Multi_indexlash_(pivot_table)_2.ipynb

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        "<a href=\"https://colab.research.google.com/github/AbdullahTheAnalyst/Data-Science-and-AI-mohir_dev-/blob/NumPy-and-Pandas/Multi_indexlash_(pivot_table)_2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Multi indexlash\n",
        "\n",
        "Hierarchial indexing\n",
        "\n",
        "Bir nechta indexdan tashkil topgan"
      ],
      "metadata": {
        "id": "lHT467UhjVP0"
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      "source": [
        "# bu Multi indexlash bizga juda katta database ga ishlov berish uchun kerak bo'ladi\n",
        "# Odatiy Series to'plam\n",
        "data = pd.Series(np.random.randn(9), index = [\"a\",\n",
        "                                              \"a\",\n",
        "                                              \"a\",\n",
        "                                              \"b\",\n",
        "                                              \"b\",\n",
        "                                              \"c\",\n",
        "                                              \"c\",\n",
        "                                              \"d\",\n",
        "                                              \"d\",\n",
        "                                              ])\n",
        "data"
      ],
      "metadata": {
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        "id": "G7YtvqWai_zJ",
        "outputId": "1064d112-4486-4e00-e140-bce10813d61f"
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              "a   -1.438600\n",
              "a    0.273812\n",
              "a   -0.550314\n",
              "b   -1.985547\n",
              "b    1.367370\n",
              "c   -0.108385\n",
              "c   -0.711387\n",
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      "source": [
        "data.index"
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          "base_uri": "https://localhost:8080/"
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        "id": "8c6qsTOdkTwg",
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              "Index(['a', 'a', 'a', 'b', 'b', 'c', 'c', 'd', 'd'], dtype='object')"
            ]
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          "metadata": {},
          "execution_count": 3
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      "source": [
        "# buni multi - indexga alishtiramiz\n",
        "# yuqori masshtabli db uchun guruhlashga juda yordam beradi\n",
        "data1 = pd.Series(np.random.randn(9), index = [[\"a\", \"a\", \"a\", \"b\", \"b\", \"c\", \"c\", \"d\", \"d\"],\n",
        "                                              [1, 2, 3, 1, 3, 1, 2, 2, 3]])\n",
        "data1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 366
        },
        "id": "pzziVROrkgmt",
        "outputId": "3888d752-d5d0-41f7-b3e4-f807137106d9"
      },
      "execution_count": 4,
      "outputs": [
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          "output_type": "execute_result",
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              "a  1   -1.259966\n",
              "   2   -0.040916\n",
              "   3    0.725736\n",
              "b  1    0.685902\n",
              "   3   -0.056911\n",
              "c  1    0.472592\n",
              "   2    0.433679\n",
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    {
      "cell_type": "code",
      "source": [
        "data1.index"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
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        "id": "zNEOq-YblQOW",
        "outputId": "042df330-7761-4bab-be30-a42311bbd097"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MultiIndex([('a', 1),\n",
              "            ('a', 2),\n",
              "            ('a', 3),\n",
              "            ('b', 1),\n",
              "            ('b', 3),\n",
              "            ('c', 1),\n",
              "            ('c', 2),\n",
              "            ('d', 2),\n",
              "            ('d', 3)],\n",
              "           )"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# faqat c indexiga tegishli datani ajratib olamiz\n",
        "data1[\"c\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 146
        },
        "id": "T1QCNaNflj_u",
        "outputId": "9db1fcf7-b3aa-4bf8-84b6-af523292eb52"
      },
      "execution_count": 6,
      "outputs": [
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          "output_type": "execute_result",
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          "metadata": {},
          "execution_count": 6
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ko'p indexini ajratib olish\n",
        "data1[\"c\" : \"d\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 209
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      "outputs": [
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          "output_type": "execute_result",
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              "c  1    0.472592\n",
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              "      <td>0.433679</td>\n",
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              "      <th rowspan=\"2\" valign=\"top\">d</th>\n",
              "      <th>2</th>\n",
              "      <td>0.902761</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-1.716570</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> float64</label>"
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          },
          "metadata": {},
          "execution_count": 7
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      ]
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      "cell_type": "code",
      "source": [
        "data1[\"a\" : \"c\"]"
      ],
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          "base_uri": "https://localhost:8080/",
          "height": 303
        },
        "id": "RAKMMinRmUh0",
        "outputId": "9253c8fd-e119-4152-ae50-b3c548bc4cda"
      },
      "execution_count": 8,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "a  1   -1.259966\n",
              "   2   -0.040916\n",
              "   3    0.725736\n",
              "b  1    0.685902\n",
              "   3   -0.056911\n",
              "c  1    0.472592\n",
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              "      <td>0.725736</td>\n",
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              "      <th rowspan=\"2\" valign=\"top\">b</th>\n",
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              "      <th>3</th>\n",
              "      <td>-0.056911</td>\n",
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              "      <th rowspan=\"2\" valign=\"top\">c</th>\n",
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          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# barcha 3-indexga tegishli elementlarni ajratib olish\n",
        "data1.loc[ : , 3]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 178
        },
        "id": "4SYhPnq9mXUi",
        "outputId": "8b07a2a7-14cb-4cfa-a1e0-e162bf9ef709"
      },
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      "outputs": [
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              "a    0.725736\n",
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              "      <th>a</th>\n",
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          "metadata": {},
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      ]
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    {
      "cell_type": "code",
      "source": [
        "# barcha b va c indexdagi elementlar\n",
        "data1.loc[[\"b\", \"c\"]]"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 209
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      "outputs": [
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              "b  1    0.685902\n",
              "   3   -0.056911\n",
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      "cell_type": "code",
      "source": [
        "# unstack va stack usullari juda foydali hisoblanadi\n",
        "# unstack -> bu multi-indexdan dataframega sochib yuboradi\n",
        "# unstack -> sochilgan Seriesni df ko'rinishiga qaytaradi\n",
        "data1.unstack()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "id": "nJnpM44TmyAI",
        "outputId": "f7e73579-e1bb-4824-8175-29b959f2e605"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          1         2         3\n",
              "a -1.259966 -0.040916  0.725736\n",
              "b  0.685902       NaN -0.056911\n",
              "c  0.472592  0.433679       NaN\n",
              "d       NaN  0.902761 -1.716570"
            ],
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              "      <th>3</th>\n",
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              "    <tr>\n",
              "      <th>a</th>\n",
              "      <td>-1.259966</td>\n",
              "      <td>-0.040916</td>\n",
              "      <td>0.725736</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>b</th>\n",
              "      <td>0.685902</td>\n",
              "      <td>NaN</td>\n",
              "      <td>-0.056911</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>c</th>\n",
              "      <td>0.472592</td>\n",
              "      <td>0.433679</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>d</th>\n",
              "      <td>NaN</td>\n",
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              "      <td>-1.716570</td>\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d4b27ff0-a819-4494-a8f7-b263e918a496 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-d4b27ff0-a819-4494-a8f7-b263e918a496');\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",
              "\n",
              "\n",
              "<div id=\"df-3edfb910-ca73-4722-a1c4-7f8082b52397\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3edfb910-ca73-4722-a1c4-7f8082b52397')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-3edfb910-ca73-4722-a1c4-7f8082b52397 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"data1\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": 1,\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.067213136129029,\n        \"min\": -1.259966255329591,\n        \"max\": 0.6859020370128622,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          -1.259966255329591,\n          0.6859020370128622,\n          0.4725921897034281\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": 2,\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4718409546721975,\n        \"min\": -0.040915922725712796,\n        \"max\": 0.9027606177238928,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          -0.040915922725712796,\n          0.43367911584445623,\n          0.9027606177238928\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": 3,\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.247120818257897,\n        \"min\": -1.7165695908876073,\n        \"max\": 0.725736420452668,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.725736420452668,\n          -0.056911150558893044,\n          -1.7165695908876073\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# stack -> df.ni yig'ilgan Series.ga o'giradi\n",
        "data1.unstack().stack()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 366
        },
        "id": "WySAM8eEnVLS",
        "outputId": "062428b2-c9a2-4f58-ab0b-ba9e9e598435"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "a  1   -1.259966\n",
              "   2   -0.040916\n",
              "   3    0.725736\n",
              "b  1    0.685902\n",
              "   3   -0.056911\n",
              "c  1    0.472592\n",
              "   2    0.433679\n",
              "d  2    0.902761\n",
              "   3   -1.716570\n",
              "dtype: float64"
            ],
            "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></th>\n",
              "      <th>0</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">a</th>\n",
              "      <th>1</th>\n",
              "      <td>-1.259966</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-0.040916</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.725736</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">b</th>\n",
              "      <th>1</th>\n",
              "      <td>0.685902</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.056911</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">c</th>\n",
              "      <th>1</th>\n",
              "      <td>0.472592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.433679</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">d</th>\n",
              "      <th>2</th>\n",
              "      <td>0.902761</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-1.716570</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> float64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dunyo shaharlarining havo va suv sifati to'g'risida dataset"
      ],
      "metadata": {
        "id": "FRt3vjjDocfT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# git hubdan repository.ni yuklab olish\n",
        "! git clone https://github.com/MansurCompAI/Practicum_Datasets.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PBzq06Gfn-8l",
        "outputId": "a24164a3-0bab-46f0-8279-f6d531fbd134"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'Practicum_Datasets'...\n",
            "remote: Enumerating objects: 60, done.\u001b[K\n",
            "remote: Counting objects: 100% (60/60), done.\u001b[K\n",
            "remote: Compressing objects: 100% (55/55), done.\u001b[K\n",
            "remote: Total 60 (delta 17), reused 16 (delta 1), pack-reused 0 (from 0)\u001b[K\n",
            "Receiving objects: 100% (60/60), 20.24 MiB | 6.02 MiB/s, done.\n",
            "Resolving deltas: 100% (17/17), done.\n",
