DS_3_Modul_3_Amaliyot_tozalash.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/Mrkomiljon/Datascience/blob/main/DS_3_Modul_3_Amaliyot_tozalash.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "cell_type": "markdown",
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        "id": "poH5phdmhSLa"
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      "source": [
        "# ![Imgur](https://i.imgur.com/5pXzCIu.png)\n",
        "\n",
        "# **DATA SCIENCE VA SUN'IY INTELLEKT PRAKTIKUM**\n",
        "\n",
        "## 3.2 Ma'lumotlarni tayyorlash\n",
        "\n",
        "# **AMALIYOT**\n",
        "## Ma'lumotlarga ishlov berish\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wX08M2KIMfHY"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
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      "metadata": {
        "id": "E-eS1Sx-MiTH",
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          "height": 381
        },
        "outputId": "b1ea3af7-2121-4691-d2e7-894f2785a4d3"
      },
      "source": [
        "df = pd.read_csv(\"https://raw.githubusercontent.com/mukhammad-irmatov/health_dataset/main/healt_info.csv\")\n",
        "df.head(3)"
      ],
      "execution_count": 35,
      "outputs": [
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              "      <th></th>\n",
              "      <th>Sno</th>\n",
              "      <th>AGE</th>\n",
              "      <th>SEX</th>\n",
              "      <th>CASTE_NAME</th>\n",
              "      <th>CATEGORY_CODE</th>\n",
              "      <th>CATEGORY_NAME</th>\n",
              "      <th>SURGERY_CODE</th>\n",
              "      <th>SURGERY</th>\n",
              "      <th>VILLAGE</th>\n",
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              "      <th>DISTRICT_NAME</th>\n",
              "      <th>PREAUTH_DATE</th>\n",
              "      <th>PREAUTH_AMT</th>\n",
              "      <th>CLAIM_DATE</th>\n",
              "      <th>CLAIM_AMOUNT</th>\n",
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              "      <th>HOSP_DISTRICT</th>\n",
              "      <th>SURGERY_DATE</th>\n",
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              "      <th>Mortality Y / N</th>\n",
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              "      <th>SRC_REGISTRATION</th>\n",
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              "      <td>07-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
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              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>37</td>\n",
              "      <td>Male</td>\n",
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              "      <td>M6</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>M6.5</td>\n",
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              "      <td>Borivanka</td>\n",
              "      <td>Kaviti</td>\n",
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              "      <td>06-08-2013 07:26</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
              "      <td>Srikakulam</td>\n",
              "      <td>08-08-2013 00:00</td>\n",
              "      <td>09-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>50</td>\n",
              "      <td>Male</td>\n",
              "      <td>BC</td>\n",
              "      <td>M6</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>M6.5</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Kapasakuddi</td>\n",
              "      <td>Kaviti</td>\n",
              "      <td>Srikakulam</td>\n",
              "      <td>09-08-2013 18:30</td>\n",
              "      <td>12500</td>\n",
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              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
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            "text/plain": [
              "   Sno  AGE     SEX  ... Mortality Y / N MORTALITY_DATE SRC_REGISTRATION\n",
              "0    1   56  Female  ...              NO            NaN                D\n",
              "1    2   37    Male  ...              NO            NaN                D\n",
              "2    3   50    Male  ...              NO            NaN                D\n",
              "\n",
              "[3 rows x 23 columns]"
            ]
          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tsm8uZ0JMr5m"
      },
      "source": [
        "Bu dataset sug'urta kompaniyasining real ma'lumotlardan tuzilgan. Bu datasetda 480000 qator sug'urta ma'lumotlar tashkil topgan.\n",
        "Quyida datasetning ba'zi ustunlari haqida qisqacha ma'lumot\n",
        "\n",
        "*   Sno = seriya raqami \n",
        "*   AGE = yoshi\n",
