hw9_pandas_in_act.ipynb

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              "                        Name    Manufacturer  Type  Calories  Fiber  Sugars\n",
              "0                  100% Bran         Nabisco  Cold        70   10.0       6\n",
              "1          100% Natural Bran     Quaker Oats  Cold       120    2.0       8\n",
              "2                   All-Bran       Kellogg's  Cold        70    9.0       5\n",
              "3  All-Bran with Extra Fiber       Kellogg's  Cold        50   14.0       0\n",
              "4             Almond Delight  Ralston Purina  Cold       110    1.0       8"
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            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ],
      "source": [
        "import pandas as pd\n",
        "cer = pd.read_csv(\"cereals.csv\")\n",
        "cer.head()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Сгруппируйте завтраки по значениям в столбце Manufacturer (Произво- дитель)\n",
        "manf = cer.groupby(\"Manufacturer\")\n",
        "manf"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EegrTU35zeb9",
        "outputId": "2a260ef6-ce97-4e69-c343-0a601dbc2d8a"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x7aba50961e40>"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 2 Определите общее количество групп и завтраков в каждой группе\n",
        "len(manf)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x10WpXsvz9cL",
        "outputId": "fc765a76-b037-4ba6-a11c-aebc7465f165"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "7"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Извлеките список завтраков, выпускаемых производителем Nabisco\n",
        "manf.get_group('Nabisco')"
      ],
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          "height": 238
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      "execution_count": 4,
      "outputs": [
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          "data": {
            "text/plain": [
              "                         Name Manufacturer  Type  Calories  Fiber  Sugars\n",
              "0                   100% Bran      Nabisco  Cold        70   10.0       6\n",
              "20     Cream of Wheat (Quick)      Nabisco   Hot       100    1.0       0\n",
              "63             Shredded Wheat      Nabisco  Cold        80    3.0       0\n",
              "64     Shredded Wheat 'n'Bran      Nabisco  Cold        90    4.0       0\n",
              "65  Shredded Wheat spoon size      Nabisco  Cold        90    3.0       0\n",
              "68    Strawberry Fruit Wheats      Nabisco  Cold        90    3.0       5"
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              "                                                     [key], {});\n",
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              "\n",
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              "            + ' to learn more about interactive tables.';\n",
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            ]
          },
          "metadata": {},
          "execution_count": 4
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Вычислите средние значения по столбцам Calories, Fiber и Sugars для каж- дого производителя\n",
        "manf[\"Calories\",\"Fiber\",\"Sugars\"].mean()"
      ],
      "metadata": {
        "id": "dhTZuVF00b3I",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "outputId": "cc331300-c183-4581-c91e-a8684692612a"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-5-ed4bff1c72ec>:2: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "  manf[\"Calories\",\"Fiber\",\"Sugars\"].mean()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                               Calories     Fiber    Sugars\n",
              "Manufacturer                                               \n",
              "American Home Food Products  100.000000  0.000000  3.000000\n",
              "General Mills                111.363636  1.272727  7.954545\n",
              "Kellogg's                    108.695652  2.739130  7.565217\n",
              "Nabisco                       86.666667  4.000000  1.833333\n",
              "Post                         108.888889  2.777778  8.777778\n",
              "Quaker Oats                   95.000000  1.337500  5.250000\n",
              "Ralston Purina               115.000000  1.875000  6.125000"
            ],
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              "      <td>111.363636</td>\n",
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              "\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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              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Найдите максимальное значение в столбце Sugars для каждого произво- дителя\n",
        "manf['Sugars'].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XEi39VSc11Wy",
        "outputId": "9e2a4cdb-b94c-4a6e-e2f1-4bca8850101c"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Manufacturer\n",
              "American Home Food Products     3\n",
              "General Mills                  14\n",
              "Kellogg's                      15\n",
              "Nabisco                         6\n",
              "Post                           15\n",
              "Quaker Oats                    12\n",
              "Ralston Purina                 11\n",