            "Updating files: 100% (13/13), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"/content/Practicum_Datasets/world_cities_air_water_quality.csv\")\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "cf9bzqsVo0zg",
        "outputId": "87177985-f9a6-4dd2-fe95-afdecb84948d"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               City                 \"Region\"                    \"Country\"  \\\n",
              "0     New York City               \"New York\"   \"United States of America\"   \n",
              "1  Washington, D.C.   \"District of Columbia\"   \"United States of America\"   \n",
              "2     San Francisco             \"California\"   \"United States of America\"   \n",
              "3            Berlin                       \"\"                    \"Germany\"   \n",
              "4       Los Angeles             \"California\"   \"United States of America\"   \n",
              "\n",
              "    \"AirQuality\"   \"WaterPollution\"  \n",
              "0      46.816038          49.504950  \n",
              "1      66.129032          49.107143  \n",
              "2      60.514019          43.000000  \n",
              "3      62.364130          28.612717  \n",
              "4      36.621622          61.299435  "
            ],
            "text/html": [
              "\n",
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              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    .dataframe thead th {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>City</th>\n",
              "      <th>\"Region\"</th>\n",
              "      <th>\"Country\"</th>\n",
              "      <th>\"AirQuality\"</th>\n",
              "      <th>\"WaterPollution\"</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>New York City</td>\n",
              "      <td>\"New York\"</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>46.816038</td>\n",
              "      <td>49.504950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Washington, D.C.</td>\n",
              "      <td>\"District of Columbia\"</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>66.129032</td>\n",
              "      <td>49.107143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>San Francisco</td>\n",
              "      <td>\"California\"</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>60.514019</td>\n",
              "      <td>43.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Berlin</td>\n",
              "      <td>\"\"</td>\n",
              "      <td>\"Germany\"</td>\n",
              "      <td>62.364130</td>\n",
              "      <td>28.612717</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>\"California\"</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>36.621622</td>\n",
              "      <td>61.299435</td>\n",
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              "\n",
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              "          + ' to learn more about interactive tables.';\n",
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              "\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3963,\n  \"fields\": [\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3796,\n        \"samples\": [\n          \"Voronezh\",\n          \"Bloomfield Hills\",\n          \"Opole\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \" \\\"Region\\\"\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1153,\n        \"samples\": [\n          \" \\\"Limassol District\\\"\",\n          \" \\\"Ilocos Region\\\"\",\n          \" \\\"Hainan\\\"\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \" \\\"Country\\\"\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 177,\n        \"samples\": [\n          \" \\\"Portugal\\\"\",\n          \" \\\"Ireland\\\"\",\n          \" \\\"Timor-Leste\\\"\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \" \\\"AirQuality\\\"\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.94475340269786,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 667,\n        \"samples\": [\n          43.333333333333336,\n          34.375,\n          78.33333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \" \\\"WaterPollution\\\"\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.663910130274456,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 561,\n        \"samples\": [\n          79.04411764705883,\n          51.19047619047619,\n          4.999999999999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# har doim data cleaning.dan oldin albatta data haqida ma'lumotlari haqida info ol\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5fUPto_apLTJ",
        "outputId": "a12a1e01-a7fc-4a93-adaa-33e7d25f31e3"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 3963 entries, 0 to 3962\n",
            "Data columns (total 5 columns):\n",
            " #   Column             Non-Null Count  Dtype  \n",
            "---  ------             --------------  -----  \n",
            " 0   City               3963 non-null   object \n",
            " 1    \"Region\"          3963 non-null   object \n",
            " 2    \"Country\"         3963 non-null   object \n",
            " 3    \"AirQuality\"      3963 non-null   float64\n",
            " 4    \"WaterPollution\"  3963 non-null   float64\n",
            "dtypes: float64(2), object(3)\n",
            "memory usage: 154.9+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ishni column name.ni to'g'irlashdan boshlaymiz (\"\" ichida yozilgan xatosi)\n",
        "index_col = [\"City\", \"Region\", \"Country\", \"AirQuality\", \"WaterPollution\"]\n",
        "df.columns = index_col\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "i16QFJRqqCTz",
        "outputId": "876caa38-a242-42a6-b028-e4ac63f7d5aa"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  City                   Region                      Country  \\\n",
              "0        New York City               \"New York\"   \"United States of America\"   \n",
              "1     Washington, D.C.   \"District of Columbia\"   \"United States of America\"   \n",
              "2        San Francisco             \"California\"   \"United States of America\"   \n",
              "3               Berlin                       \"\"                    \"Germany\"   \n",
              "4          Los Angeles             \"California\"   \"United States of America\"   \n",
              "...                ...                      ...                          ...   \n",
              "3958             Yanbu        \"Medina Province\"               \"Saudi Arabia\"   \n",
              "3959           Cordoba              \"Andalusia\"                      \"Spain\"   \n",
              "3960               Vic              \"Catalonia\"                      \"Spain\"   \n",
              "3961           Segovia       \"Castile and Leon\"                      \"Spain\"   \n",
              "3962       Zamora city       \"Castile and Leon\"                      \"Spain\"   \n",
              "\n",
              "      AirQuality  WaterPollution  \n",
              "0      46.816038       49.504950  \n",
              "1      66.129032       49.107143  \n",
              "2      60.514019       43.000000  \n",
              "3      62.364130       28.612717  \n",
              "4      36.621622       61.299435  \n",
              "...          ...             ...  \n",
              "3958    0.000000       50.000000  \n",
              "3959   85.714286        8.333333  \n",
              "3960  100.000000        0.000000  \n",
              "3961  100.000000        0.000000  \n",
              "3962  100.000000       50.000000  \n",
              "\n",
              "[3963 rows x 5 columns]"
            ],
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>City</th>\n",
              "      <th>Region</th>\n",
              "      <th>Country</th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>WaterPollution</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>New York City</td>\n",
              "      <td>\"New York\"</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>46.816038</td>\n",
              "      <td>49.504950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Washington, D.C.</td>\n",
              "      <td>\"District of Columbia\"</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>66.129032</td>\n",
              "      <td>49.107143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>San Francisco</td>\n",
              "      <td>\"California\"</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>60.514019</td>\n",
              "      <td>43.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Berlin</td>\n",
              "      <td>\"\"</td>\n",
              "      <td>\"Germany\"</td>\n",
              "      <td>62.364130</td>\n",
              "      <td>28.612717</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>\"California\"</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>36.621622</td>\n",
              "      <td>61.299435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3958</th>\n",
              "      <td>Yanbu</td>\n",
              "      <td>\"Medina Province\"</td>\n",
              "      <td>\"Saudi Arabia\"</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3959</th>\n",
              "      <td>Cordoba</td>\n",
              "      <td>\"Andalusia\"</td>\n",
              "      <td>\"Spain\"</td>\n",
              "      <td>85.714286</td>\n",
              "      <td>8.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3960</th>\n",
              "      <td>Vic</td>\n",
              "      <td>\"Catalonia\"</td>\n",
              "      <td>\"Spain\"</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3961</th>\n",
              "      <td>Segovia</td>\n",
              "      <td>\"Castile and Leon\"</td>\n",
              "      <td>\"Spain\"</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3962</th>\n",
              "      <td>Zamora city</td>\n",
              "      <td>\"Castile and Leon\"</td>\n",
              "      <td>\"Spain\"</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3963 rows × 5 columns</p>\n",
              "</div>\n",
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              "\n",
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              "        document.querySelector('#df-c04ff55c-df99-48e1-a704-92b7c9457cd0 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-c04ff55c-df99-48e1-a704-92b7c9457cd0');\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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              "\n",
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              "\n",
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              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
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              "    60% {\n",
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              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-ec3513f5-50eb-4e5e-942e-576961314ddc button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_fe663e0f-ba75-4df8-8bc3-8691b837140b\">\n",
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              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
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              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
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              "        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",
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              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
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              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3963,\n  \"fields\": [\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3796,\n        \"samples\": [\n          \"Voronezh\",\n          \"Bloomfield Hills\",\n          \"Opole\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Region\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1153,\n        \"samples\": [\n          \" \\\"Limassol District\\\"\",\n          \" \\\"Ilocos Region\\\"\",\n          \" \\\"Hainan\\\"\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Country\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 177,\n        \"samples\": [\n          \" \\\"Portugal\\\"\",\n          \" \\\"Ireland\\\"\",\n          \" \\\"Timor-Leste\\\"\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.94475340269786,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 667,\n        \"samples\": [\n          43.333333333333336,\n          34.375,\n          78.33333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.663910130274456,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 561,\n        \"samples\": [\n          79.04411764705883,\n          51.19047619047619,\n          4.999999999999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Region va Country ichida hamma element \"\" ichida yozilgan va buni to'g'irlashimiz kerak\n",
        "# .map(lambda x: x.replace('\"', '')) -> \" ning o'rnida bo'sh qoldirish uchun dastur\n",
        "df[\"Region\"] = df[\"Region\"].map(lambda x: x.replace('\"', ''))\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "aXeWOC5Qqc1u",
        "outputId": "70621cd8-ab31-4464-cdf6-016991584a4d"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  City                 Region                      Country  \\\n",
              "0        New York City               New York   \"United States of America\"   \n",
              "1     Washington, D.C.   District of Columbia   \"United States of America\"   \n",
              "2        San Francisco             California   \"United States of America\"   \n",
              "3               Berlin                                           \"Germany\"   \n",
              "4          Los Angeles             California   \"United States of America\"   \n",