        "*   SEX = jinsi (female = ayol, male = erkak)\n",
        "*   CASTE_NAME = kasta nomi (Hindistonda har bir inson ma'lum bir kastaga oid bo'ladi)\n",
        "*   CATEGORY_CODE = kategoriya kodi\n",
        "*   CATEGORY_Name = kategoriya nomi\n",
        "*   SURGERY_CODE = operatsiya kodi\n",
        "*   Mandal_Name = mandal nomlanishi ya'ni familiyasi desak ham bo'ladi\n",
        "*   Mortality Y/N = vafot etgan yoki vafot etmaganligi\n",
        "*   MORTALITY_DATE = qachon vafot etganligi\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FNLOb9yhxI0b"
      },
      "source": [
        "### **1-mashq**. Datasetdagi barcha takrorlangan qatorlar sonini toping"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o64K3q-UBNAm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c120b66e-30ad-4c19-f896-b9199a7fdd7f"
      },
      "source": [
        "# Javobni shuyerga yozing\n",
        "\n",
        "df.duplicated().sum()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9GJiUd445Kr1"
      },
      "source": [
        "#### **2-mashq**. Datasetdagi quyidagi ustunlar o'chirib yuborilsin:<br>\n",
        "*   Sno\n",
        "*   CATEGORY_CODE\n",
        "*   SURGERY_CODE\n",
        "*   MANDAL_NAME\n",
        "*   DISTRICT_NAME\n",
        "*   HOSP_DISTRICT\n",
        "<BR>\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W8LCqh3466n-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 956
        },
        "outputId": "5664cac9-deed-4129-cab5-3b0a253f65a3"
      },
      "source": [
        "df.drop(['Sno', 'CATEGORY_CODE', 'SURGERY_CODE', 'MANDAL_NAME', 'DISTRICT_NAME', 'HOSP_DISTRICT'],axis='columns', inplace=True)\n",
        "df"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <th>CLAIM_AMOUNT</th>\n",
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              "      <th>DISCHARGE_DATE</th>\n",
              "      <th>Mortality Y / N</th>\n",
              "      <th>MORTALITY_DATE</th>\n",
              "      <th>SRC_REGISTRATION</th>\n",
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              "      <th>0</th>\n",
              "      <td>56</td>\n",
              "      <td>Female</td>\n",
              "      <td>BC</td>\n",
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              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
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              "      <td>NaN</td>\n",
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              "      <th>1</th>\n",
              "      <td>37</td>\n",
              "      <td>Male</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Borivanka</td>\n",
              "      <td>06-08-2013 07:26</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
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              "      <td>09-09-2013 00:00</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>50</td>\n",
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              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Kapasakuddi</td>\n",
              "      <td>09-08-2013 18:30</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11500</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
              "      <td>15-08-2013 00:00</td>\n",
              "      <td>18-10-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>45</td>\n",
              "      <td>Male</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Telikipenta</td>\n",
              "      <td>24-08-2013 19:37</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
              "      <td>24-08-2013 00:00</td>\n",
              "      <td>27-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>54</td>\n",
              "      <td>Male</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Thandemvalasa</td>\n",
              "      <td>28-08-2013 17:03</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
              "      <td>31-08-2013 00:00</td>\n",
              "      <td>02-10-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335389</th>\n",
              "      <td>65</td>\n",
              "      <td>Male</td>\n",
              "      <td>SC</td>\n",
              "      <td>OPHTHALMOLOGY  SURGERY</td>\n",
              "      <td>Vitrectomy Plus Silicon Oil Or Gas (14.75)</td>\n",
              "      <td>Chintalapudi</td>\n",
              "      <td>08-06-2017 06:40</td>\n",
              "      <td>23320</td>\n",
              "      <td>04-08-2017 21:23</td>\n",
              "      <td>23320</td>\n",
              "      <td>Sankar Eye Hospital</td>\n",
              "      <td>C</td>\n",
              "      <td>09-06-2017 00:00</td>\n",
              "      <td>10-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335390</th>\n",
