Heart_Failure.ipynb

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        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
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        "heart_failure_raw_df = pd.read_csv('/content/drive/MyDrive/Datasets/Heartfailure.zip')\n",
        "heart_failure_df = heart_failure_raw_df.copy()\n",
        "heart_failure_df"
      ],
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              "      age  anaemia  creatinine_phosphokinase  diabetes  ejection_fraction  \\\n",
              "0    75.0        0                       582         0                 20   \n",
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              "\n",
              "     high_blood_pressure  platelets  serum_creatinine  serum_sodium  sex  \\\n",
              "0                      1  265000.00               1.9           130    1   \n",
              "1                      0  263358.03               1.1           136    1   \n",
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              "297                    0  140000.00               1.4           140    1   \n",
              "298                    0  395000.00               1.6           136    1   \n",
              "\n",
              "     smoking  time  DEATH_EVENT  \n",
              "0          0     4            1  \n",
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        "#renaming DEATH_EVENT as patient_dead for my convenience\n",
        "heart_failure_df.rename(columns = {'DEATH_EVENT':'patient_dead'}, inplace = True)\n",
        "#drop the time column which is not necessary for our analysis\n",
        "heart_failure_df.drop(['time'],axis=1, inplace =True, errors = 'ignore')\n",
        "#changing the data type of age column from float to int\n",
        "heart_failure_df.age = heart_failure_df.age.astype(int)\n",
        "#changing the data type of following columns to bool type for our convenience\n",
        "heart_failure_df[['anaemia','diabetes','high_blood_pressure', 'smoking', 'patient_dead']] = heart_failure_df[['anaemia','diabetes', 'high_blood_pressure', 'smoking', 'patient_dead']].astype(bool)\n",
        "#changing the value of sex column to male or female\n",
        "heart_failure_df['sex'] = np.where(heart_failure_df['sex'] == 1, 'Male','Female')\n",
        "#to convert the platelet-count into kilo-platelets/mcL\n",
        "heart_failure_df.platelets = (heart_failure_df. platelets/1000).astype(int)\n",
        "heart_failure_df"
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              "     age  anaemia  creatinine_phosphokinase  diabetes  ejection_fraction  \\\n",
              "0     75    False                       582     False                 20   \n",
              "1     55    False                      7861     False                 38   \n",
              "2     65    False                       146     False                 20   \n",
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              "..   ...      ...                       ...       ...                ...   \n",
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              "297   45    False                      2413     False                 38   \n",
              "298   50    False                       196     False                 45   \n",
              "\n",
              "     high_blood_pressure  platelets  serum_creatinine  serum_sodium     sex  \\\n",
              "0                   True        265               1.9           130    Male   \n",
              "1                  False        263               1.1           136    Male   \n",
              "2                  False        162               1.3           129    Male   \n",
              "3                  False        210               1.9           137    Male   \n",
              "4                  False        327               2.7           116  Female   \n",
              "..                   ...        ...               ...           ...     ...   \n",
              "294                 True        155               1.1           143    Male   \n",
              "295                False        270               1.2           139  Female   \n",
              "296                False        742               0.8           138  Female   \n",
              "297                False        140               1.4           140    Male   \n",
              "298                False        395               1.6           136    Male   \n",
              "\n",
              "     smoking  patient_dead  \n",
              "0      False          True  \n",
              "1      False          True  \n",
              "2       True          True  \n",
              "3      False          True  \n",
              "4      False          True  \n",
              "..       ...           ...  \n",
              "294     True         False  \n",
              "295    False         False  \n",
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              "      <td>1.3</td>\n",
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              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>50</td>\n",
              "      <td>True</td>\n",
              "      <td>111</td>\n",
              "      <td>False</td>\n",
              "      <td>20</td>\n",
              "      <td>False</td>\n",
              "      <td>210</td>\n",
              "      <td>1.9</td>\n",
              "      <td>137</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>65</td>\n",
              "      <td>True</td>\n",
              "      <td>160</td>\n",
              "      <td>True</td>\n",
              "      <td>20</td>\n",
              "      <td>False</td>\n",
              "      <td>327</td>\n",
              "      <td>2.7</td>\n",
              "      <td>116</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>True</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>294</th>\n",
              "      <td>62</td>\n",
              "      <td>False</td>\n",
              "      <td>61</td>\n",
              "      <td>True</td>\n",
              "      <td>38</td>\n",
              "      <td>True</td>\n",
              "      <td>155</td>\n",
              "      <td>1.1</td>\n",
              "      <td>143</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>295</th>\n",
              "      <td>55</td>\n",
              "      <td>False</td>\n",
              "      <td>1820</td>\n",
              "      <td>False</td>\n",
              "      <td>38</td>\n",
              "      <td>False</td>\n",
              "      <td>270</td>\n",
              "      <td>1.2</td>\n",
              "      <td>139</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>296</th>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>2060</td>\n",
              "      <td>True</td>\n",
              "      <td>60</td>\n",
              "      <td>False</td>\n",
              "      <td>742</td>\n",
              "      <td>0.8</td>\n",
              "      <td>138</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>297</th>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>2413</td>\n",
              "      <td>False</td>\n",
              "      <td>38</td>\n",
              "      <td>False</td>\n",
              "      <td>140</td>\n",
              "      <td>1.4</td>\n",
              "      <td>140</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>298</th>\n",
              "      <td>50</td>\n",
              "      <td>False</td>\n",
              "      <td>196</td>\n",
              "      <td>False</td>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>395</td>\n",
              "      <td>1.6</td>\n",
              "      <td>136</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>299 rows × 12 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4d86c214-d214-494f-87ff-d33e9f796bcd')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-4d86c214-d214-494f-87ff-d33e9f796bcd 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-4d86c214-d214-494f-87ff-d33e9f796bcd');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "L_WwNEaakp3V",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c1bc40c3-2d1d-4574-b49b-2bbbe120812e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "heart_failure_df.isnull().any()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O5KCFo3c1beP",
        "outputId": "afa1eeec-2ab3-477e-8c93-fe0c724a9d48"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age                         False\n",
              "anaemia                     False\n",
              "creatinine_phosphokinase    False\n",
              "diabetes                    False\n",
              "ejection_fraction           False\n",
              "high_blood_pressure         False\n",
              "platelets                   False\n",
              "serum_creatinine            False\n",
              "serum_sodium                False\n",
              "sex                         False\n",
              "smoking                     False\n",
              "patient_dead                False\n",
              "dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "heart_failure_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4H18eEZn1d4I",
        "outputId": "e02f97bc-d689-4e85-862b-f9757ff3c991"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 299 entries, 0 to 298\n",
            "Data columns (total 12 columns):\n",
            " #   Column                    Non-Null Count  Dtype  \n",
            "---  ------                    --------------  -----  \n",
            " 0   age                       299 non-null    int64  \n",
            " 1   anaemia                   299 non-null    bool   \n",
            " 2   creatinine_phosphokinase  299 non-null    int64  \n",
            " 3   diabetes                  299 non-null    bool   \n",
            " 4   ejection_fraction         299 non-null    int64  \n",
            " 5   high_blood_pressure       299 non-null    bool   \n",
            " 6   platelets                 299 non-null    int64  \n",
            " 7   serum_creatinine          299 non-null    float64\n",