              "...                ...                    ...                          ...   \n",
              "3958             Yanbu        Medina Province               \"Saudi Arabia\"   \n",
              "3959           Cordoba              Andalusia                      \"Spain\"   \n",
              "3960               Vic              Catalonia                      \"Spain\"   \n",
              "3961           Segovia       Castile and Leon                      \"Spain\"   \n",
              "3962       Zamora city       Castile and Leon                      \"Spain\"   \n",
              "\n",
              "      AirQuality  WaterPollution  \n",
              "0      46.816038       49.504950  \n",
              "1      66.129032       49.107143  \n",
              "2      60.514019       43.000000  \n",
              "3      62.364130       28.612717  \n",
              "4      36.621622       61.299435  \n",
              "...          ...             ...  \n",
              "3958    0.000000       50.000000  \n",
              "3959   85.714286        8.333333  \n",
              "3960  100.000000        0.000000  \n",
              "3961  100.000000        0.000000  \n",
              "3962  100.000000       50.000000  \n",
              "\n",
              "[3963 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-eeac7ca2-2761-44f2-83d8-3e11a8bb4aba\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>City</th>\n",
              "      <th>Region</th>\n",
              "      <th>Country</th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>WaterPollution</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>New York City</td>\n",
              "      <td>New York</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>46.816038</td>\n",
              "      <td>49.504950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Washington, D.C.</td>\n",
              "      <td>District of Columbia</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>66.129032</td>\n",
              "      <td>49.107143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>San Francisco</td>\n",
              "      <td>California</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>60.514019</td>\n",
              "      <td>43.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Berlin</td>\n",
              "      <td></td>\n",
              "      <td>\"Germany\"</td>\n",
              "      <td>62.364130</td>\n",
              "      <td>28.612717</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>California</td>\n",
              "      <td>\"United States of America\"</td>\n",
              "      <td>36.621622</td>\n",
              "      <td>61.299435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3958</th>\n",
              "      <td>Yanbu</td>\n",
              "      <td>Medina Province</td>\n",
              "      <td>\"Saudi Arabia\"</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3959</th>\n",
              "      <td>Cordoba</td>\n",
              "      <td>Andalusia</td>\n",
              "      <td>\"Spain\"</td>\n",
              "      <td>85.714286</td>\n",
              "      <td>8.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3960</th>\n",
              "      <td>Vic</td>\n",
              "      <td>Catalonia</td>\n",
              "      <td>\"Spain\"</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3961</th>\n",
              "      <td>Segovia</td>\n",
              "      <td>Castile and Leon</td>\n",
              "      <td>\"Spain\"</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3962</th>\n",
              "      <td>Zamora city</td>\n",
              "      <td>Castile and Leon</td>\n",
              "      <td>\"Spain\"</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3963 rows × 5 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "            style=\"display:none;\">\n",
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              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "      fill: #D2E3FC;\n",
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              "    [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",
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              "\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-eeac7ca2-2761-44f2-83d8-3e11a8bb4aba 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-eeac7ca2-2761-44f2-83d8-3e11a8bb4aba');\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",
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              "\n",
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              "\n",
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              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-55757ec7-2ca9-4283-a815-5fbc240696be button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_2564369c-34fb-4822-bb0b-5dd22507b4ac\">\n",
              "    <style>\n",
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              "      [theme=dark] .colab-df-generate {\n",
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              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
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              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3963,\n  \"fields\": [\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3796,\n        \"samples\": [\n          \"Voronezh\",\n          \"Bloomfield Hills\",\n          \"Opole\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Region\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1153,\n        \"samples\": [\n          \" Limassol District\",\n          \" Ilocos Region\",\n          \" Hainan\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Country\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 177,\n        \"samples\": [\n          \" \\\"Portugal\\\"\",\n          \" \\\"Ireland\\\"\",\n          \" \\\"Timor-Leste\\\"\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.94475340269786,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 667,\n        \"samples\": [\n          43.333333333333336,\n          34.375,\n          78.33333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.663910130274456,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 561,\n        \"samples\": [\n          79.04411764705883,\n          51.19047619047619,\n          4.999999999999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Region va Country ichida hamma element \"\" ichida yozilgan va buni to'g'irlashimiz kerak\n",
        "# .map(lambda x: x.replace('\"', '')) -> \" ning o'rnida bo'sh qoldirish uchun dastur\n",
        "df[\"Country\"] = df[\"Country\"].map(lambda x: x.replace('\"', ''))\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "eV10UPCAr4Go",
        "outputId": "9cbc5eee-fb34-4b03-b292-90bb33bef337"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  City                 Region                    Country  \\\n",
              "0        New York City               New York   United States of America   \n",
              "1     Washington, D.C.   District of Columbia   United States of America   \n",
              "2        San Francisco             California   United States of America   \n",
              "3               Berlin                                           Germany   \n",
              "4          Los Angeles             California   United States of America   \n",
              "...                ...                    ...                        ...   \n",
              "3958             Yanbu        Medina Province               Saudi Arabia   \n",
              "3959           Cordoba              Andalusia                      Spain   \n",
              "3960               Vic              Catalonia                      Spain   \n",
              "3961           Segovia       Castile and Leon                      Spain   \n",
              "3962       Zamora city       Castile and Leon                      Spain   \n",
              "\n",
              "      AirQuality  WaterPollution  \n",
              "0      46.816038       49.504950  \n",
              "1      66.129032       49.107143  \n",
              "2      60.514019       43.000000  \n",
              "3      62.364130       28.612717  \n",
              "4      36.621622       61.299435  \n",
              "...          ...             ...  \n",
              "3958    0.000000       50.000000  \n",
              "3959   85.714286        8.333333  \n",
              "3960  100.000000        0.000000  \n",
              "3961  100.000000        0.000000  \n",
              "3962  100.000000       50.000000  \n",
              "\n",
              "[3963 rows x 5 columns]"
            ],
            "text/html": [
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>City</th>\n",
              "      <th>Region</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>New York City</td>\n",
              "      <td>New York</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>46.816038</td>\n",
              "      <td>49.504950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Washington, D.C.</td>\n",
              "      <td>District of Columbia</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>66.129032</td>\n",
              "      <td>49.107143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>San Francisco</td>\n",
              "      <td>California</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>60.514019</td>\n",
              "      <td>43.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Berlin</td>\n",
              "      <td></td>\n",
              "      <td>Germany</td>\n",
              "      <td>62.364130</td>\n",
              "      <td>28.612717</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>California</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>36.621622</td>\n",
              "      <td>61.299435</td>\n",
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              "    <tr>\n",
              "      <th>3958</th>\n",
              "      <td>Yanbu</td>\n",
              "      <td>Medina Province</td>\n",
              "      <td>Saudi Arabia</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3959</th>\n",
              "      <td>Cordoba</td>\n",
              "      <td>Andalusia</td>\n",
              "      <td>Spain</td>\n",
              "      <td>85.714286</td>\n",
              "      <td>8.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3960</th>\n",
              "      <td>Vic</td>\n",
              "      <td>Catalonia</td>\n",
              "      <td>Spain</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3961</th>\n",
              "      <td>Segovia</td>\n",
              "      <td>Castile and Leon</td>\n",
              "      <td>Spain</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3962</th>\n",
              "      <td>Zamora city</td>\n",
              "      <td>Castile and Leon</td>\n",
              "      <td>Spain</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3963 rows × 5 columns</p>\n",
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              "\n",
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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",
              "          + ' 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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              "\n",
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              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3963,\n  \"fields\": [\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3796,\n        \"samples\": [\n          \"Voronezh\",\n          \"Bloomfield Hills\",\n          \"Opole\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Region\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1153,\n        \"samples\": [\n          \" Limassol District\",\n          \" Ilocos Region\",\n          \" Hainan\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Country\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 177,\n        \"samples\": [\n          \" Portugal\",\n          \" Ireland\",\n          \" Timor-Leste\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.94475340269786,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 667,\n        \"samples\": [\n          43.333333333333336,\n          34.375,\n          78.33333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.663910130274456,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 561,\n        \"samples\": [\n          79.04411764705883,\n          51.19047619047619,\n          4.999999999999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# yuqorida update qilingan data.ni yangi csv file.ga save qilish kerak\n",
        "# index = False ->boshqa index paydo bo'lishini oldini oladi\n",
        "df.to_csv(\"Updated_dataset\", index = False)"
      ],
      "metadata": {
        "id": "f_oEfvLgr7nc"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# bui bajarsak, Germany oldida space mavjudligini ko'rishimiz mumkin\n",
        "df[df[\"Country\"] == \"Germany\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "id": "5FAhvnY1x8AT",
        "outputId": "7f66f740-d174-431b-c818-b880cac35b26"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [City, Region, Country, AirQuality, WaterPollution]\n",
              "Index: []"
            ],
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              "\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-9b4460c6-1bcc-495c-9aa3-650a7e9b75db 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-9b4460c6-1bcc-495c-9aa3-650a7e9b75db');\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",
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              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "repr_error": "Out of range float values are not JSON compliant: nan"
            }
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Country\"][100]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "BPBXUHmhyh9T",