              "      <td>54</td>\n",
              "      <td>Female</td>\n",
              "      <td>OC</td>\n",
              "      <td>MEDICAL ONCOLOGY</td>\n",
              "      <td>Chemotherapy for Breast Cancer with Paclitaxel</td>\n",
              "      <td>Udayagiri @ Kondayapale</td>\n",
              "      <td>05-06-2017 22:35</td>\n",
              "      <td>7140</td>\n",
              "      <td>02-08-2017 19:11</td>\n",
              "      <td>7140</td>\n",
              "      <td>BASAVATARAKAM INDO AMERICAN CANCER HOSPITAL an...</td>\n",
              "      <td>C</td>\n",
              "      <td>06-06-2017 00:00</td>\n",
              "      <td>06-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335391</th>\n",
              "      <td>19</td>\n",
              "      <td>Female</td>\n",
              "      <td>SC</td>\n",
              "      <td>MEDICAL ONCOLOGY</td>\n",
              "      <td>Palliative Chemotherapy for unlisted Regimen</td>\n",
              "      <td>Vinduru</td>\n",
              "      <td>06-06-2017 06:13</td>\n",
              "      <td>5000</td>\n",
              "      <td>04-10-2017 19:46</td>\n",
              "      <td>5000</td>\n",
              "      <td>M.N.J.Hospitals</td>\n",
              "      <td>G</td>\n",
              "      <td>09-06-2017 00:00</td>\n",
              "      <td>10-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335392</th>\n",
              "      <td>50</td>\n",
              "      <td>Male</td>\n",
              "      <td>BC</td>\n",
              "      <td>GENITO URINARY SURGERIES</td>\n",
              "      <td>ursl</td>\n",
              "      <td>Duppituru</td>\n",
              "      <td>05-06-2017 23:37</td>\n",
              "      <td>25000</td>\n",
              "      <td>04-08-2017 20:59</td>\n",
              "      <td>25000</td>\n",
              "      <td>GAJUWAKA HOSPITALS PVT LTD RK HOSPITAL</td>\n",
              "      <td>C</td>\n",
              "      <td>06-06-2017 00:00</td>\n",
              "      <td>10-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335393</th>\n",
              "      <td>46</td>\n",
              "      <td>Female</td>\n",
              "      <td>SC</td>\n",
              "      <td>MEDICAL ONCOLOGY</td>\n",
              "      <td>Chemotherapy for Cervical Cancer with Weekly C...</td>\n",
              "      <td>Ananthavaram</td>\n",
              "      <td>06-06-2017 23:02</td>\n",
              "      <td>2040</td>\n",
              "      <td>09-08-2017 19:43</td>\n",
              "      <td>2040</td>\n",
              "      <td>SURYA GLOBAL MULTI SPECIALITY HOSPITALS AND CA...</td>\n",
              "      <td>C</td>\n",
              "      <td>07-06-2017 00:00</td>\n",
              "      <td>07-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>MC</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>335394 rows × 17 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ca62dce8-0364-4a44-90b5-ccb011f69d6f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      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-ca62dce8-0364-4a44-90b5-ccb011f69d6f 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-ca62dce8-0364-4a44-90b5-ccb011f69d6f');\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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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        AGE     SEX CASTE_NAME  ... Mortality Y / N MORTALITY_DATE SRC_REGISTRATION\n",
              "0        56  Female         BC  ...              NO            NaN                D\n",
              "1        37    Male         BC  ...              NO            NaN                D\n",
              "2        50    Male         BC  ...              NO            NaN                D\n",
              "3        45    Male         BC  ...              NO            NaN                D\n",
              "4        54    Male         BC  ...              NO            NaN                D\n",
              "...     ...     ...        ...  ...             ...            ...              ...\n",
              "335389   65    Male         SC  ...              NO            NaN                D\n",
              "335390   54  Female         OC  ...              NO            NaN                D\n",
              "335391   19  Female         SC  ...              NO            NaN                D\n",
              "335392   50    Male         BC  ...              NO            NaN                D\n",
              "335393   46  Female         SC  ...              NO            NaN               MC\n",
              "\n",
              "[335394 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wVuuU-XZO-0Y"
      },
      "source": [