              "Name: Sugars, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Найдите минимальное значение в столбце Fiber для каждого производителя\n",
        "manf['Fiber'].min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kptxjfZK2AhO",
        "outputId": "0c356f69-eceb-408a-90ef-af92fdc79b73"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Manufacturer\n",
              "American Home Food Products    0.0\n",
              "General Mills                  0.0\n",
              "Kellogg's                      0.0\n",
              "Nabisco                        1.0\n",
              "Post                           0.0\n",
              "Quaker Oats                    0.0\n",
              "Ralston Purina                 0.0\n",
              "Name: Fiber, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Найдите завтраки с наименьшим количеством сахара (столбец Sugars)\n",
        "# по производителям и верните их в виде нового DataFrame\n",
        "\n",
        "def small_sugar(ddf):\n",
        "  return ddf.nsmallest(1, 'Sugars')\n",
        "\n",
        "manf.apply(small_sugar)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "jLCX4FCs2J4F",
        "outputId": "24ddce5e-c861-4730-f5b0-48a932aaac05"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                     Name  \\\n",
              "Manufacturer                                                \n",
              "American Home Food Products 43                      Maypo   \n",
              "General Mills               11                   Cheerios   \n",
              "Kellogg's                   3   All-Bran with Extra Fiber   \n",
              "Nabisco                     20     Cream of Wheat (Quick)   \n",
              "Post                        33                 Grape-Nuts   \n",
              "Quaker Oats                 57             Quaker Oatmeal   \n",
              "Ralston Purina              61                  Rice Chex   \n",
              "\n",
              "                                               Manufacturer  Type  Calories  \\\n",
              "Manufacturer                                                                  \n",
              "American Home Food Products 43  American Home Food Products   Hot       100   \n",
              "General Mills               11                General Mills  Cold       110   \n",
              "Kellogg's                   3                     Kellogg's  Cold        50   \n",
              "Nabisco                     20                      Nabisco   Hot       100   \n",
              "Post                        33                         Post  Cold       110   \n",
              "Quaker Oats                 57                  Quaker Oats   Hot       100   \n",
              "Ralston Purina              61               Ralston Purina  Cold       110   \n",
              "\n",
              "                                Fiber  Sugars  \n",
              "Manufacturer                                   \n",
              "American Home Food Products 43    0.0       3  \n",
              "General Mills               11    2.0       1  \n",
              "Kellogg's                   3    14.0       0  \n",
              "Nabisco                     20    1.0       0  \n",
              "Post                        33    3.0       3  \n",
              "Quaker Oats                 57    2.7      -1  \n",
              "Ralston Purina              61    0.0       2  "
            ],
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              "      <td>Nabisco</td>\n",
              "      <td>Hot</td>\n",
              "      <td>100</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Post</th>\n",
              "      <th>33</th>\n",
              "      <td>Grape-Nuts</td>\n",
              "      <td>Post</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Quaker Oats</th>\n",
              "      <th>57</th>\n",
              "      <td>Quaker Oatmeal</td>\n",
              "      <td>Quaker Oats</td>\n",
              "      <td>Hot</td>\n",
              "      <td>100</td>\n",
              "      <td>2.7</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ralston Purina</th>\n",
              "      <th>61</th>\n",
              "      <td>Rice Chex</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d2422dc6-a43e-45da-b6e7-fb3fdfa5282a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <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",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-52537ec5-8b9a-4fa5-9af6-61315a316dab\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-52537ec5-8b9a-4fa5-9af6-61315a316dab')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart: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-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart: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",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-52537ec5-8b9a-4fa5-9af6-61315a316dab button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\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",
              "      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-d2422dc6-a43e-45da-b6e7-fb3fdfa5282a 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-d2422dc6-a43e-45da-b6e7-fb3fdfa5282a');\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"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    }
  ]
}