            " 8   serum_sodium              299 non-null    int64  \n",
            " 9   sex                       299 non-null    object \n",
            " 10  smoking                   299 non-null    bool   \n",
            " 11  patient_dead              299 non-null    bool   \n",
            "dtypes: bool(5), float64(1), int64(5), object(1)\n",
            "memory usage: 17.9+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "heart_failure_df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        },
        "id": "2sKy89sK2Gud",
        "outputId": "524a0c6a-dbb9-42e6-c94c-045ce4f5c3ff"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              age  creatinine_phosphokinase  ejection_fraction   platelets  \\\n",
              "count  299.000000                299.000000         299.000000  299.000000   \n",
              "mean    60.829431                581.839465          38.083612  263.327759   \n",
              "std     11.894997                970.287881          11.834841   97.805105   \n",
              "min     40.000000                 23.000000          14.000000   25.000000   \n",
              "25%     51.000000                116.500000          30.000000  212.500000   \n",
              "50%     60.000000                250.000000          38.000000  262.000000   \n",
              "75%     70.000000                582.000000          45.000000  303.500000   \n",
              "max     95.000000               7861.000000          80.000000  850.000000   \n",
              "\n",
              "       serum_creatinine  serum_sodium  \n",
              "count         299.00000    299.000000  \n",
              "mean            1.39388    136.625418  \n",
              "std             1.03451      4.412477  \n",
              "min             0.50000    113.000000  \n",
              "25%             0.90000    134.000000  \n",
              "50%             1.10000    137.000000  \n",
              "75%             1.40000    140.000000  \n",
              "max             9.40000    148.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b8328bce-b108-43c1-99bc-8d604aba711e\">\n",
              "    <div 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>age</th>\n",
              "      <th>creatinine_phosphokinase</th>\n",
              "      <th>ejection_fraction</th>\n",
              "      <th>platelets</th>\n",
              "      <th>serum_creatinine</th>\n",
              "      <th>serum_sodium</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>299.000000</td>\n",
              "      <td>299.000000</td>\n",
              "      <td>299.000000</td>\n",
              "      <td>299.000000</td>\n",
              "      <td>299.00000</td>\n",
              "      <td>299.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>60.829431</td>\n",
              "      <td>581.839465</td>\n",
              "      <td>38.083612</td>\n",
              "      <td>263.327759</td>\n",
              "      <td>1.39388</td>\n",
              "      <td>136.625418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>11.894997</td>\n",
              "      <td>970.287881</td>\n",
              "      <td>11.834841</td>\n",
              "      <td>97.805105</td>\n",
              "      <td>1.03451</td>\n",
              "      <td>4.412477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>40.000000</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>0.50000</td>\n",
              "      <td>113.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>51.000000</td>\n",
              "      <td>116.500000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>212.500000</td>\n",
              "      <td>0.90000</td>\n",
              "      <td>134.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>60.000000</td>\n",
              "      <td>250.000000</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>262.000000</td>\n",
              "      <td>1.10000</td>\n",
              "      <td>137.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>70.000000</td>\n",
              "      <td>582.000000</td>\n",
              "      <td>45.000000</td>\n",
              "      <td>303.500000</td>\n",
              "      <td>1.40000</td>\n",
              "      <td>140.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>95.000000</td>\n",
              "      <td>7861.000000</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>850.000000</td>\n",
              "      <td>9.40000</td>\n",
              "      <td>148.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b8328bce-b108-43c1-99bc-8d604aba711e')\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b8328bce-b108-43c1-99bc-8d604aba711e 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-b8328bce-b108-43c1-99bc-8d604aba711e');\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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              "  </div>\n",
              "  "
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          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
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      "cell_type": "code",
      "source": [
        "heart_failure_df.drop('creatinine_phosphokinase', inplace= True, axis=1, errors ='ignore')"
      ],
      "metadata": {
        "id": "pJxQkpeEoH3f"
      },
      "execution_count": null,
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        "heart_failure_df.info()"
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      },
      "execution_count": null,
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        {
          "output_type": "stream",
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 299 entries, 0 to 298\n",
            "Data columns (total 11 columns):\n",
            " #   Column               Non-Null Count  Dtype  \n",
            "---  ------               --------------  -----  \n",
            " 0   age                  299 non-null    int64  \n",
            " 1   anaemia              299 non-null    bool   \n",
            " 2   diabetes             299 non-null    bool   \n",
            " 3   ejection_fraction    299 non-null    int64  \n",
            " 4   high_blood_pressure  299 non-null    bool   \n",
            " 5   platelets            299 non-null    int64  \n",
            " 6   serum_creatinine     299 non-null    float64\n",
            " 7   serum_sodium         299 non-null    int64  \n",
            " 8   sex                  299 non-null    object \n",
            " 9   smoking              299 non-null    bool   \n",
            " 10  patient_dead         299 non-null    bool   \n",
            "dtypes: bool(5), float64(1), int64(4), object(1)\n",
            "memory usage: 15.6+ KB\n"
          ]
        }
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        "column_details_df=pd.read_html(\"https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-020-1023-5/tables/1 \")[0]\n",
        "column_details_df.drop('Range',inplace=True,axis=1,errors='ignore')\n",
        "column_details_df.drop([3,4,7,13],inplace=True,axis=0,errors='ignore')\n",
        "column_details_df.columns=['feature','explanation','measurement_unit']\n",
        "column_details_df"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "eB5H_tu-5R0D",
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              "                 feature                                      explanation  \\\n",
              "0                    Age                               Age of the patient   \n",
              "1                Anaemia        Decrease of red blood cells or hemoglobin   \n",
              "2    High blood pressure                    If a patient has hypertension   \n",
              "5               Diabetes                      If the patient has diabetes   \n",
              "6      Ejection fraction                      Percentage of blood leaving   \n",
              "8                    Sex                                     Woman or man   \n",
              "9              Platelets                           Platelets in the blood   \n",
              "10      Serum creatinine                 Level of creatinine in the blood   \n",
              "11          Serum sodium                     Level of sodium in the blood   \n",
              "12               Smoking                            If the patient smokes   \n",
              "14  (target) death event  If the patient died during the follow-up period   \n",
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              "    measurement_unit  \n",
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              "6         Percentage  \n",
              "8             Binary  \n",
              "9   kiloplatelets/mL  \n",
              "10             mg/dL  \n",
              "11             mEq/L  \n",
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              "      <th>5</th>\n",
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              "      <th>6</th>\n",
              "      <td>Ejection fraction</td>\n",
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              "      <td>Percentage</td>\n",
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        "column_details_df=column_details_df.reindex([0,1,5,6,2,9,10,11,8,12,14])\n",
        "column_details_df.feature=heart_failure_df.columns\n",
        "column_details_df.set_index(['feature'], inplace =True)\n",
        "column_details_df"
      ],
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              "                                                         explanation  \\\n",
              "feature                                                                \n",
              "age                                               Age of the patient   \n",
              "anaemia                    Decrease of red blood cells or hemoglobin   \n",
              "diabetes                                 If the patient has diabetes   \n",
              "ejection_fraction                        Percentage of blood leaving   \n",
              "high_blood_pressure                    If a patient has hypertension   \n",