        "outputId": "1e5dc652-64e5-4ded-89b1-ae5fb64394cc"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "' India'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Country\"] = df[\"Country\"].map(lambda x: x.strip())\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "QgFcqlMQytFz",
        "outputId": "086b1089-18c3-4583-ec4c-3c48fc82c91d"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  City                 Region                   Country  \\\n",
              "0        New York City               New York  United States of America   \n",
              "1     Washington, D.C.   District of Columbia  United States of America   \n",
              "2        San Francisco             California  United States of America   \n",
              "3               Berlin                                          Germany   \n",
              "4          Los Angeles             California  United States of America   \n",
              "...                ...                    ...                       ...   \n",
              "3958             Yanbu        Medina Province              Saudi Arabia   \n",
              "3959           Cordoba              Andalusia                     Spain   \n",
              "3960               Vic              Catalonia                     Spain   \n",
              "3961           Segovia       Castile and Leon                     Spain   \n",
              "3962       Zamora city       Castile and Leon                     Spain   \n",
              "\n",
              "      AirQuality  WaterPollution  \n",
              "0      46.816038       49.504950  \n",
              "1      66.129032       49.107143  \n",
              "2      60.514019       43.000000  \n",
              "3      62.364130       28.612717  \n",
              "4      36.621622       61.299435  \n",
              "...          ...             ...  \n",
              "3958    0.000000       50.000000  \n",
              "3959   85.714286        8.333333  \n",
              "3960  100.000000        0.000000  \n",
              "3961  100.000000        0.000000  \n",
              "3962  100.000000       50.000000  \n",
              "\n",
              "[3963 rows x 5 columns]"
            ],
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              "\n",
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              "      <th>0</th>\n",
              "      <td>New York City</td>\n",
              "      <td>New York</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>46.816038</td>\n",
              "      <td>49.504950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Washington, D.C.</td>\n",
              "      <td>District of Columbia</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>66.129032</td>\n",
              "      <td>49.107143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>San Francisco</td>\n",
              "      <td>California</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>60.514019</td>\n",
              "      <td>43.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Berlin</td>\n",
              "      <td></td>\n",
              "      <td>Germany</td>\n",
              "      <td>62.364130</td>\n",
              "      <td>28.612717</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>California</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>36.621622</td>\n",
              "      <td>61.299435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>3958</th>\n",
              "      <td>Yanbu</td>\n",
              "      <td>Medina Province</td>\n",
              "      <td>Saudi Arabia</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>50.000000</td>\n",
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              "    <tr>\n",
              "      <th>3959</th>\n",
              "      <td>Cordoba</td>\n",
              "      <td>Andalusia</td>\n",
              "      <td>Spain</td>\n",
              "      <td>85.714286</td>\n",
              "      <td>8.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3960</th>\n",
              "      <td>Vic</td>\n",
              "      <td>Catalonia</td>\n",
              "      <td>Spain</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3961</th>\n",
              "      <td>Segovia</td>\n",
              "      <td>Castile and Leon</td>\n",
              "      <td>Spain</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3962</th>\n",
              "      <td>Zamora city</td>\n",
              "      <td>Castile and Leon</td>\n",
              "      <td>Spain</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3963 rows × 5 columns</p>\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0312dbd1-6e44-45dd-b425-39dd76269257 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_ee126668-1cae-4c6b-9ce3-0e3060e1e5e3\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
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              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
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              "\n",
              "      [theme=dark] .colab-df-generate {\n",
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              "        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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3963,\n  \"fields\": [\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3796,\n        \"samples\": [\n          \"Voronezh\",\n          \"Bloomfield Hills\",\n          \"Opole\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Region\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1153,\n        \"samples\": [\n          \" Limassol District\",\n          \" Ilocos Region\",\n          \" Hainan\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Country\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 177,\n        \"samples\": [\n          \"Portugal\",\n          \"Ireland\",\n          \"Timor-Leste\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.94475340269786,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 667,\n        \"samples\": [\n          43.333333333333336,\n          34.375,\n          78.33333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.663910130274456,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 561,\n        \"samples\": [\n          79.04411764705883,\n          51.19047619047619,\n          4.999999999999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Country\"][100]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "eRMSh5yeyySE",
        "outputId": "0788f47c-0469-48ee-bf4c-40b14e023253"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'India'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# germany.ga tegishli data.lar chiqardik\n",
        "df[df[\"Country\"] == \"Germany\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "bDffMhJUy0x4",
        "outputId": "34b82c54-da83-4285-d264-b9d344dea0f0"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        City                   Region  Country  AirQuality  \\\n",
              "3                     Berlin                           Germany   62.364130   \n",
              "28                   Cologne   North Rhine-Westphalia  Germany   60.714286   \n",
              "40                      Bonn   North Rhine-Westphalia  Germany   82.812500   \n",
              "52                 Heilbronn        Baden-Wurttemberg  Germany   80.000000   \n",
              "76                    Aachen   North Rhine-Westphalia  Germany   70.454545   \n",
              "...                      ...                      ...      ...         ...   \n",
              "2693             Bad Waldsee        Baden-Wurttemberg  Germany  100.000000   \n",
              "2714  Weilheim in Oberbayern                  Bavaria  Germany  100.000000   \n",
              "2727                  Buckow              Brandenburg  Germany   87.500000   \n",
              "3942                  Erfurt                Thuringia  Germany   85.000000   \n",
              "3943  Garmisch-Partenkirchen                  Bavaria  Germany  100.000000   \n",
              "\n",
              "      WaterPollution  \n",
              "3          28.612717  \n",
              "28         27.777778  \n",
              "40         22.500000  \n",
              "52          0.000000  \n",
              "76         17.857143  \n",
              "...              ...  \n",
              "2693       50.000000  \n",
              "2714       50.000000  \n",
              "2727       50.000000  \n",
              "3942       50.000000  \n",
              "3943       50.000000  \n",
              "\n",
              "[124 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-73a45533-4f8b-4a4f-848e-0351220ac5f4\" class=\"colab-df-container\">\n",
              "    <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",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>City</th>\n",
              "      <th>Region</th>\n",
              "      <th>Country</th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>WaterPollution</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Berlin</td>\n",
              "      <td></td>\n",
              "      <td>Germany</td>\n",
              "      <td>62.364130</td>\n",
              "      <td>28.612717</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Cologne</td>\n",
              "      <td>North Rhine-Westphalia</td>\n",
              "      <td>Germany</td>\n",
              "      <td>60.714286</td>\n",
              "      <td>27.777778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>Bonn</td>\n",
              "      <td>North Rhine-Westphalia</td>\n",
              "      <td>Germany</td>\n",
              "      <td>82.812500</td>\n",
              "      <td>22.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>Heilbronn</td>\n",
              "      <td>Baden-Wurttemberg</td>\n",
              "      <td>Germany</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>76</th>\n",
              "      <td>Aachen</td>\n",
              "      <td>North Rhine-Westphalia</td>\n",
              "      <td>Germany</td>\n",
              "      <td>70.454545</td>\n",
              "      <td>17.857143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2693</th>\n",
              "      <td>Bad Waldsee</td>\n",
              "      <td>Baden-Wurttemberg</td>\n",
              "      <td>Germany</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2714</th>\n",
              "      <td>Weilheim in Oberbayern</td>\n",
              "      <td>Bavaria</td>\n",
              "      <td>Germany</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2727</th>\n",
              "      <td>Buckow</td>\n",
              "      <td>Brandenburg</td>\n",
              "      <td>Germany</td>\n",
              "      <td>87.500000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3942</th>\n",
              "      <td>Erfurt</td>\n",
              "      <td>Thuringia</td>\n",
              "      <td>Germany</td>\n",
              "      <td>85.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3943</th>\n",
              "      <td>Garmisch-Partenkirchen</td>\n",
              "      <td>Bavaria</td>\n",
              "      <td>Germany</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>124 rows × 5 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-73a45533-4f8b-4a4f-848e-0351220ac5f4')\"\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 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-73a45533-4f8b-4a4f-848e-0351220ac5f4 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-73a45533-4f8b-4a4f-848e-0351220ac5f4');\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",
              "\n",
              "\n",
              "<div id=\"df-941dd356-fd9d-49af-95b2-2b927a6d2286\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-941dd356-fd9d-49af-95b2-2b927a6d2286')\"\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",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-941dd356-fd9d-49af-95b2-2b927a6d2286 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df[df[\\\"Country\\\"] == \\\"Germany\\\"]\",\n  \"rows\": 124,\n  \"fields\": [\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 124,\n        \"samples\": [\n          \"Dresden\",\n          \"Hamm\",\n          \"Freiburg im Breisgau\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Region\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 14,\n        \"samples\": [\n          \" Saarland\",\n          \" Saxony\",\n          \" \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Country\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Germany\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 13.577640475768073,\n        \"min\": 43.125,\n        \"max\": 100.0,\n        \"num_unique_values\": 45,\n        \"samples\": [\n          79.16666666666667\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 21.704279408409523,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 39,\n        \"samples\": [\n          41.66666666666667\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# uzbekistanga.ga tegishli data.lar chiqardik\n",
        "df[df[\"Country\"] == \"Uzbekistan\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "wwcDwzG9y4L2",
        "outputId": "8688e524-5d69-4be9-b136-afdc3fb79644"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        City Region     Country  AirQuality  WaterPollution\n",
              "21  Tashkent         Uzbekistan   56.451613       49.166667"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-95cb1027-bd31-4497-942b-1924a2c625bc\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
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              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>City</th>\n",
              "      <th>Region</th>\n",
              "      <th>Country</th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>WaterPollution</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Tashkent</td>\n",
