>\n",
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              "          const element = document.querySelector('#df-e458b2f7-cee6-4105-b190-4e872e055a0c');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        speed\n",
              "class        \n",
              "bird    405.0\n",
              "mammal   80.2"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.groupby(\"class\").mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "2xZfpIWie8bI",
        "outputId": "6a37d267-6660-4a62-edb5-d468e218c30f"
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      "execution_count": null,
      "outputs": [
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              "      <td>50.066667</td>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "             speed\n",
              "class             \n",
              "bird    278.000000\n",
              "mammal   50.066667"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.loc[data.groupby([\"class\"])[\"speed\"].idxmax()]"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "wQlRevTefCBN",
        "outputId": "e387834d-45fd-4743-a616-b6833b7ed7fe"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            "text/plain": [
              "        class  speed\n",
              "eagle    bird  405.0\n",
              "lion   mammal   80.2"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.sort_values('speed').groupby(['class']).tail(1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "igJ2bxUjfB-s",
        "outputId": "827f7bfb-246c-4403-bf25-8ea18fe4b679"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-12c7c71b-f261-467a-87e4-81223a326dac button.colab-df-convert');\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-12c7c71b-f261-467a-87e4-81223a326dac');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        class  speed\n",
              "lion   mammal   80.2\n",
              "eagle    bird  405.0"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.groupby(['class'])['speed'].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3fXrNylqfB7E",
        "outputId": "3d74920e-e10c-481c-cd91-f679826d403f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "class\n",
              "bird      405.0\n",
              "mammal     80.2\n",
              "Name: speed, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "igDje48efB4A"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "jzj0-UVFfB08"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}