              "platelets                                     Platelets in the blood   \n",
              "serum_creatinine                    Level of creatinine in the blood   \n",
              "serum_sodium                            Level of sodium in the blood   \n",
              "sex                                                     Woman or man   \n",
              "smoking                                        If the patient smokes   \n",
              "patient_dead         If the patient died during the follow-up period   \n",
              "\n",
              "                     measurement_unit  \n",
              "feature                                \n",
              "age                             Years  \n",
              "anaemia                       Boolean  \n",
              "diabetes                      Boolean  \n",
              "ejection_fraction          Percentage  \n",
              "high_blood_pressure           Boolean  \n",
              "platelets            kiloplatelets/mL  \n",
              "serum_creatinine                mg/dL  \n",
              "serum_sodium                    mEq/L  \n",
              "sex                            Binary  \n",
              "smoking                       Boolean  \n",
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        "column_details_df[\"normal_value\"] = ['None',\n",
        "                                     'None',\n",
        "                                     'None',\n",
        "                                     '55% - 70%',\n",
        "                                     'None',\n",
        "                                     '150 - 400 kilo-platelets / mcL',\n",
        "                                     '0.6 - 1.2 mg/dL',\n",
        "                                     '135 - 145 mEq /L',\n",
        "                                     'None', 'None', 'None'\n",
        "                                    ]\n",
        "column_details_df"
      ],
      "metadata": {
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          "height": 539
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        "id": "9Sjqd10q-21K",
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              "                                                         explanation  \\\n",
              "feature                                                                \n",
              "age                                               Age of the patient   \n",
              "anaemia                    Decrease of red blood cells or hemoglobin   \n",
              "diabetes                                 If the patient has diabetes   \n",
              "ejection_fraction                        Percentage of blood leaving   \n",
              "high_blood_pressure                    If a patient has hypertension   \n",
              "platelets                                     Platelets in the blood   \n",
              "serum_creatinine                    Level of creatinine in the blood   \n",
              "serum_sodium                            Level of sodium in the blood   \n",
              "sex                                                     Woman or man   \n",
              "smoking                                        If the patient smokes   \n",
              "patient_dead         If the patient died during the follow-up period   \n",
              "\n",
              "                     measurement_unit                    normal_value  \n",
              "feature                                                                \n",
              "age                             Years                            None  \n",
              "anaemia                       Boolean                            None  \n",
              "diabetes                      Boolean                            None  \n",
              "ejection_fraction          Percentage                       55% - 70%  \n",
              "high_blood_pressure           Boolean                            None  \n",
              "platelets            kiloplatelets/mL  150 - 400 kilo-platelets / mcL  \n",
              "serum_creatinine                mg/dL                 0.6 - 1.2 mg/dL  \n",
              "serum_sodium                    mEq/L                135 - 145 mEq /L  \n",
              "sex                            Binary                            None  \n",
              "smoking                       Boolean                            None  \n",
              "patient_dead                  Boolean                            None  "
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              "    <tr>\n",
              "      <th>age</th>\n",
              "      <td>Age of the patient</td>\n",
              "      <td>Years</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>anaemia</th>\n",
              "      <td>Decrease of red blood cells or hemoglobin</td>\n",
              "      <td>Boolean</td>\n",
              "      <td>None</td>\n",
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              "    <tr>\n",
              "      <th>diabetes</th>\n",
              "      <td>If the patient has diabetes</td>\n",
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              "    <tr>\n",
              "      <th>ejection_fraction</th>\n",
              "      <td>Percentage of blood leaving</td>\n",
              "      <td>Percentage</td>\n",
              "      <td>55% - 70%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>high_blood_pressure</th>\n",
              "      <td>If a patient has hypertension</td>\n",
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              "      <th>platelets</th>\n",
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              "      <th>serum_creatinine</th>\n",
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              "      <th>serum_sodium</th>\n",
              "      <td>Level of sodium in the blood</td>\n",
              "      <td>mEq/L</td>\n",
              "      <td>135 - 145 mEq /L</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
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              "      <td>None</td>\n",
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              "    <tr>\n",
              "      <th>smoking</th>\n",
              "      <td>If the patient smokes</td>\n",
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              "      <td>None</td>\n",
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              "    <tr>\n",
              "      <th>patient_dead</th>\n",
              "      <td>If the patient died during the follow-up period</td>\n",
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Index: 11 entries, age to patient_dead\n",
            "Data columns (total 3 columns):\n",
            " #   Column            Non-Null Count  Dtype \n",
            "---  ------            --------------  ----- \n",
            " 0   explanation       11 non-null     object\n",
            " 1   measurement_unit  11 non-null     object\n",
            " 2   normal_value      11 non-null     object\n",
            "dtypes: object(3)\n",
            "memory usage: 352.0+ bytes\n"
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 299 entries, 0 to 298\n",
            "Data columns (total 11 columns):\n",
            " #   Column               Non-Null Count  Dtype  \n",
            "---  ------               --------------  -----  \n",
            " 0   age                  299 non-null    int64  \n",
            " 1   anaemia              299 non-null    bool   \n",
            " 2   diabetes             299 non-null    bool   \n",
            " 3   ejection_fraction    299 non-null    int64  \n",
            " 4   high_blood_pressure  299 non-null    bool   \n",
            " 5   platelets            299 non-null    int64  \n",
            " 6   serum_creatinine     299 non-null    float64\n",
            " 7   serum_sodium         299 non-null    int64  \n",
            " 8   sex                  299 non-null    object \n",
            " 9   smoking              299 non-null    bool   \n",
            " 10  patient_dead         299 non-null    bool   \n",
            "dtypes: bool(5), float64(1), int64(4), object(1)\n",
            "memory usage: 15.6+ KB\n"
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              "              age  ejection_fraction   platelets  serum_creatinine  \\\n",
              "count  299.000000         299.000000  299.000000         299.00000   \n",
              "mean    60.829431          38.083612  263.327759           1.39388   \n",
              "std     11.894997          11.834841   97.805105           1.03451   \n",
              "min     40.000000          14.000000   25.000000           0.50000   \n",
              "25%     51.000000          30.000000  212.500000           0.90000   \n",
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              "75%     70.000000          45.000000  303.500000           1.40000   \n",
              "max     95.000000          80.000000  850.000000           9.40000   \n",
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              "       serum_sodium  \n",
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              "std        4.412477  \n",
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    {
      "cell_type": "code",
      "source": [
        "#Number of Male and Female\n",
        "heart_failure_df.sex.value_counts()"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
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      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Male      194\n",
              "Female    105\n",
              "Name: sex, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Number of patients with anaemia\n",
        "heart_failure_df.anaemia.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XAm8I_dk_iUT",
        "outputId": "ed6664a7-cfa6-46cb-9094-0f9d6b3e52ba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False    170\n",
              "True     129\n",
              "Name: anaemia, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Number of patients with diabetes\n",