              "      <td></td>\n",
              "      <td>Uzbekistan</td>\n",
              "      <td>56.451613</td>\n",
              "      <td>49.166667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "            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 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-95cb1027-bd31-4497-942b-1924a2c625bc 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-95cb1027-bd31-4497-942b-1924a2c625bc');\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",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df[df[\\\"Country\\\"] == \\\"Uzbekistan\\\"]\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Tashkent\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Region\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \" \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Country\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Uzbekistan\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 56.4516129032258,\n        \"max\": 56.4516129032258,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          56.4516129032258\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 49.16666666666666,\n        \"max\": 49.16666666666666,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          49.16666666666666\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**pivot_table** orqali multi-indexlash"
      ],
      "metadata": {
        "id": "WaZw1c63zRB0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "Pl94j2VTzORw",
        "outputId": "117c80ca-8f31-4cbe-a516-982e92949015"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               City                 Region                   Country  \\\n",
              "0     New York City               New York  United States of America   \n",
              "1  Washington, D.C.   District of Columbia  United States of America   \n",
              "2     San Francisco             California  United States of America   \n",
              "\n",
              "   AirQuality  WaterPollution  \n",
              "0   46.816038       49.504950  \n",
              "1   66.129032       49.107143  \n",
              "2   60.514019       43.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-76524804-d2c3-4262-b2e2-b13761f7ccd0\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>City</th>\n",
              "      <th>Region</th>\n",
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              "      <th>AirQuality</th>\n",
              "      <th>WaterPollution</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>New York City</td>\n",
              "      <td>New York</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>46.816038</td>\n",
              "      <td>49.504950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Washington, D.C.</td>\n",
              "      <td>District of Columbia</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>66.129032</td>\n",
              "      <td>49.107143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>San Francisco</td>\n",
              "      <td>California</td>\n",
              "      <td>United States of America</td>\n",
              "      <td>60.514019</td>\n",
              "      <td>43.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
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              "            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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-76524804-d2c3-4262-b2e2-b13761f7ccd0 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-76524804-d2c3-4262-b2e2-b13761f7ccd0');\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",
              "\n",
              "\n",
              "<div id=\"df-e1ae4b4e-71ad-4f04-8e6e-3ddf2cfd914c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e1ae4b4e-71ad-4f04-8e6e-3ddf2cfd914c')\"\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",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e1ae4b4e-71ad-4f04-8e6e-3ddf2cfd914c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 3963,\n  \"fields\": [\n    {\n      \"column\": \"City\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3796,\n        \"samples\": [\n          \"Voronezh\",\n          \"Bloomfield Hills\",\n          \"Opole\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Region\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1153,\n        \"samples\": [\n          \" Limassol District\",\n          \" Ilocos Region\",\n          \" Hainan\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Country\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 177,\n        \"samples\": [\n          \"Portugal\",\n          \"Ireland\",\n          \"Timor-Leste\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.94475340269786,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 667,\n        \"samples\": [\n          43.333333333333336,\n          34.375,\n          78.33333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.663910130274456,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 561,\n        \"samples\": [\n          79.04411764705883,\n          51.19047619047619,\n          4.999999999999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# qiymatlati 'AirQuality', 'WaterPollution' bo'lgan pivot table\n",
        "df1 = pd.pivot_table(df, index = [\"Country\", \"City\"], values=['AirQuality', 'WaterPollution'])"
      ],
      "metadata": {
        "id": "w4iKxcsNzZak"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "I2_myPUwz6fW",
        "outputId": "0cc953a3-3624-4937-ef85-9e13db952374"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                      AirQuality  WaterPollution\n",
              "Country     City                                \n",
              "Afghanistan Andkhoy    50.000000       50.000000\n",
              "            Farah     100.000000        0.000000\n",
              "            Herat      43.750000       31.250000\n",
              "            Kabul      18.421053       81.060606\n",
              "            Kandahar    0.000000       75.000000\n",
              "...                          ...             ...\n",
              "Zambia      Mansa      75.000000       25.000000\n",
              "Zimbabwe    Bindura    50.000000       75.000000\n",
              "            Bulawayo   67.857143       71.428571\n",
              "            Harare     38.461538       87.500000\n",
              "            Masvingo   25.000000       62.500000\n",
              "\n",
              "[3895 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-bfc5236c-48d9-4cee-870a-eb0f24f88164\" class=\"colab-df-container\">\n",
              "    <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></th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>WaterPollution</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>City</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
              "      <th>Andkhoy</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Farah</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Herat</th>\n",
              "      <td>43.750000</td>\n",
              "      <td>31.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kabul</th>\n",
              "      <td>18.421053</td>\n",
              "      <td>81.060606</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kandahar</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <th>Mansa</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zimbabwe</th>\n",
              "      <th>Bindura</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bulawayo</th>\n",
              "      <td>67.857143</td>\n",
              "      <td>71.428571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harare</th>\n",
              "      <td>38.461538</td>\n",
              "      <td>87.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Masvingo</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>62.500000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3895 rows × 2 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bfc5236c-48d9-4cee-870a-eb0f24f88164')\"\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 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-bfc5236c-48d9-4cee-870a-eb0f24f88164 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-bfc5236c-48d9-4cee-870a-eb0f24f88164');\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",
              "\n",
              "\n",
              "<div id=\"df-b6bd1ce5-a5aa-44cd-85b0-cb4b1efeaff9\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b6bd1ce5-a5aa-44cd-85b0-cb4b1efeaff9')\"\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",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-b6bd1ce5-a5aa-44cd-85b0-cb4b1efeaff9 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_f8ea0827-dce2-4d83-bc01-c4ff77e5f27f\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df1')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_f8ea0827-dce2-4d83-bc01-c4ff77e5f27f button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df1');\n",
              "      }\n",
              "      })();\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df1",
              "summary": "{\n  \"name\": \"df1\",\n  \"rows\": 3895,\n  \"fields\": [\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.92835970900157,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          12.903225806451612,\n          66.17647058823529,\n          69.44444444444444\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.569554030128938,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          61.53846153846154,\n          54.16666666666666,\n          34.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1.index"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0eT70SEh16O8",
        "outputId": "4a499639-6f17-4580-bf95-3dc56c2aa7bb"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MultiIndex([('Afghanistan',        'Andkhoy'),\n",
              "            ('Afghanistan',          'Farah'),\n",
              "            ('Afghanistan',          'Herat'),\n",
              "            ('Afghanistan',          'Kabul'),\n",
              "            ('Afghanistan',       'Kandahar'),\n",
              "            ('Afghanistan', 'Mazar-i-Sharif'),\n",
              "            (    'Albania',         'Ballsh'),\n",
              "            (    'Albania',         'Burrel'),\n",
              "            (    'Albania',         'Durres'),\n",
              "            (    'Albania',        'Elbasan'),\n",
              "            ...\n",
              "            (      'Yemen',          'Sanaa'),\n",
              "            (      'Yemen',         'Ta'izz'),\n",
              "            (     'Zambia',       'Chingola'),\n",
              "            (     'Zambia',          'Kitwe'),\n",
              "            (     'Zambia',         'Lusaka'),\n",
              "            (     'Zambia',          'Mansa'),\n",
              "            (   'Zimbabwe',        'Bindura'),\n",
              "            (   'Zimbabwe',       'Bulawayo'),\n",
              "            (   'Zimbabwe',         'Harare'),\n",
              "            (   'Zimbabwe',       'Masvingo')],\n",
              "           names=['Country', 'City'], length=3895)"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1.loc[[\"Uzbekistan\", \"Tajikistan\", \"Zambia\"]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "FhE47cTB2L8F",
        "outputId": "7826fc45-78d9-4b0d-e86c-2925b819dceb"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     AirQuality  WaterPollution\n",
              "Country    City                                \n",
              "Uzbekistan Tashkent   56.451613       49.166667\n",
              "Tajikistan Dushanbe   41.666667       61.111111\n",
              "Zambia     Chingola   75.000000      100.000000\n",
              "           Kitwe       0.000000      100.000000\n",
              "           Lusaka     33.333333       98.076923\n",
              "           Mansa      75.000000       25.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-163b58da-695c-4101-9543-177a3a07dfc5\" class=\"colab-df-container\">\n",
              "    <div>\n",
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              "      <th>AirQuality</th>\n",
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              "      <th>Uzbekistan</th>\n",
              "      <th>Tashkent</th>\n",
              "      <td>56.451613</td>\n",
              "      <td>49.166667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tajikistan</th>\n",
              "      <th>Dushanbe</th>\n",
              "      <td>41.666667</td>\n",
              "      <td>61.111111</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zambia</th>\n",
              "      <th>Chingola</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kitwe</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Lusaka</th>\n",
              "      <td>33.333333</td>\n",
              "      <td>98.076923</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mansa</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    }\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",
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              "\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",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-163b58da-695c-4101-9543-177a3a07dfc5 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-163b58da-695c-4101-9543-177a3a07dfc5');\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",
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              "      --bg-color: #E8F0FE;\n",
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              "\n",
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              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