        "#### **3-mashq**. Datasetdagi sex(jinsi) nomli qatordagi qiymatlarni unique funksiyasi orqali tekshiring.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i9e_7Icu0Xms",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b3b6f178-4e42-4799-ceb6-946b7ace1f44"
      },
      "source": [
        "df.SEX.unique()"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Female', 'Male', 'Male(Child)', 'Female(Child)', 'FEMALE'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nfwZ0uQo1xXm"
      },
      "source": [
        "#### **4-mashq**. Datasetdagi sex(jinsi) nomli qatordagi qiymatlarni **Erkak** va **Ayol** ga o'zgartiring:\n",
        "O'zgartirish quyidagicha bo'lsin:\n",
        "\n",
        "\n",
        "*   Male -> Erkak\n",
        "*   Male(child) -> Erkak\n",
        "*   Female - > Ayol\n",
        "*   Female(child) - Ayol\n",
        "*   MALE -> Erkak\n",
        "*   FEMALE -> Ayol\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "54IqaOmz159z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d00650cb-3f30-489b-8027-88f983d7aa8c"
      },
      "source": [
        "dict={'Female':'Ayol', 'Male':'Erkak', 'Male(Child)':'Erkak', 'Female(Child)':'Ayol', 'FEMALE':'Ayol'}\n",
        "df['SEX'].map(dict)"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0          Ayol\n",
              "1         Erkak\n",
              "2         Erkak\n",
              "3         Erkak\n",
              "4         Erkak\n",
              "          ...  \n",
              "335389    Erkak\n",
              "335390     Ayol\n",
              "335391     Ayol\n",
              "335392    Erkak\n",
              "335393     Ayol\n",
              "Name: SEX, Length: 335394, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t_KWHWqj3D38"
      },
      "source": [
        "#### **5-mashq**. Endi xuddi shu SEX columndagi ma'lumotlarni raqamlarga o'zgartiring: Erkaklarni 1 raqamiga, Ayollarni 0 raqamiga o'zgartiring.\n",
        "*   Erkak -> 1\n",
        "*   Ayol -> 0"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CU3ygcnh3LAd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 548
        },
        "outputId": "aa4dbde7-3d19-48b5-8bfb-16c5beb59cd3"
      },
      "source": [
        "dict={'Female':'0', 'Male':'1', 'Male(Child)':'1', 'Female(Child)':'0', 'FEMALE':'0'}\n",
        "df['SEX']=df['SEX'].map(dict)\n",
        "df.head()"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-14dccb68-5594-47f6-86fa-e5967a6e9064\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
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              "      <th></th>\n",
              "      <th>AGE</th>\n",
              "      <th>SEX</th>\n",
              "      <th>CASTE_NAME</th>\n",
              "      <th>CATEGORY_NAME</th>\n",
              "      <th>SURGERY</th>\n",
              "      <th>VILLAGE</th>\n",
              "      <th>PREAUTH_DATE</th>\n",
              "      <th>PREAUTH_AMT</th>\n",
              "      <th>CLAIM_DATE</th>\n",
              "      <th>CLAIM_AMOUNT</th>\n",
              "      <th>HOSP_NAME</th>\n",
              "      <th>HOSP_TYPE</th>\n",
              "      <th>SURGERY_DATE</th>\n",
              "      <th>DISCHARGE_DATE</th>\n",
              "      <th>Mortality Y / N</th>\n",
              "      <th>MORTALITY_DATE</th>\n",
              "      <th>SRC_REGISTRATION</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>56</td>\n",
              "      <td>0</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Lolugu</td>\n",
              "      <td>03-08-2013 20:38</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
              "      <td>06-08-2013 00:00</td>\n",
              "      <td>07-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>Borivanka</td>\n",
              "      <td>06-08-2013 07:26</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
              "      <td>08-08-2013 00:00</td>\n",
              "      <td>09-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Kapasakuddi</td>\n",
              "      <td>09-08-2013 18:30</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11500</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
              "      <td>15-08-2013 00:00</td>\n",
              "      <td>18-10-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Telikipenta</td>\n",
              "      <td>24-08-2013 19:37</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
              "      <td>24-08-2013 00:00</td>\n",
              "      <td>27-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>54</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Thandemvalasa</td>\n",
              "      <td>28-08-2013 17:03</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>G</td>\n",