        "heart_failure_df.diabetes.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ipOLYbx7_w8S",
        "outputId": "3af9b7a6-2364-493d-dbb5-db7f29d92607"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False    174\n",
              "True     125\n",
              "Name: diabetes, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Number of patients with high BP\n",
        "heart_failure_df.high_blood_pressure.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bwEG2Imk_-vC",
        "outputId": "fecce569-4aeb-466c-f754-66d2a04063dc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False    194\n",
              "True     105\n",
              "Name: high_blood_pressure, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Number of patients with smoking habit\n",
        "heart_failure_df.smoking.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "myH6fSDYAP2v",
        "outputId": "21d60020-3a82-4aaa-c2f9-0f7612223498"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False    203\n",
              "True      96\n",
              "Name: smoking, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Number of patients died during follow-up period\n",
        "heart_failure_df.groupby(['patient_dead','sex']).size().reset_index().pivot(columns='patient_dead',index='sex',values=0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "3dz1mvWSAVeN",
        "outputId": "572d75a1-d739-4b1e-ae1c-12889febc096"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "patient_dead  False  True \n",
              "sex                       \n",
              "Female           71     34\n",
              "Male            132     62"
            ],
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              "\n",
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              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
            ]
          },
          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Number of patients with abnormal ejection fraction\n",
        "column_details_df.normal_value['ejection_fraction']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "FvIzut6GA7Yt",
        "outputId": "2c285deb-9d01-4588-840c-9b2c557c6c6d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'55% - 70%'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "abn_ef=heart_failure_df[(heart_failure_df.ejection_fraction < 55)| (heart_failure_df.ejection_fraction>70)]\n",
        "abn_ef"
      ],
      "metadata": {
        "colab": {
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          "height": 487
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        "id": "1iwd2QBqpGTk",
        "outputId": "a4567ca1-0d09-401b-e141-960c632f7ec1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     age  anaemia  diabetes  ejection_fraction  high_blood_pressure  \\\n",
              "0     75    False     False                 20                 True   \n",
              "1     55    False     False                 38                False   \n",
              "2     65    False     False                 20                False   \n",
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              "297   45    False     False                 38                False   \n",
              "298   50    False     False                 45                False   \n",
              "\n",
              "     platelets  serum_creatinine  serum_sodium     sex  smoking  patient_dead  \n",
              "0          265               1.9           130    Male    False          True  \n",
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              "3          210               1.9           137    Male    False          True  \n",
              "4          327               2.7           116  Female    False          True  \n",
              "..         ...               ...           ...     ...      ...           ...  \n",
              "293        179               0.9           136    Male     True         False  \n",
              "294        155               1.1           143    Male     True         False  \n",
              "295        270               1.2           139  Female    False         False  \n",
              "297        140               1.4           140    Male     True         False  \n",
              "298        395               1.6           136    Male     True         False  \n",
              "\n",
              "[261 rows x 11 columns]"
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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",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-41f6e81e-1d69-4372-9272-0ef46eb300bd 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-41f6e81e-1d69-4372-9272-0ef46eb300bd');\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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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Number of patients with abnormal platelets count\n",
        "column_details_df.normal_value['platelets']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "t7LtnZSxpk42",
        "outputId": "0750e5c1-5e17-4d1f-d8ee-d23dc42ea393"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'150 - 400 kilo-platelets / mcL'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "abn_platelets=heart_failure_df[(heart_failure_df.platelets < 150)| (heart_failure_df.platelets>400)]\n",
        "abn_platelets"
      ],
      "metadata": {
        "outputId": "d6a6deec-b292-425d-a4ef-3d2cb44a30a5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "wepyJZQWp5gL"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     age  anaemia  diabetes  ejection_fraction  high_blood_pressure  \\\n",
              "6     75     True     False                 15                False   \n",
              "7     60     True      True                 60                False   \n",
              "12    45     True     False                 30                False   \n",
              "14    49     True     False                 30                 True   \n",
              "15    82     True     False                 50                False   \n",
              "19    48     True      True                 55                False   \n",
              "25    80    False      True                 38                False   \n",
              "47    60    False      True                 38                 True   \n",
              "48    80     True     False                 20                 True   \n",
              "51    53     True     False                 20                 True   \n",
              "55    95     True     False                 30                False   \n",
              "65    60    False     False                 20                False   \n",
              "69    65    False      True                 25                False   \n",
              "71    58    False      True                 35                False   \n",
              "73    65    False      True                 50                False   \n",
              "85    51    False     False                 50                False   \n",
              "102   80    False     False                 25                False   \n",
              "105   72     True     False                 30                 True   \n",
              "109   45    False      True                 35                False   \n",
              "117   85     True     False                 60                False   \n",
              "123   60     True     False                 30                 True   \n",
              "162   63     True     False                 40                False   \n",
              "163   50     True      True                 35                False   \n",
              "167   59    False      True                 20                False   \n",
              "176   69    False     False                 40                False   \n",
              "177   49     True     False                 50                False   \n",
              "194   45    False     False                 20                 True   \n",
              "200   63     True     False                 45                False   \n",
              "211   50    False     False                 62                 True   \n",
              "212   78    False     False                 50                False   \n",
              "223   47    False     False                 25                False   \n",
              "224   58    False      True                 25                False   \n",
              "227   55     True     False                 35                 True   \n",
              "230   60    False     False                 30                False   \n",
              "235   77     True     False                 50                 True   \n",
              "240   70    False      True                 35                 True   \n",
              "250   50    False     False                 30                 True   \n",
              "264   61    False      True                 38                False   \n",
              "267   56     True      True                 38                False   \n",
              "275   45    False     False                 38                 True   \n",
              "277   70    False      True                 38                False   \n",
              "279   55    False      True                 38                False   \n",
              "281   70    False     False                 40                False   \n",
              "287   45    False      True                 55                False   \n",
              "291   60    False     False                 35                False   \n",
              "296   45    False      True                 60                False   \n",
              "297   45    False     False                 38                False   \n",
              "\n",
              "     platelets  serum_creatinine  serum_sodium     sex  smoking  patient_dead  \n",
              "6          127              1.20           137    Male    False          True  \n",
              "7          454              1.10           131    Male     True          True  \n",