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              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "    90% {\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "      quickchartButtonEl.style.display =\n",
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              "    })();\n",
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              "\n",
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              "type": "dataframe",
              "summary": "{\n  \"name\": \"df1\",\n  \"rows\": 6,\n  \"fields\": [\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 28.570982087752352,\n        \"min\": 0.0,\n        \"max\": 75.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          41.66666666666667,\n          33.333333333333336,\n          75.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 31.926882279476715,\n        \"min\": 25.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          61.11111111111112,\n          25.0,\n          100.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1[\"AirPollution\"] = 100 - df1[\"AirQuality\"]\n",
        "df1[\"WaterQuality\"] = 100 - df1[\"WaterPollution\"]\n",
        "df1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "gTxxbm8j3Hla",
        "outputId": "11483988-7f28-4f43-82e2-e708c3cb8932"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                      AirQuality  WaterPollution  AirPollution  WaterQuality\n",
              "Country     City                                                            \n",
              "Afghanistan Andkhoy    50.000000       50.000000     50.000000     50.000000\n",
              "            Farah     100.000000        0.000000      0.000000    100.000000\n",
              "            Herat      43.750000       31.250000     56.250000     68.750000\n",
              "            Kabul      18.421053       81.060606     81.578947     18.939394\n",
              "            Kandahar    0.000000       75.000000    100.000000     25.000000\n",
              "...                          ...             ...           ...           ...\n",
              "Zambia      Mansa      75.000000       25.000000     25.000000     75.000000\n",
              "Zimbabwe    Bindura    50.000000       75.000000     50.000000     25.000000\n",
              "            Bulawayo   67.857143       71.428571     32.142857     28.571429\n",
              "            Harare     38.461538       87.500000     61.538462     12.500000\n",
              "            Masvingo   25.000000       62.500000     75.000000     37.500000\n",
              "\n",
              "[3895 rows x 4 columns]"
            ],
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>WaterPollution</th>\n",
              "      <th>AirPollution</th>\n",
              "      <th>WaterQuality</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>City</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
              "      <th>Andkhoy</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Farah</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Herat</th>\n",
              "      <td>43.750000</td>\n",
              "      <td>31.250000</td>\n",
              "      <td>56.250000</td>\n",
              "      <td>68.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kabul</th>\n",
              "      <td>18.421053</td>\n",
              "      <td>81.060606</td>\n",
              "      <td>81.578947</td>\n",
              "      <td>18.939394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kandahar</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <th>Mansa</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zimbabwe</th>\n",
              "      <th>Bindura</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bulawayo</th>\n",
              "      <td>67.857143</td>\n",
              "      <td>71.428571</td>\n",
              "      <td>32.142857</td>\n",
              "      <td>28.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harare</th>\n",
              "      <td>38.461538</td>\n",
              "      <td>87.500000</td>\n",
              "      <td>61.538462</td>\n",
              "      <td>12.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Masvingo</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>62.500000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>37.500000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3895 rows × 4 columns</p>\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df1",
              "summary": "{\n  \"name\": \"df1\",\n  \"rows\": 3895,\n  \"fields\": [\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.92835970900157,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          12.903225806451612,\n          66.17647058823529,\n          69.44444444444444\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.569554030128938,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          61.53846153846154,\n          54.16666666666666,\n          34.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AirPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.928359709001448,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          87.09677419354838,\n          33.82352941176471,\n          30.555555555555557\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.56955403012895,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          38.46153846153846,\n          45.83333333333334,\n          65.625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# tepada index.larni rows orqali multi-indexladik\n",
        "# endi esa column.larni multi-indexlab chiqamiz\n",
        "df3 = pd.DataFrame(df1.values, index = df1.index, columns =\n",
        "                   [[\"AIR\", \"AIR\", \"WATER\", \"WATER\",],\n",
        "                    [\"AirQuality\",\t\"AirPollution\",\t\"WaterPollution\",\t\"WaterQuality\"]\n",
        "                    ])\n",
        "df3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 486
        },
        "id": "eJWH2MQf37s0",
        "outputId": "1f976c9c-a4e6-4d55-d2aa-714ad2aed38d"
      },
      "execution_count": 37,
      "outputs": [
        {
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          "data": {
            "text/plain": [
              "                             AIR                       WATER             \n",
              "                      AirQuality AirPollution WaterPollution WaterQuality\n",
              "Country     City                                                         \n",
              "Afghanistan Andkhoy    50.000000    50.000000      50.000000    50.000000\n",
              "            Farah     100.000000     0.000000       0.000000   100.000000\n",
              "            Herat      43.750000    31.250000      56.250000    68.750000\n",
              "            Kabul      18.421053    81.060606      81.578947    18.939394\n",
              "            Kandahar    0.000000    75.000000     100.000000    25.000000\n",
              "...                          ...          ...            ...          ...\n",
              "Zambia      Mansa      75.000000    25.000000      25.000000    75.000000\n",
              "Zimbabwe    Bindura    50.000000    75.000000      50.000000    25.000000\n",
              "            Bulawayo   67.857143    71.428571      32.142857    28.571429\n",
              "            Harare     38.461538    87.500000      61.538462    12.500000\n",
              "            Masvingo   25.000000    62.500000      75.000000    37.500000\n",
              "\n",
              "[3895 rows x 4 columns]"
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              "      <th></th>\n",
              "      <th colspan=\"2\" halign=\"left\">AIR</th>\n",
              "      <th colspan=\"2\" halign=\"left\">WATER</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>AirPollution</th>\n",
              "      <th>WaterPollution</th>\n",
              "      <th>WaterQuality</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>City</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
              "      <th>Andkhoy</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Farah</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Herat</th>\n",
              "      <td>43.750000</td>\n",
              "      <td>31.250000</td>\n",
              "      <td>56.250000</td>\n",
              "      <td>68.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kabul</th>\n",
              "      <td>18.421053</td>\n",
              "      <td>81.060606</td>\n",
              "      <td>81.578947</td>\n",
              "      <td>18.939394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kandahar</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <th>Mansa</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zimbabwe</th>\n",
              "      <th>Bindura</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bulawayo</th>\n",
              "      <td>67.857143</td>\n",
              "      <td>71.428571</td>\n",
              "      <td>32.142857</td>\n",
              "      <td>28.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harare</th>\n",
              "      <td>38.461538</td>\n",
              "      <td>87.500000</td>\n",
              "      <td>61.538462</td>\n",
              "      <td>12.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Masvingo</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>62.500000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>37.500000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "<p>3895 rows × 4 columns</p>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df3",
              "summary": "{\n  \"name\": \"df3\",\n  \"rows\": 3895,\n  \"fields\": [\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.92835970900157,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          12.903225806451612,\n          66.17647058823529,\n          69.44444444444444\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.569554030128938,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          61.53846153846154,\n          54.16666666666666,\n          34.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.928359709001448,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          87.09677419354838,\n          33.82352941176471,\n          30.555555555555557\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.56955403012895,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          38.46153846153846,\n          45.83333333333334,\n          65.625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df3[\"AIR\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "sDOEzp-r91gg",
        "outputId": "374ebe4c-d099-44fe-b352-680aa48af472"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                      AirQuality  AirPollution\n",
              "Country     City                              \n",
              "Afghanistan Andkhoy    50.000000     50.000000\n",
              "            Farah     100.000000      0.000000\n",
              "            Herat      43.750000     31.250000\n",
              "            Kabul      18.421053     81.060606\n",
              "            Kandahar    0.000000     75.000000\n",
              "...                          ...           ...\n",
              "Zambia      Mansa      75.000000     25.000000\n",
              "Zimbabwe    Bindura    50.000000     75.000000\n",
              "            Bulawayo   67.857143     71.428571\n",
              "            Harare     38.461538     87.500000\n",
              "            Masvingo   25.000000     62.500000\n",
              "\n",
              "[3895 rows x 2 columns]"
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>AirPollution</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>City</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
              "      <th>Andkhoy</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Farah</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Herat</th>\n",
              "      <td>43.750000</td>\n",
              "      <td>31.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kabul</th>\n",
              "      <td>18.421053</td>\n",
              "      <td>81.060606</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kandahar</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <th>Mansa</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zimbabwe</th>\n",
              "      <th>Bindura</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bulawayo</th>\n",
              "      <td>67.857143</td>\n",
              "      <td>71.428571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harare</th>\n",
              "      <td>38.461538</td>\n",
              "      <td>87.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Masvingo</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>62.500000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3895 rows × 2 columns</p>\n",
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              "\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-43ccaad5-a802-4208-a1db-622409da4b8d');\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",
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              "          + ' to learn more about interactive tables.';\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
              "\n",
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              "            style=\"display:none;\">\n",
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              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "\n",
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              "\n",
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              "    fill: var(--fill-color);\n",
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              "    width: 32px;\n",
              "  }\n",
              "\n",
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              "    background-color: var(--hover-bg-color);\n",