              "      <td>31-08-2013 00:00</td>\n",
              "      <td>02-10-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-14dccb68-5594-47f6-86fa-e5967a6e9064 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-14dccb68-5594-47f6-86fa-e5967a6e9064');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   AGE SEX CASTE_NAME  ... Mortality Y / N MORTALITY_DATE SRC_REGISTRATION\n",
              "0   56   0         BC  ...              NO            NaN                D\n",
              "1   37   1         BC  ...              NO            NaN                D\n",
              "2   50   1         BC  ...              NO            NaN                D\n",
              "3   45   1         BC  ...              NO            NaN                D\n",
              "4   54   1         BC  ...              NO            NaN                D\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i4n7ulS75WA4"
      },
      "source": [
        "#### **6-mashq**. Shu jarayonni HOSP_TYPE ustuni uchun ham amalga oshiring. \n",
        "*   G - General hospital (umumiy kasalxona) degani\n",
        "*   C - Special hospital (maxsus kasalxona) degani\n",
        "<br><b>O'zgarish quyidagicha bo'lsin:</b>\n",
        "*   G -> Umumiy \n",
        "*   C -> Maxsus\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BEokSEre43GK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 548
        },
        "outputId": "8ce46bb5-aeba-41c3-b488-e0967b0de295"
      },
      "source": [
        "dict={'G':'Umumiy', 'C':'Maxsus'}\n",
        "df['HOSP_TYPE']=df['HOSP_TYPE'].map(dict)\n",
        "df.head()\n",
        "\n"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-aaa25eaa-188b-4bfd-99f2-7222dfd8fb13\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>AGE</th>\n",
              "      <th>SEX</th>\n",
              "      <th>CASTE_NAME</th>\n",
              "      <th>CATEGORY_NAME</th>\n",
              "      <th>SURGERY</th>\n",
              "      <th>VILLAGE</th>\n",
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              "      <th>CLAIM_DATE</th>\n",
              "      <th>CLAIM_AMOUNT</th>\n",
              "      <th>HOSP_NAME</th>\n",
              "      <th>HOSP_TYPE</th>\n",
              "      <th>SURGERY_DATE</th>\n",
              "      <th>DISCHARGE_DATE</th>\n",
              "      <th>Mortality Y / N</th>\n",
              "      <th>MORTALITY_DATE</th>\n",
              "      <th>SRC_REGISTRATION</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>56</td>\n",
              "      <td>0</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Lolugu</td>\n",
              "      <td>03-08-2013 20:38</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>06-08-2013 00:00</td>\n",
              "      <td>07-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>37</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Borivanka</td>\n",
              "      <td>06-08-2013 07:26</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>08-08-2013 00:00</td>\n",
              "      <td>09-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Kapasakuddi</td>\n",
              "      <td>09-08-2013 18:30</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11500</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>15-08-2013 00:00</td>\n",
              "      <td>18-10-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Telikipenta</td>\n",
              "      <td>24-08-2013 19:37</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>24-08-2013 00:00</td>\n",
              "      <td>27-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>54</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Thandemvalasa</td>\n",
              "      <td>28-08-2013 17:03</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>31-08-2013 00:00</td>\n",
              "      <td>02-10-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-aaa25eaa-188b-4bfd-99f2-7222dfd8fb13')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      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-aaa25eaa-188b-4bfd-99f2-7222dfd8fb13 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-aaa25eaa-188b-4bfd-99f2-7222dfd8fb13');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   AGE SEX CASTE_NAME  ... Mortality Y / N MORTALITY_DATE SRC_REGISTRATION\n",
              "0   56   0         BC  ...              NO            NaN                D\n",
              "1   37   1         BC  ...              NO            NaN                D\n",
              "2   50   1         BC  ...              NO            NaN                D\n",
              "3   45   1         BC  ...              NO            NaN                D\n",