              "12         136              1.10           137    Male    False          True  \n",
              "14         427              1.00           138  Female    False         False  \n",
              "15          47              1.30           136    Male    False          True  \n",
              "19          87              1.90           121  Female    False          True  \n",
              "25         149              1.90           144    Male     True          True  \n",
              "47         451              0.60           138    Male     True          True  \n",
              "48         140              4.40           133    Male    False          True  \n",
              "51         418              1.40           139  Female    False          True  \n",
              "55         461              2.00           132    Male    False          True  \n",
              "65         119              2.90           127    Male     True          True  \n",
              "69         497              1.83           135    Male    False          True  \n",
              "71         122              0.90           139    Male     True         False  \n",
              "73         149              1.30           137    Male     True         False  \n",
              "85         406              0.70           140    Male    False         False  \n",
              "102        149              1.10           144    Male     True         False  \n",
              "105        621              1.70           138  Female     True          True  \n",
              "109        850              1.30           142    Male     True         False  \n",
              "117        507              3.20           138  Female    False         False  \n",
              "123        127              0.90           145  Female    False         False  \n",
              "162        448              0.90           137    Male     True         False  \n",
              "163         75              0.90           142  Female    False          True  \n",
              "167         70              2.40           134    Male    False          True  \n",
              "176        105              1.00           135    Male     True         False  \n",
              "177        132              1.00           140  Female    False         False  \n",
              "194        126              1.60           135    Male    False          True  \n",
              "200         73              0.70           137    Male    False         False  \n",
              "211        147              0.80           140    Male     True         False  \n",
              "212        481              1.40           138    Male     True         False  \n",
              "223        130              0.80           134    Male    False         False  \n",
              "224        504              1.00           138    Male    False         False  \n",
              "227        141              1.00           140    Male    False         False  \n",
              "230         62              1.70           127  Female    False          True  \n",
              "235        406              1.10           137    Male    False         False  \n",
              "240        533              1.30           139  Female    False         False  \n",
              "250        404              0.50           139  Female    False         False  \n",
              "264        147              1.20           141    Male    False         False  \n",
              "267        133              1.70           140    Male    False         False  \n",
              "275        422              0.80           137  Female    False         False  \n",
              "277         25              1.10           140    Male    False         False  \n",
              "279        451              1.30           136  Female    False         False  \n",
              "281         51              2.70           136    Male     True         False  \n",
              "287        543              1.00           132  Female    False         False  \n",
              "291        133              1.40           139    Male    False         False  \n",
              "296        742              0.80           138  Female    False         False  \n",
              "297        140              1.40           140    Male     True         False  "
            ],
            "text/html": [
              "\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>age</th>\n",
              "      <th>anaemia</th>\n",
              "      <th>diabetes</th>\n",
              "      <th>ejection_fraction</th>\n",
              "      <th>high_blood_pressure</th>\n",
              "      <th>platelets</th>\n",
              "      <th>serum_creatinine</th>\n",
              "      <th>serum_sodium</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoking</th>\n",
              "      <th>patient_dead</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>6</th>\n",
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              "      <td>True</td>\n",
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              "      <td>15</td>\n",
              "      <td>False</td>\n",
              "      <td>127</td>\n",
              "      <td>1.20</td>\n",
              "      <td>137</td>\n",
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              "    </tr>\n",
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              "      <th>7</th>\n",
              "      <td>60</td>\n",
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              "      <td>60</td>\n",
              "      <td>False</td>\n",
              "      <td>454</td>\n",
              "      <td>1.10</td>\n",
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              "      <th>12</th>\n",
              "      <td>45</td>\n",
              "      <td>True</td>\n",
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              "      <td>30</td>\n",
              "      <td>False</td>\n",
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              "      <td>True</td>\n",
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              "      <th>14</th>\n",
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              "      <td>True</td>\n",
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              "      <td>30</td>\n",
              "      <td>True</td>\n",
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              "      <td>1.00</td>\n",
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              "      <th>19</th>\n",
              "      <td>48</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>55</td>\n",
              "      <td>False</td>\n",
              "      <td>87</td>\n",
              "      <td>1.90</td>\n",
              "      <td>121</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
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              "      <th>25</th>\n",
              "      <td>80</td>\n",
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              "      <td>True</td>\n",
              "      <td>38</td>\n",
              "      <td>False</td>\n",
              "      <td>149</td>\n",
              "      <td>1.90</td>\n",
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              "      <td>True</td>\n",
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              "      <th>47</th>\n",
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              "      <td>38</td>\n",
              "      <td>True</td>\n",
              "      <td>451</td>\n",
              "      <td>0.60</td>\n",
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              "      <th>48</th>\n",
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              "      <td>True</td>\n",
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              "      <td>True</td>\n",
              "      <td>140</td>\n",
              "      <td>4.40</td>\n",
              "      <td>133</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
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              "      <th>51</th>\n",
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              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>20</td>\n",
              "      <td>True</td>\n",
              "      <td>418</td>\n",
              "      <td>1.40</td>\n",
              "      <td>139</td>\n",
              "      <td>Female</td>\n",
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              "      <th>55</th>\n",
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              "      <td>True</td>\n",
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              "      <td>30</td>\n",
              "      <td>False</td>\n",
              "      <td>461</td>\n",
              "      <td>2.00</td>\n",
              "      <td>132</td>\n",
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              "      <th>65</th>\n",
              "      <td>60</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>20</td>\n",
              "      <td>False</td>\n",
              "      <td>119</td>\n",
              "      <td>2.90</td>\n",
              "      <td>127</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
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              "      <th>69</th>\n",
              "      <td>65</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>25</td>\n",
              "      <td>False</td>\n",
              "      <td>497</td>\n",
              "      <td>1.83</td>\n",
              "      <td>135</td>\n",
              "      <td>Male</td>\n",
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              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>35</td>\n",
              "      <td>False</td>\n",
              "      <td>122</td>\n",
              "      <td>0.90</td>\n",
              "      <td>139</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
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              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>65</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>50</td>\n",