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              "\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-57088cd4-7786-44a2-ae85-699dbaa5981a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df3[\\\"AIR\\\"]\",\n  \"rows\": 3895,\n  \"fields\": [\n    {\n      \"column\": \"AirQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.92835970900157,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          12.903225806451612,\n          66.17647058823529,\n          69.44444444444444\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AirPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.569554030128938,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          61.53846153846154,\n          54.16666666666666,\n          34.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df3[\"WATER\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "KtB0Yekr_OQA",
        "outputId": "326a7cae-2226-47e6-fe4d-495ba543aa64"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                      WaterPollution  WaterQuality\n",
              "Country     City                                  \n",
              "Afghanistan Andkhoy        50.000000     50.000000\n",
              "            Farah           0.000000    100.000000\n",
              "            Herat          56.250000     68.750000\n",
              "            Kabul          81.578947     18.939394\n",
              "            Kandahar      100.000000     25.000000\n",
              "...                              ...           ...\n",
              "Zambia      Mansa          25.000000     75.000000\n",
              "Zimbabwe    Bindura        50.000000     25.000000\n",
              "            Bulawayo       32.142857     28.571429\n",
              "            Harare         61.538462     12.500000\n",
              "            Masvingo       75.000000     37.500000\n",
              "\n",
              "[3895 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-80cb70a7-c3e9-4576-ae96-a0d628fa44e5\" class=\"colab-df-container\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>WaterPollution</th>\n",
              "      <th>WaterQuality</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>City</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
              "      <th>Andkhoy</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Farah</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Herat</th>\n",
              "      <td>56.250000</td>\n",
              "      <td>68.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kabul</th>\n",
              "      <td>81.578947</td>\n",
              "      <td>18.939394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kandahar</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <th>Mansa</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zimbabwe</th>\n",
              "      <th>Bindura</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bulawayo</th>\n",
              "      <td>32.142857</td>\n",
              "      <td>28.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harare</th>\n",
              "      <td>61.538462</td>\n",
              "      <td>12.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Masvingo</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>37.500000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3895 rows × 2 columns</p>\n",
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              "\n",
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              "        const element = document.querySelector('#df-80cb70a7-c3e9-4576-ae96-a0d628fa44e5');\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",
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              "        element.appendChild(docLink);\n",
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              "\n",
              "\n",
              "<div id=\"df-69521281-3ff7-412f-960b-98d43612908e\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-69521281-3ff7-412f-960b-98d43612908e')\"\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",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-69521281-3ff7-412f-960b-98d43612908e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df3[\\\"WATER\\\"]\",\n  \"rows\": 3895,\n  \"fields\": [\n    {\n      \"column\": \"WaterPollution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.928359709001448,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          87.09677419354838,\n          33.82352941176471,\n          30.555555555555557\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WaterQuality\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.56955403012895,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          38.46153846153846,\n          45.83333333333334,\n          65.625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ikki mavjud column.larning ismlariga nom berish uchun\n",
        "df3.columns.names = [\"Birinchi ustun:\", \"Ikkinchi ustun:\"]\n",
        "df3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 486
        },
        "id": "pwARfSvn_Q9w",
        "outputId": "2dba6d5a-23e6-48b1-b2dd-969a21d675f8"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Birinchi ustun:              AIR                       WATER             \n",
              "Ikkinchi ustun:       AirQuality AirPollution WaterPollution WaterQuality\n",
              "Country     City                                                         \n",
              "Afghanistan Andkhoy    50.000000    50.000000      50.000000    50.000000\n",
              "            Farah     100.000000     0.000000       0.000000   100.000000\n",
              "            Herat      43.750000    31.250000      56.250000    68.750000\n",
              "            Kabul      18.421053    81.060606      81.578947    18.939394\n",
              "            Kandahar    0.000000    75.000000     100.000000    25.000000\n",
              "...                          ...          ...            ...          ...\n",
              "Zambia      Mansa      75.000000    25.000000      25.000000    75.000000\n",
              "Zimbabwe    Bindura    50.000000    75.000000      50.000000    25.000000\n",
              "            Bulawayo   67.857143    71.428571      32.142857    28.571429\n",
              "            Harare     38.461538    87.500000      61.538462    12.500000\n",
              "            Masvingo   25.000000    62.500000      75.000000    37.500000\n",
              "\n",
              "[3895 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6fde66f5-d3ee-4dfe-b0c1-761e297b4862\" class=\"colab-df-container\">\n",
              "    <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 tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr:last-of-type th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Birinchi ustun:</th>\n",
              "      <th colspan=\"2\" halign=\"left\">AIR</th>\n",
              "      <th colspan=\"2\" halign=\"left\">WATER</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Ikkinchi ustun:</th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>AirPollution</th>\n",
              "      <th>WaterPollution</th>\n",
              "      <th>WaterQuality</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country</th>\n",
              "      <th>City</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
              "      <th>Andkhoy</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Farah</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Herat</th>\n",
              "      <td>43.750000</td>\n",
              "      <td>31.250000</td>\n",
              "      <td>56.250000</td>\n",
              "      <td>68.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kabul</th>\n",
              "      <td>18.421053</td>\n",
              "      <td>81.060606</td>\n",
              "      <td>81.578947</td>\n",
              "      <td>18.939394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kandahar</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <th>Mansa</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zimbabwe</th>\n",
              "      <th>Bindura</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bulawayo</th>\n",
              "      <td>67.857143</td>\n",
              "      <td>71.428571</td>\n",
              "      <td>32.142857</td>\n",
              "      <td>28.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harare</th>\n",
              "      <td>38.461538</td>\n",
              "      <td>87.500000</td>\n",
              "      <td>61.538462</td>\n",
              "      <td>12.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Masvingo</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>62.500000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>37.500000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3895 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6fde66f5-d3ee-4dfe-b0c1-761e297b4862')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-6fde66f5-d3ee-4dfe-b0c1-761e297b4862 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-6fde66f5-d3ee-4dfe-b0c1-761e297b4862');\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",
              "\n",
              "\n",
              "<div id=\"df-e76f546a-a41c-41a6-afd1-320255784084\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e76f546a-a41c-41a6-afd1-320255784084')\"\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",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e76f546a-a41c-41a6-afd1-320255784084 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_9ee41c70-f2cd-41de-bbc2-2df895ac39c2\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
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              "        border-radius: 50%;\n",
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              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate: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-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df3')\"\n",
              "            title=\"Generate code using this dataframe.\"\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",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df3');\n",
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              "      })();\n",
              "    </script>\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df3",
              "summary": "{\n  \"name\": \"df3\",\n  \"rows\": 3895,\n  \"fields\": [\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.92835970900157,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          12.903225806451612,\n          66.17647058823529,\n          69.44444444444444\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.569554030128938,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          61.53846153846154,\n          54.16666666666666,\n          34.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.928359709001448,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          87.09677419354838,\n          33.82352941176471,\n          30.555555555555557\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.56955403012895,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          38.46153846153846,\n          45.83333333333334,\n          65.625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# index nomlarini tekshirish\n",
        "df3.index.names"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hGCjkoZC__Nf",
        "outputId": "edb96d32-e799-4b2d-ff8b-7dc86ce37842"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "FrozenList(['Davlat', 'Shahar'])"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df3.index.names = [\"Davlat\", \"Shahar\"]\n",
        "df3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 486
        },
        "id": "WQD5D74TAGjI",
        "outputId": "d44f847b-fde6-48d7-83b0-713032618740"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Birinchi ustun:              AIR                       WATER             \n",
              "Ikkinchi ustun:       AirQuality AirPollution WaterPollution WaterQuality\n",
              "Davlat      Shahar                                                       \n",
              "Afghanistan Andkhoy    50.000000    50.000000      50.000000    50.000000\n",
              "            Farah     100.000000     0.000000       0.000000   100.000000\n",
              "            Herat      43.750000    31.250000      56.250000    68.750000\n",
              "            Kabul      18.421053    81.060606      81.578947    18.939394\n",
              "            Kandahar    0.000000    75.000000     100.000000    25.000000\n",
              "...                          ...          ...            ...          ...\n",
              "Zambia      Mansa      75.000000    25.000000      25.000000    75.000000\n",
              "Zimbabwe    Bindura    50.000000    75.000000      50.000000    25.000000\n",
              "            Bulawayo   67.857143    71.428571      32.142857    28.571429\n",
              "            Harare     38.461538    87.500000      61.538462    12.500000\n",
              "            Masvingo   25.000000    62.500000      75.000000    37.500000\n",
              "\n",
              "[3895 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b4cc731b-6686-459e-bc58-c6f592934c98\" class=\"colab-df-container\">\n",
              "    <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",
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              "\n",
              "    .dataframe thead tr:last-of-type th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Birinchi ustun:</th>\n",
              "      <th colspan=\"2\" halign=\"left\">AIR</th>\n",
              "      <th colspan=\"2\" halign=\"left\">WATER</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Ikkinchi ustun:</th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>AirPollution</th>\n",
              "      <th>WaterPollution</th>\n",