              "4   54   1         BC  ...              NO            NaN                D\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "id": "ALhBzKu35lBb"
      },
      "source": [
        "#@title **To'g'ri javob**\n",
        "df[\"HOSP_TYPE\"] = df[\"HOSP_TYPE\"].map({'G':\"Umumiy\", 'C':\"Maxsus\"})\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4YozaezB4qqa"
      },
      "source": [
        "#### **7-mashq**. O'zgartirish amalga oshirilgach, HOSP_TYPE ustunida qancha Umumiy va qancha Maxsus kasalxonalar borligini ham aniqlang\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XNa8b4s25IUN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9a930fe9-3122-4571-ef08-8845da4a3f43"
      },
      "source": [
        "df.HOSP_TYPE.value_counts()"
      ],
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Maxsus    241139\n",
              "Umumiy     94255\n",
              "Name: HOSP_TYPE, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "id": "j472LUxgU0P-"
      },
      "source": [
        "#@title **To'g'ri javob**\n",
        "df[\"HOSP_TYPE\"].value_counts()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kEr2LYiJ_I-k"
      },
      "source": [
        "#### **8-mashq**. Datasetda qancha takrorlangan qatorlar borligini aniqlang  \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7EzWPhDZ_i5o",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e19cb0aa-7b02-4677-a0ff-0313be00d3a1"
      },
      "source": [
        "df.duplicated().sum()\n",
        "\n"
      ],
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "30"
            ]
          },
          "metadata": {},
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "id": "J3yF9CKM5eTs"
      },
      "source": [
        "#@title **To'g'ri javob**\n",
        "sum(df.duplicated())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6gphfgtd_nJK"
      },
      "source": [
        "#### **9-mashq**. Datasetda barcha takrorlangan qatorlarni o'chirib yuboring  \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DdsEuZXg_tEd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 956
        },
        "outputId": "ddbb69a8-5e8e-428d-a381-316c4a69e17e"
      },
      "source": [
        "# Javobni shuyerga yozing\n",
        "df.drop_duplicates()\n"
      ],
      "execution_count": 75,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-c1d49a4c-5e7a-43be-b9a1-1c59f4ba45bf\">\n",
              "    <div 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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              "    .dataframe tbody tr th {\n",
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>AGE</th>\n",
              "      <th>SEX</th>\n",
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              "      <th>HOSP_NAME</th>\n",
              "      <th>HOSP_TYPE</th>\n",
              "      <th>SURGERY_DATE</th>\n",
              "      <th>DISCHARGE_DATE</th>\n",
              "      <th>Mortality Y / N</th>\n",
              "      <th>MORTALITY_DATE</th>\n",
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              "      <th>0</th>\n",
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              "      <td>03-08-2013 20:38</td>\n",
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              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>06-08-2013 00:00</td>\n",
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              "      <td>NO</td>\n",
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              "      <td>1</td>\n",
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              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Borivanka</td>\n",
              "      <td>06-08-2013 07:26</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>08-08-2013 00:00</td>\n",
              "      <td>09-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Kapasakuddi</td>\n",
              "      <td>09-08-2013 18:30</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11500</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>15-08-2013 00:00</td>\n",
              "      <td>18-10-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Telikipenta</td>\n",
              "      <td>24-08-2013 19:37</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>24-08-2013 00:00</td>\n",
              "      <td>27-09-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>54</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>NEPHROLOGY</td>\n",
              "      <td>Maintenance Hemodialysis For Crf</td>\n",
              "      <td>Thandemvalasa</td>\n",
              "      <td>28-08-2013 17:03</td>\n",
              "      <td>12500</td>\n",
              "      <td>22-03-2017 20:25</td>\n",
              "      <td>11000</td>\n",