              "      <td>False</td>\n",
              "      <td>149</td>\n",
              "      <td>1.30</td>\n",
              "      <td>137</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
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              "    <tr>\n",
              "      <th>85</th>\n",
              "      <td>51</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>50</td>\n",
              "      <td>False</td>\n",
              "      <td>406</td>\n",
              "      <td>0.70</td>\n",
              "      <td>140</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>102</th>\n",
              "      <td>80</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>25</td>\n",
              "      <td>False</td>\n",
              "      <td>149</td>\n",
              "      <td>1.10</td>\n",
              "      <td>144</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>72</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>30</td>\n",
              "      <td>True</td>\n",
              "      <td>621</td>\n",
              "      <td>1.70</td>\n",
              "      <td>138</td>\n",
              "      <td>Female</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>35</td>\n",
              "      <td>False</td>\n",
              "      <td>850</td>\n",
              "      <td>1.30</td>\n",
              "      <td>142</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>85</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>60</td>\n",
              "      <td>False</td>\n",
              "      <td>507</td>\n",
              "      <td>3.20</td>\n",
              "      <td>138</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>60</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>30</td>\n",
              "      <td>True</td>\n",
              "      <td>127</td>\n",
              "      <td>0.90</td>\n",
              "      <td>145</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>63</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>40</td>\n",
              "      <td>False</td>\n",
              "      <td>448</td>\n",
              "      <td>0.90</td>\n",
              "      <td>137</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>163</th>\n",
              "      <td>50</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>35</td>\n",
              "      <td>False</td>\n",
              "      <td>75</td>\n",
              "      <td>0.90</td>\n",
              "      <td>142</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>167</th>\n",
              "      <td>59</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>20</td>\n",
              "      <td>False</td>\n",
              "      <td>70</td>\n",
              "      <td>2.40</td>\n",
              "      <td>134</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>176</th>\n",
              "      <td>69</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>40</td>\n",
              "      <td>False</td>\n",
              "      <td>105</td>\n",
              "      <td>1.00</td>\n",
              "      <td>135</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>49</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>50</td>\n",
              "      <td>False</td>\n",
              "      <td>132</td>\n",
              "      <td>1.00</td>\n",
              "      <td>140</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>194</th>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>20</td>\n",
              "      <td>True</td>\n",
              "      <td>126</td>\n",
              "      <td>1.60</td>\n",
              "      <td>135</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
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              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>63</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>73</td>\n",
              "      <td>0.70</td>\n",
              "      <td>137</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "      <th>211</th>\n",
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              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>62</td>\n",
              "      <td>True</td>\n",
              "      <td>147</td>\n",
              "      <td>0.80</td>\n",
              "      <td>140</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
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              "      <th>212</th>\n",
              "      <td>78</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>50</td>\n",
              "      <td>False</td>\n",
              "      <td>481</td>\n",
              "      <td>1.40</td>\n",
              "      <td>138</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
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              "    <tr>\n",
              "      <th>223</th>\n",
              "      <td>47</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>25</td>\n",
              "      <td>False</td>\n",
              "      <td>130</td>\n",
              "      <td>0.80</td>\n",
              "      <td>134</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>224</th>\n",
              "      <td>58</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>25</td>\n",
              "      <td>False</td>\n",
              "      <td>504</td>\n",
              "      <td>1.00</td>\n",
              "      <td>138</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>227</th>\n",
              "      <td>55</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>35</td>\n",
              "      <td>True</td>\n",
              "      <td>141</td>\n",
              "      <td>1.00</td>\n",
              "      <td>140</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>230</th>\n",
              "      <td>60</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>30</td>\n",
              "      <td>False</td>\n",
              "      <td>62</td>\n",
              "      <td>1.70</td>\n",
              "      <td>127</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>235</th>\n",
              "      <td>77</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>50</td>\n",
              "      <td>True</td>\n",
              "      <td>406</td>\n",
              "      <td>1.10</td>\n",
              "      <td>137</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>70</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>35</td>\n",
              "      <td>True</td>\n",
              "      <td>533</td>\n",
              "      <td>1.30</td>\n",
              "      <td>139</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "    <tr>\n",
              "      <th>250</th>\n",
              "      <td>50</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>30</td>\n",
              "      <td>True</td>\n",
              "      <td>404</td>\n",
              "      <td>0.50</td>\n",
              "      <td>139</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "      <th>264</th>\n",
              "      <td>61</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>38</td>\n",
              "      <td>False</td>\n",
              "      <td>147</td>\n",
              "      <td>1.20</td>\n",
              "      <td>141</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "      <th>267</th>\n",
              "      <td>56</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>38</td>\n",
              "      <td>False</td>\n",
              "      <td>133</td>\n",
              "      <td>1.70</td>\n",
              "      <td>140</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "      <th>275</th>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>38</td>\n",
              "      <td>True</td>\n",
              "      <td>422</td>\n",
              "      <td>0.80</td>\n",
              "      <td>137</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "      <th>277</th>\n",
              "      <td>70</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>38</td>\n",
              "      <td>False</td>\n",
              "      <td>25</td>\n",
              "      <td>1.10</td>\n",
              "      <td>140</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
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              "      <th>279</th>\n",
              "      <td>55</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>38</td>\n",
              "      <td>False</td>\n",
              "      <td>451</td>\n",
              "      <td>1.30</td>\n",
              "      <td>136</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "      <th>281</th>\n",
              "      <td>70</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>40</td>\n",
              "      <td>False</td>\n",
              "      <td>51</td>\n",
              "      <td>2.70</td>\n",
              "      <td>136</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
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              "      <th>287</th>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>55</td>\n",
              "      <td>False</td>\n",
              "      <td>543</td>\n",
              "      <td>1.00</td>\n",
              "      <td>132</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "    <tr>\n",
              "      <th>291</th>\n",
              "      <td>60</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>35</td>\n",
              "      <td>False</td>\n",
              "      <td>133</td>\n",
              "      <td>1.40</td>\n",
              "      <td>139</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "    <tr>\n",
              "      <th>296</th>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>60</td>\n",
              "      <td>False</td>\n",
              "      <td>742</td>\n",
              "      <td>0.80</td>\n",
              "      <td>138</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>297</th>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>38</td>\n",
              "      <td>False</td>\n",
              "      <td>140</td>\n",