              "      <th>WaterQuality</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Davlat</th>\n",
              "      <th>Shahar</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
              "      <th>Andkhoy</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Farah</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Herat</th>\n",
              "      <td>43.750000</td>\n",
              "      <td>31.250000</td>\n",
              "      <td>56.250000</td>\n",
              "      <td>68.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kabul</th>\n",
              "      <td>18.421053</td>\n",
              "      <td>81.060606</td>\n",
              "      <td>81.578947</td>\n",
              "      <td>18.939394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kandahar</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <th>Mansa</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zimbabwe</th>\n",
              "      <th>Bindura</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bulawayo</th>\n",
              "      <td>67.857143</td>\n",
              "      <td>71.428571</td>\n",
              "      <td>32.142857</td>\n",
              "      <td>28.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harare</th>\n",
              "      <td>38.461538</td>\n",
              "      <td>87.500000</td>\n",
              "      <td>61.538462</td>\n",
              "      <td>12.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Masvingo</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>62.500000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>37.500000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3895 rows × 4 columns</p>\n",
              "</div>\n",
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              "\n",
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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",
              "          + ' to learn more about interactive tables.';\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
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              "type": "dataframe",
              "variable_name": "df3",
              "summary": "{\n  \"name\": \"df3\",\n  \"rows\": 3895,\n  \"fields\": [\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.92835970900157,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          12.903225806451612,\n          66.17647058823529,\n          69.44444444444444\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.569554030128938,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          61.53846153846154,\n          54.16666666666666,\n          34.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.928359709001448,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          87.09677419354838,\n          33.82352941176471,\n          30.555555555555557\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.56955403012895,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          38.46153846153846,\n          45.83333333333334,\n          65.625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# darajalarni o'zgartirish metodi\n",
        "# ya'ni indexlarning o'rnini almashtirish\n",
        "df3.swaplevel(\"Davlat\", \"Shahar\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 486
        },
        "id": "1zx3ZWVBCspx",
        "outputId": "796ae074-bac2-449d-e710-8fb1dcae26bc"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Birinchi ustun:              AIR                       WATER             \n",
              "Ikkinchi ustun:       AirQuality AirPollution WaterPollution WaterQuality\n",
              "Shahar   Davlat                                                          \n",
              "Andkhoy  Afghanistan   50.000000    50.000000      50.000000    50.000000\n",
              "Farah    Afghanistan  100.000000     0.000000       0.000000   100.000000\n",
              "Herat    Afghanistan   43.750000    31.250000      56.250000    68.750000\n",
              "Kabul    Afghanistan   18.421053    81.060606      81.578947    18.939394\n",
              "Kandahar Afghanistan    0.000000    75.000000     100.000000    25.000000\n",
              "...                          ...          ...            ...          ...\n",
              "Mansa    Zambia        75.000000    25.000000      25.000000    75.000000\n",
              "Bindura  Zimbabwe      50.000000    75.000000      50.000000    25.000000\n",
              "Bulawayo Zimbabwe      67.857143    71.428571      32.142857    28.571429\n",
              "Harare   Zimbabwe      38.461538    87.500000      61.538462    12.500000\n",
              "Masvingo Zimbabwe      25.000000    62.500000      75.000000    37.500000\n",
              "\n",
              "[3895 rows x 4 columns]"
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              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Birinchi ustun:</th>\n",
              "      <th colspan=\"2\" halign=\"left\">AIR</th>\n",
              "      <th colspan=\"2\" halign=\"left\">WATER</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Ikkinchi ustun:</th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>AirPollution</th>\n",
              "      <th>WaterPollution</th>\n",
              "      <th>WaterQuality</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shahar</th>\n",
              "      <th>Davlat</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Andkhoy</th>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Farah</th>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Herat</th>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>43.750000</td>\n",
              "      <td>31.250000</td>\n",
              "      <td>56.250000</td>\n",
              "      <td>68.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kabul</th>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>18.421053</td>\n",
              "      <td>81.060606</td>\n",
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              "      <td>18.939394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kandahar</th>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>0.000000</td>\n",
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              "      <td>100.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mansa</th>\n",
              "      <th>Zambia</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bindura</th>\n",
              "      <th>Zimbabwe</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bulawayo</th>\n",
              "      <th>Zimbabwe</th>\n",
              "      <td>67.857143</td>\n",
              "      <td>71.428571</td>\n",
              "      <td>32.142857</td>\n",
              "      <td>28.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harare</th>\n",
              "      <th>Zimbabwe</th>\n",
              "      <td>38.461538</td>\n",
              "      <td>87.500000</td>\n",
              "      <td>61.538462</td>\n",
              "      <td>12.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Masvingo</th>\n",
              "      <th>Zimbabwe</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>62.500000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>37.500000</td>\n",
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              "  </tbody>\n",
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              "<p>3895 rows × 4 columns</p>\n",
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              "summary": "{\n  \"name\": \"df3\",\n  \"rows\": 3895,\n  \"fields\": [\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.92835970900157,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          12.903225806451612,\n          66.17647058823529,\n          69.44444444444444\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.569554030128938,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          61.53846153846154,\n          54.16666666666666,\n          34.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.928359709001448,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          87.09677419354838,\n          33.82352941176471,\n          30.555555555555557\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.56955403012895,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          38.46153846153846,\n          45.83333333333334,\n          65.625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# indexlarni tartiblash\n",
        "# level -> bu asl holati\n",
        "# ascending = False -> teskari tartibda tartiblash\n",
        "df3.sort_index(level = 0, ascending = False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 486
        },
        "id": "1__fK439DBQE",
        "outputId": "cc363fcc-4ca1-4c3f-9294-d6d64632d087"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Birinchi ustun:              AIR                       WATER             \n",
              "Ikkinchi ustun:       AirQuality AirPollution WaterPollution WaterQuality\n",
              "Davlat      Shahar                                                       \n",
              "Zimbabwe    Masvingo   25.000000    62.500000      75.000000    37.500000\n",
              "            Harare     38.461538    87.500000      61.538462    12.500000\n",
              "            Bulawayo   67.857143    71.428571      32.142857    28.571429\n",
              "            Bindura    50.000000    75.000000      50.000000    25.000000\n",
              "Zambia      Mansa      75.000000    25.000000      25.000000    75.000000\n",
              "...                          ...          ...            ...          ...\n",
              "Afghanistan Kandahar    0.000000    75.000000     100.000000    25.000000\n",
              "            Kabul      18.421053    81.060606      81.578947    18.939394\n",
              "            Herat      43.750000    31.250000      56.250000    68.750000\n",
              "            Farah     100.000000     0.000000       0.000000   100.000000\n",
              "            Andkhoy    50.000000    50.000000      50.000000    50.000000\n",
              "\n",
              "[3895 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6fffa67f-ead8-4e4f-9513-ad5181418d9c\" class=\"colab-df-container\">\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Birinchi ustun:</th>\n",
              "      <th colspan=\"2\" halign=\"left\">AIR</th>\n",
              "      <th colspan=\"2\" halign=\"left\">WATER</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Ikkinchi ustun:</th>\n",
              "      <th>AirQuality</th>\n",
              "      <th>AirPollution</th>\n",
              "      <th>WaterPollution</th>\n",
              "      <th>WaterQuality</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Davlat</th>\n",
              "      <th>Shahar</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Zimbabwe</th>\n",
              "      <th>Masvingo</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>62.500000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>37.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Harare</th>\n",
              "      <td>38.461538</td>\n",
              "      <td>87.500000</td>\n",
              "      <td>61.538462</td>\n",
              "      <td>12.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bulawayo</th>\n",
              "      <td>67.857143</td>\n",
              "      <td>71.428571</td>\n",
              "      <td>32.142857</td>\n",
              "      <td>28.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bindura</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <th>Mansa</th>\n",
              "      <td>75.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>75.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">Afghanistan</th>\n",
              "      <th>Kandahar</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kabul</th>\n",
              "      <td>18.421053</td>\n",
              "      <td>81.060606</td>\n",
              "      <td>81.578947</td>\n",
              "      <td>18.939394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Herat</th>\n",
              "      <td>43.750000</td>\n",
              "      <td>31.250000</td>\n",
              "      <td>56.250000</td>\n",
              "      <td>68.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Farah</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andkhoy</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3895 rows × 4 columns</p>\n",
              "</div>\n",
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              "  }\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "\n",
              "    </div>\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df3\",\n  \"rows\": 3895,\n  \"fields\": [\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.928359709001594,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          27.500000000000004,\n          61.02941176470589,\n          70.6896551724138\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"AIR\",\n        \"AirPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.569554030129087,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          42.74193548387097,\n          35.714285714285715,\n          39.58333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterPollution\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.928359709001576,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 686,\n        \"samples\": [\n          72.5,\n          38.97058823529411,\n          29.310344827586206\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"WATER\",\n        \"WaterQuality\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 25.569554030129094,\n        \"min\": 0.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 572,\n        \"samples\": [\n          57.25806451612903,\n          64.28571428571428,\n          60.41666666666667\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    }
  ]
}