              "      <td>Rims Govt. General Hospital, Srikakulam</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>31-08-2013 00:00</td>\n",
              "      <td>02-10-2013 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335389</th>\n",
              "      <td>65</td>\n",
              "      <td>1</td>\n",
              "      <td>SC</td>\n",
              "      <td>OPHTHALMOLOGY  SURGERY</td>\n",
              "      <td>Vitrectomy Plus Silicon Oil Or Gas (14.75)</td>\n",
              "      <td>Chintalapudi</td>\n",
              "      <td>08-06-2017 06:40</td>\n",
              "      <td>23320</td>\n",
              "      <td>04-08-2017 21:23</td>\n",
              "      <td>23320</td>\n",
              "      <td>Sankar Eye Hospital</td>\n",
              "      <td>Maxsus</td>\n",
              "      <td>09-06-2017 00:00</td>\n",
              "      <td>10-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335390</th>\n",
              "      <td>54</td>\n",
              "      <td>0</td>\n",
              "      <td>OC</td>\n",
              "      <td>MEDICAL ONCOLOGY</td>\n",
              "      <td>Chemotherapy for Breast Cancer with Paclitaxel</td>\n",
              "      <td>Udayagiri @ Kondayapale</td>\n",
              "      <td>05-06-2017 22:35</td>\n",
              "      <td>7140</td>\n",
              "      <td>02-08-2017 19:11</td>\n",
              "      <td>7140</td>\n",
              "      <td>BASAVATARAKAM INDO AMERICAN CANCER HOSPITAL an...</td>\n",
              "      <td>Maxsus</td>\n",
              "      <td>06-06-2017 00:00</td>\n",
              "      <td>06-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335391</th>\n",
              "      <td>19</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>MEDICAL ONCOLOGY</td>\n",
              "      <td>Palliative Chemotherapy for unlisted Regimen</td>\n",
              "      <td>Vinduru</td>\n",
              "      <td>06-06-2017 06:13</td>\n",
              "      <td>5000</td>\n",
              "      <td>04-10-2017 19:46</td>\n",
              "      <td>5000</td>\n",
              "      <td>M.N.J.Hospitals</td>\n",
              "      <td>Umumiy</td>\n",
              "      <td>09-06-2017 00:00</td>\n",
              "      <td>10-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335392</th>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>BC</td>\n",
              "      <td>GENITO URINARY SURGERIES</td>\n",
              "      <td>ursl</td>\n",
              "      <td>Duppituru</td>\n",
              "      <td>05-06-2017 23:37</td>\n",
              "      <td>25000</td>\n",
              "      <td>04-08-2017 20:59</td>\n",
              "      <td>25000</td>\n",
              "      <td>GAJUWAKA HOSPITALS PVT LTD RK HOSPITAL</td>\n",
              "      <td>Maxsus</td>\n",
              "      <td>06-06-2017 00:00</td>\n",
              "      <td>10-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>D</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335393</th>\n",
              "      <td>46</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>MEDICAL ONCOLOGY</td>\n",
              "      <td>Chemotherapy for Cervical Cancer with Weekly C...</td>\n",
              "      <td>Ananthavaram</td>\n",
              "      <td>06-06-2017 23:02</td>\n",
              "      <td>2040</td>\n",
              "      <td>09-08-2017 19:43</td>\n",
              "      <td>2040</td>\n",
              "      <td>SURYA GLOBAL MULTI SPECIALITY HOSPITALS AND CA...</td>\n",
              "      <td>Maxsus</td>\n",
              "      <td>07-06-2017 00:00</td>\n",
              "      <td>07-06-2017 00:00</td>\n",
              "      <td>NO</td>\n",
              "      <td>NaN</td>\n",
              "      <td>MC</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>335364 rows × 17 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c1d49a4c-5e7a-43be-b9a1-1c59f4ba45bf')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "\n",
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              "\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c1d49a4c-5e7a-43be-b9a1-1c59f4ba45bf button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c1d49a4c-5e7a-43be-b9a1-1c59f4ba45bf');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "        }\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        AGE SEX CASTE_NAME  ... Mortality Y / N MORTALITY_DATE SRC_REGISTRATION\n",
              "0        56   0         BC  ...              NO            NaN                D\n",
              "1        37   1         BC  ...              NO            NaN                D\n",
              "2        50   1         BC  ...              NO            NaN                D\n",