              "      <td>1.40</td>\n",
              "      <td>140</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
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              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-16deee08-1570-4ac0-8e1d-89a73fa228b9')\"\n",
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            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#to find the normal value of creatinine level in the blood\n",
        "column_details_df.normal_value['serum_creatinine']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "p0hImgkqqRuS",
        "outputId": "0fb8248e-8822-4d3c-a018-3d9533999bc6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'0.6 - 1.2 mg/dL'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "abn_creatinine=heart_failure_df[(heart_failure_df.serum_creatinine < 0.6)| (heart_failure_df.serum_creatinine>1.2)]\n",
        "abn_creatinine"
      ],
      "metadata": {
        "outputId": "62a5fb2b-5522-4a7a-e35b-57e39e2dd0e3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "m34UQzDqqTM9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     age  anaemia  diabetes  ejection_fraction  high_blood_pressure  \\\n",
              "0     75    False     False                 20                 True   \n",
              "2     65    False     False                 20                False   \n",
              "3     50     True     False                 20                False   \n",
              "4     65     True      True                 20                False   \n",
              "5     90     True     False                 40                 True   \n",
              "..   ...      ...       ...                ...                  ...   \n",
              "282   42    False     False                 30                False   \n",
              "286   60    False     False                 35                False   \n",
              "291   60    False     False                 35                False   \n",
              "297   45    False     False                 38                False   \n",
              "298   50    False     False                 45                False   \n",
              "\n",
              "     platelets  serum_creatinine  serum_sodium     sex  smoking  patient_dead  \n",
              "0          265               1.9           130    Male    False          True  \n",
              "2          162               1.3           129    Male     True          True  \n",
              "3          210               1.9           137    Male    False          True  \n",
              "4          327               2.7           116  Female    False          True  \n",
              "5          204               2.1           132    Male     True          True  \n",
              "..         ...               ...           ...     ...      ...           ...  \n",
              "282        215               3.8           128    Male     True         False  \n",
              "286        279               1.7           140    Male    False         False  \n",
              "291        133               1.4           139    Male    False         False  \n",
              "297        140               1.4           140    Male     True         False  \n",
              "298        395               1.6           136    Male     True         False  \n",
              "\n",
              "[102 rows x 11 columns]"
            ],
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              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>65</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
              "      <td>20</td>\n",
              "      <td>False</td>\n",
              "      <td>327</td>\n",
              "      <td>2.7</td>\n",
              "      <td>116</td>\n",
              "      <td>Female</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>90</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>40</td>\n",
              "      <td>True</td>\n",
              "      <td>204</td>\n",
              "      <td>2.1</td>\n",
              "      <td>132</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>True</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>282</th>\n",
              "      <td>42</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>30</td>\n",
              "      <td>False</td>\n",
              "      <td>215</td>\n",
              "      <td>3.8</td>\n",
              "      <td>128</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>286</th>\n",
              "      <td>60</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>35</td>\n",
              "      <td>False</td>\n",
              "      <td>279</td>\n",
              "      <td>1.7</td>\n",
              "      <td>140</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>291</th>\n",
              "      <td>60</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>35</td>\n",
              "      <td>False</td>\n",
              "      <td>133</td>\n",
              "      <td>1.4</td>\n",
              "      <td>139</td>\n",
              "      <td>Male</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>297</th>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>38</td>\n",
              "      <td>False</td>\n",
              "      <td>140</td>\n",
              "      <td>1.4</td>\n",
              "      <td>140</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
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              "    <tr>\n",
              "      <th>298</th>\n",
              "      <td>50</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>45</td>\n",
              "      <td>False</td>\n",
              "      <td>395</td>\n",
              "      <td>1.6</td>\n",
              "      <td>136</td>\n",
              "      <td>Male</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>102 rows × 11 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1a7b5da0-5739-4b5a-8c71-740a950cb201')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\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",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\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-1a7b5da0-5739-4b5a-8c71-740a950cb201 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-1a7b5da0-5739-4b5a-8c71-740a950cb201');\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",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#to find the normal value of sodium level in the blood\n",
        "column_details_df.normal_value['serum_sodium']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "wImnAlL9qwLJ",
        "outputId": "b2f51c94-8997-4ec7-821d-a6d42271e38c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'135 - 145 mEq /L'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "abn_sodium=heart_failure_df[(heart_failure_df.serum_sodium < 135)| (heart_failure_df.serum_sodium>145)]\n",
        "abn_sodium"
      ],
      "metadata": {
        "outputId": "7e0811ea-0b4e-4bf4-e8ff-b8fce834923a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "-f8NLq8yq4AO"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     age  anaemia  diabetes  ejection_fraction  high_blood_pressure  \\\n",
              "0     75    False     False                 20                 True   \n",
              "2     65    False     False                 20                False   \n",
              "4     65     True      True                 20                False   \n",
              "5     90     True     False                 40                 True   \n",
              "7     60     True      True                 60                False   \n",
              "..   ...      ...       ...                ...                  ...   \n",
              "270   44    False      True                 30                 True   \n",
              "271   51    False      True                 40                False   \n",
              "272   67    False     False                 38                False   \n",
              "282   42    False     False                 30                False   \n",
              "287   45    False      True                 55                False   \n",
              "\n",
              "     platelets  serum_creatinine  serum_sodium     sex  smoking  patient_dead  \n",
              "0          265               1.9           130    Male    False          True  \n",
              "2          162               1.3           129    Male     True          True  \n",
              "4          327               2.7           116  Female    False          True  \n",
              "5          204               2.1           132    Male     True          True  \n",
              "7          454               1.1           131    Male     True          True  \n",
              "..         ...               ...           ...     ...      ...           ...  \n",
              "270        263               1.6           130    Male     True         False  \n",
              "271        221               0.9           134  Female    False         False  \n",
              "272        215               1.2           133  Female    False         False  \n",
              "282        215               3.8           128    Male     True         False  \n",
              "287        543               1.0           132  Female    False         False  \n",
              "\n",
              "[85 rows x 11 columns]"
            ],
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              "<p>85 rows × 11 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7498c78f-402b-48fc-b7ff-87c8516ba57d')\"\n",
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              "          const element = document.querySelector('#df-7498c78f-402b-48fc-b7ff-87c8516ba57d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "heart_failure_df.sample(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 270
        },
        "id": "qqxClCMLrOCn",
        "outputId": "1458a553-2c52-4d6c-9123-1d0f0e404a84"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     age  anaemia  diabetes  ejection_fraction  high_blood_pressure  \\\n",