              "3        45   1         BC  ...              NO            NaN                D\n",
              "4        54   1         BC  ...              NO            NaN                D\n",
              "...     ...  ..        ...  ...             ...            ...              ...\n",
              "335389   65   1         SC  ...              NO            NaN                D\n",
              "335390   54   0         OC  ...              NO            NaN                D\n",
              "335391   19   0         SC  ...              NO            NaN                D\n",
              "335392   50   1         BC  ...              NO            NaN                D\n",
              "335393   46   0         SC  ...              NO            NaN               MC\n",
              "\n",
              "[335364 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "id": "sy_c4uyI_t6f"
      },
      "source": [
        "#@title **To'g'ri javob**\n",
        "df.drop_duplicates(inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bN26F9LP_2RE"
      },
      "source": [
        "#### **10-mashq**. Datasetdan shifoxona turiga ko'ra (umumiy va maxsus), ClAIM_AMOUNTning o'rtacha qiymatlarini toping.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t2NcocXLFI78",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "072f8149-c457-4698-ccfc-426219bb7dd0"
      },
      "source": [
        "df.groupby(['HOSP_TYPE']).CLAIM_AMOUNT.mean()\n",
        "\n"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "HOSP_TYPE\n",
              "Maxsus    30272.214457\n",
              "Umumiy    22683.900769\n",
              "Name: CLAIM_AMOUNT, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7QnvZvW6F3Su"
      },
      "source": [
        "#### **11-mashq**. Datasetdan shifoxona turiga ko'ra (umumiy va maxsus), ClAIM_AMOUNTning minimum qiymatlarini toping.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5K42PI7tF0On",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "324f8f81-a0c5-4220-c78f-1c62b68ab848"
      },
      "source": [
        "df.groupby(['HOSP_TYPE']).CLAIM_AMOUNT.min()\n"
      ],
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "HOSP_TYPE\n",
              "Maxsus    2\n",
              "Umumiy    2\n",
              "Name: CLAIM_AMOUNT, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KQKllXlaF5D7"
      },
      "source": [
        "#### **12-mashq**. Datasetdan shifoxona turiga ko'ra (umumiy va maxsus), CLAIM_AMOUNTning maksimum qiymatlarini toping.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7RNQVzsCF8-m",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "843b3ce2-4f5d-4d87-9fb8-95de3b3df09d"
      },
      "source": [
        "# Javobni shuyerga yozing\n",
        "df.groupby(['HOSP_TYPE']).CLAIM_AMOUNT.max()\n"
      ],
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "HOSP_TYPE\n",
              "Maxsus    520000\n",
              "Umumiy    520000\n",
              "Name: CLAIM_AMOUNT, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "id": "PM-8O6dZF-c_"
      },
      "source": [
        "#@title **To'g'ri javob**\n",
        "df.groupby('HOSP_TYPE').CLAIM_AMOUNT.max()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JhL3fPU4HJkK"
      },
      "source": [
        ".agg() yordamida istalgan funksiyalarni chaqirishimiz mumkin, misol uchun numpy dagi mean (o'rta qiymat) funiksiyasini ham qo'shamiz. Natijalarni faqat price ustuni uchun chiqaramiz:"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZaAwTY8RHLBB"
      },
      "source": [
        "#### **13-mashq**. Datasetdan jinsiga ko'ra CLAIM_AMOUNTning min, max va o'rta qiymatlarni agg() usuli yordamida toping.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-X_HduSGH00I",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "01df1adb-d334-40cb-c11a-92514cc7f00e"
      },
      "source": [
        "df.groupby(['SEX']).CLAIM_AMOUNT.agg([min, max, np.mean])\n",
        "\n"
      ],
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
              "  <div id=\"df-f08b6282-f890-453a-bd97-526eb6a58987\">\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f08b6282-f890-453a-bd97-526eb6a58987 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-f08b6282-f890-453a-bd97-526eb6a58987');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     min     max          mean\n",
              "SEX                           \n",
              "0      2  520000  25958.693494\n",
              "1      2  520000  29584.682625"
            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "id": "3372GXlAHsvB"
      },
      "source": [
        "#@title **To'g'ri javob**\n",
        "df.groupby('SEX').CLAIM_AMOUNT.agg([min, max, np.mean])\n"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}