              "128   61    False     False                 30                 True   \n",
              "97    70     True     False                 60                False   \n",
              "56    70     True     False                 35                False   \n",
              "104   60    False     False                 50                 True   \n",
              "182   65    False      True                 25                False   \n",
              "\n",
              "     platelets  serum_creatinine  serum_sodium     sex  smoking  patient_dead  \n",
              "128        267               0.7           136    Male     True         False  \n",
              "97         255               1.1           136  Female    False         False  \n",
              "56         223               2.7           138    Male     True         False  \n",
              "104        286               2.3           143  Female    False         False  \n",
              "182        265               1.2           136    Male     True          True  "
            ],
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              "    .colab-df-convert:hover {\n",
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              "\n",
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              "\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c80f3d71-80e5-4e55-bf2c-001e9f510174 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c80f3d71-80e5-4e55-bf2c-001e9f510174');\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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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib as mp\n",
        "import matplotlib.patches as mpatches\n",
        "%matplotlib inline\n",
        "sns.set_style('darkgrid')\n",
        "mp.rcParams['font.size']=14\n",
        "mp.rcParams['figure.figsize']=(9,5)\n",
        "mp.rcParams['figure.facecolor']='white'"
      ],
      "metadata": {
        "id": "nZJzX9VDrip5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.hist(heart_failure_df.age, bins=np.arange(40,100,5),color= 'mediumpurple')\n",
        "plt.xlabel(\"Age of Patients (Years)\")\n",
        "plt.ylabel(\"Number of Patients\")\n",
        "plt.title(\"Distribution of Age\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 420
        },
        "id": "uCEz9s5D8f4e",
        "outputId": "501f74dd-ac81-4674-fa9d-2cdd2bbcce83"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#to store the gender counts into a variable\n",
        "gender_counts=heart_failure_df.sex.value_counts()\n",
        "plt.figure(figsize=(12,6))\n",
        "plt.pie(gender_counts,labels=gender_counts.index,autopct='%.1f%%', startangle=90, explode=[0.1,0], colors=['lightskyblue','plum'])\n",
        "plt.title(\"Gender Distribution (Male or Female)\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 525
        },
        "id": "qMuBGGpC9Hi9",
        "outputId": "e4a1e488-fdc1-4f65-98db-d80ec72418a1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#count number of patients dead\n",
        "dead_counts= heart_failure_df.patient_dead.value_counts()\n",
        "dead_counts"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "69UzKLRQ9_Sd",
        "outputId": "330480d3-92c0-474b-cd58-7097cd073bd6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False    203\n",
              "True      96\n",
              "Name: patient_dead, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "plt.pie(dead_counts,labels=['Alive','Dead'],autopct='%.3f%%', startangle=90, explode=[0.1,0], colors=['aquamarine','lightcoral'])\n",
        "plt.title(\"% of Patients Dead & Alive\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 525
        },
        "id": "eubpGgEV-Ogm",
        "outputId": "59ff96c4-75df-493d-f97b-799ede164d90"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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PHs0dd9zhXWsFOHHiBL/4xS/OGrz5+fnNVt/evXsBsNvt/PznP6/3cUeOHAHg+PHjdd7fs2fPOm/3jGhP33XfEPfccw+rV69m1qxZzJ07l3HjxjFs2DBGjBhBnz59Gn28xvLUfOpo3fP1Ki8v56c//Wm9z/V8j44fP+79cOJ0OnnyySe9o7WzPdfDM3PgWVc+XVBQEL169Wr0entlZSVPPfUUbrebP/7xjyQkJPCrX/0Kp9PJ66+/zr333susWbNqbEjzfDg8//zzG/VaS5cuJTc3l9DQUK666qoa9/Xv35/zzjuPPXv28PnnnzdbF6/rr7+eLVu2MHfu3BofzDdt2kRaWhpRUVG1Plx5vr8fffSRN7xP51kLr+/fgpw7BbMFZGRkMHPmTC6++GLvtO7rr7+O0+nkxRdf9O7Qbdu2LU8//TTvvfceTz311FmP69msZLfbzzjl6dkZ3pTwOJvG7OJ+4okn2L17N927d+eRRx5h2LBhxMfHe6eWH3vsMebNm4fT6Wy2+jxLBKd/gKiP5xSy09W3M9ozzWucttGtIS688ELee+89Xn/9ddavX8+cOXO87VD79u3L9OnTa+2ob06eJhinjlILCwuBql/Ojf16vf3228ybN4+wsDD+53/+h/Hjx9O5c2ciIiKw2WzMnj2bp556qtb31/NzWddo2eNM99Vn2bJlZGdn07179xo7oh955BGcTidvvfUWP//5z5k1axajRo3C5XKxcuVK7HZ7vbMF9fFMU19yySV1Ngu6/vrr2bNnD/Pnz+c3v/lNszTBueqqq/jTn/7E3r172bdvn3f3v+eD0ZQpUwgPD6/xHM/3d//+/Wc9fn3/FuTcKZgt4A9/+AMAzzzzjPe2zZs3ExER4Q1lgEsvvdR7X0N4Rjput5ucnJx6f3l5Rhqnr+22puzsbFauXAlUrYvXNcJvzpGyhydQu3TpwtKlS5v9+Odq9OjRjB49mrKyMrZu3cqmTZv49ttv2bdvH9OnT2fWrFlMnDix2V/X6XR611lP3e/g+XqNGjWKDz/8sFHH9HyoePzxx+uc+q/v++v5uaxrrdTjTPfVxzMLUlc7zN/+9re4XC7eeecd7rvvPt544w2OHz/OiRMnmDp1aqMa4pw4cYIVK1YAsGjRojp7Xnvk5OTwww8/NDr469KmTRsuvfRSFi5cyNy5c3n88ceprKz0LhmcPo0NVd/fwsJC3nvvPS644IJzrkGaRmvMJluwYAE//PAD06dPr7HR4tTzmj08f2/oaRWJiYkEB1d99qpv7aqgoMC7oak1pkfr47mwRGxsbJ2h7HQ62blzZ53PbUrHJA/PL8nMzMwWCf76NLbmiIgIxo4dy0MPPcS8efO8I+X6Ti86V1999RW5ubnAjx8IAe/Sw4EDBxq97u35Htd3rnJ9exx69+4NVPVur4vL5apxGmJDeT5k1HdRk9/97nfccccd3tO8/vznPxMZGcnDDz/cqNeZO3cuLpeLkJAQ4uPj6/3jqaclNoF9+eWXuFwuli5dSkFBAV27dq1z2crz/d23b1+z1SCNp2A2UVFREX/6058YMGAAd955Z4374uLiyM3NrXHurOcTfkNbJEZGRnr/8b3zzjt1Pua9997D5XIRFxfH4MGDm/Aumoenu1hxcTFlZWW17p87d26N3cGn8kzH1fW8s+nevTsDBw7E7XbX+zVqCedSs81mY/jw4QD17hI/FwcOHODZZ58FYPLkyfTv399734gRI+jQoQP5+fneXcYN5fke17UWnJKSUu+MxYQJE4CqjUl1/QwsWLCgSedze0aEGRkZ9a6nPv3000ybNo2ysjJyc3P56U9/2ujmGp6gveWWW1i1alW9fzy73VesWNFs56ePHz+e9u3bk52dzerVq2ucu1zXh8Mrr7wSqFpjbsrPpjQPBbOJXnjhBXJycvjDH/5Qqxf1mDFjcLvd/POf/wSqRgWvvvqq976G+uUvf4nNZmPZsmXMnDmzxmkl33zzDW+++SYA9913X63OVq2pb9++xMXF4XQ6+cMf/kBFRYX3voULF/LHP/6x3g5GiYmJ2Gw2cnNzvZtXGuN3v/sdwcHBvPHGG/z973/3rrN5VFRUsGzZMqZPn97oY9enITVPnz6db7/9ttYvyLS0ND777DOg8ZuQziQ9PZ1XXnmFm266iYKCAnr27Mkf//jHGo8JDQ31tqicMWMG7777bq21xpKSEhYtWlRrH4TnQ+KLL77IiRMnvLfv3buX+++/v1anMI8rr7yS7t27U1FRwSOPPFIjnLdu3cqzzz7bpDXZPn36eEeUTz31FO+9916N07ucTicLFixg1apV3ts++uijBi8lQVUXLs8H6htvvPGMj504cSLx8fE4nU6++OKLhr+RMwgODubqq68GqhoNeabU65rGBrjppptISkriyJEj/Pd//3edP5sHDhzgH//4R7N0AJS6aY3ZJFu2bOGTTz7hjjvuqPOX6wMPPMCSJUt4++23+fbbb3E4HGRlZZGQkMBdd93V4Ne54IILePzxx/nLX/7CK6+8wgcffEBiYiInTpzwjrauu+460y+XGBwczKOPPspTTz3FnDlz+O6770hMTOTkyZNkZWUxbtw42rVrV+fIJjY2losvvpilS5cybdo0+vXr511ff/LJJ+tsJ3mq0aNH89e//pWnnnqK119/nbfeeotevXoRFRVFQUEB6enp53SebF0aUvPq1atZtGgRwcHBdO/enTZt2lBQUEBqaiqGYdCzZ88mfVjwnMLmUVpaSnZ2tjfwbDYb11xzDf/7v/9LbGxsredPnTqV3Nxcnn/+eZ577jlefPFFevXqRVhYGHl5eaSnp+N2u2sszQA8/PDDrFmzhl27djFp0iR69epFZWUlhw8fpnPnzjz44IO8+OKLtV4vLCyMF198kbvvvpt169YxceJEkpKSKC0t5fDhwwwZMoTu3bvXaivZEDNmzKC0tJRvv/2WZ599ln/84x/06tULwzA4cuQIpaWlhIWF8cQTT7B3716++OILfvGLX/DBBx/UmEmoj2e0PGDAgLP+HAYHB3Pttdfy9ttvM2fOHO67775Gv5+6XH/99bz//vvePRzDhg2jR48edT42NDSUWbNm8cADD7B582auu+46OnfuTIcOHaisrCQjI8P7wfW5555rlvqkNgWzCRwOB8888wwdO3bk17/+dZ2P6dOnDx988AEvvPACW7duxW63c9lll/G73/2u0Vf7ufvuuxk2bBjvvPMOmzZtYu/evURFRXHRRRdx0003eXeCm23atGnExsby1ltvsWfPHg4fPkxiYiJ33XUXd911F08//XS9z/3LX/7Cyy+/zLJlyzhw4IA3SE8f/dbnqquuYvjw4XzwwQesXLmSo0ePUl5eTkxMDIMGDeKiiy7ytm5sLmer+S9/+QurVq1iy5YtZGVlcfToUcLDwxk0aBCXXXYZt99+e63GIw1x6g50u91OVFQUbdu25ZJLLmHw4MFMnTr1rNO1d911F+PGjePf//43a9euJS0tjcrKSmJjYxk5ciQTJkyotYEpOTmZTz75hJdeeokNGzZw+PBhOnbsyB133MGDDz54xs13gwcPZu7cubz00kusWrWKAwcO0LlzZ375y19y//33N/liL6GhocycOZOlS5fy+eefs23bNvbv3094eDi9evVi/Pjx3Hbbbd5gOnr0KBs3buTee+/l3//+d70BB1UfeDwbrc42WvaYNm0ab7/9NocPH2bTpk2MGDGiSe/rVAMHDiQpKcm707q+0bJH586d+fTTT5k/fz4LFixg9+7d7Nq1i9DQUDp16sTkyZOZNGlSvdeRl3NnM5pyHoeIiIi0CK0xi4iIWIiCWURExEIUzCIiIhaiYBYREbEQBbOIiIiFKJhFREQsRMEsIiJiIQpmERERC1Ewi4iIWIiCWURExEIUzCIiIhaiYBYREbEQBbOIiIiFKJhFREQsRMEsIiJiIQpmERERC1Ewi4iIWIiCWURExEIUzCIiIhaiYBYREbEQBbOIiIiFKJhFREQsRMEsIiJiIQpmERERC1Ewi4iIWIiCWURExEIUzCIiIhaiYBYREbEQBbOIiIiFKJhFREQsRMEsIiJiIQpmERERC1Ewi4iIWIiCWURExEIUzCIiIhaiYBYREbEQBbOIiIiFKJhFREQsRMEsIiJiIQpmERERC1Ewi4iIWIiCWURExEIUzCIiIhaiYBYREbEQBbOIiIiFKJhFREQsRMEsIiJiIQpmERERC1Ewi4iIWIiCWURExEIUzCIiIhaiYBYREbEQBbOIiIiFBJtdgIg0P6O8HMMwsNlsYLOB3Q52O7agoLofbxjgdv94g82Gza7P7SJmUDCL+KGSDz7AdexY7TuCgrCFh9f+ExHh/X+q/2tv0wZ7XBy2qKiqgOeUAFdwi7QYBbNIIHG5MEpKMEpKGv6coKAfQzo2FrvnT7t22OPisEdGeh9quFxVI/PqIBeRxlMwi8iZuVy48/Jw5+XVfX9wMPa4OII6diSoc2fvH1t4OFAd1hphizSYgllEzo3TiTs7G3d2No6dO70329q2JahTpx/DuksX7NHRgEbWImeiYBaRFmEUFOAsKMC5b5/3NltERFVIJyYS3Ls3QV27YrPbFdQip7AZhmGYXYSINK/iN9+se/OX1YSEEJyYSHCvXgT37o29UydsNhuGy1XvDnIRf6cRs4iYx+HAmZKCMyWl6u/h4QT36OEN6qCEhKqd4IahNWoJGApmEbGO8nKc+/Z5p79tkZEE9+tHyIABBPfpgy0oCMPtVkiLX1Mwi4hlGaWlOLZtw7FtG4SGEpKUVBXS/fphCw7WlLf4JQWzSDNxY+DGwIYNG2Cn7o1MTtxU4KYcF04MDAzc1c83gE6EE6JuubVVVuLYubNq53dICMF9+xIyYAAhycnYQkIU0uI3FMwiDeQJ0NNDtwQnuVSSRyWluCjDRflp/636fzdluHBx5v2WD9KXBMJa9s34OocD5549OPfsoSwoiOA+fQg57zxCBgyAkBCtSYtPUzCLnMaFUSN8XRjkU0kOld4ArvrjIJ9KHGcJWmlhLhfO/ftx7t9P2TffEDJoEKEjRxLcpYtG0eKTFMwS0E4NYQODXCo5ShnHKCOLcnKppBinotdXOBw4tmzBsWUL9g4dCB0xgtAhQ7CFhWnTmPgMBbMEDHd1vHpGwnlUcpRSjlHOMcrIpJxK3Gc6hPgQ94kTlC9YQPl33xEycGDVKLpbN42ixfIUzOK3Tg3iMlwcopiM6tHwccqpUAgHBqfTu7PbnpBA6PDhhA4dCmFV6/jqNiZWo2AWv+LCIAgbLgzSKOEgxaRQQhblmo4W3NnZlC9aRPmSJYQOGULY+PHY2rbVNLdYioJZfJoLAztgw8ZJKjhAESmUkEqJNmVJ/ZxOKjdtonLzZkIGDiRswoSqLmMKaLEABbP4HM+ouAwXB6uDOIViinCaXZr4GsPwnhsd3K8fYRMmaB1aTKdgFp/gCeMKXOyikJ0UcIQSrRJLs3EeOIDzwAGCEhMJGz+ekL59FdBiCgWzWJYnjB242UshOynkIMVnbdAhci5caWmU/vvf2Dt2rAroAQPA7VZAS6tRMIuluKvPK3YDByhiBwXsp0jrxdLq3FlZlM2eTUX79oRPmkTIeedpBC2tQsEsluAJ5COUsJ0C9lJIuSaqxQLcOTmUfvYZQV27En755QQnJmqTmLQoBbOYxo3hPcd4I7lsJI8CHGaXJVInV0YGJe+8Q3DfvoRffrn3WtE6D1qam4JZWp1n7TiLctaSwy4K1fRSfIbz4EGKU1IIGTaM8EmTIDxco2dpVgpmaRVG9SUNDWAnBawnlwzKzC5LpGkMA8fmzTh27iRs/HjCxo4F0PqzNAsFs7Qoz3R1CU7Wkctm8ijBZXZZIs2jspKKJUuo3LSJiMmTCRkwQOvPcs4UzNIiPIGcQRmrOck+irSVS/yWkZ9P6X/+Q3C/fkRMnQpRUQpnaTIFszSrUwP5e05wmBKzSxJpNc4DByh65RXCL72U0NGjwTAU0NJoCmZpFp5APlYdyIcUyBKoKispX7gQx44dRFx3Hfb4eO3clkZRMMs58QTyccr5nixSFMgiQNXpVcWvv07YRRcRNnEioM1h0jAKZmkSTyBnUs73nOAgxWaXJGI9bjcVK1bg2L2biGuvrWpOonOf5SwUzNIonkDOqg7kAwpkkbNy5+RQ8s47hAwfTsTll2MEB2v0LPVSMEuDGRgU4mAhmeylyOxyRHyOY/NmnAcPEjltGkHdumnkLHXSdkE5KzcGlbj5jixmclChLHIOjMJCSt55h4rlyzEMA8OtEwmlJo2YpV4uDOzAVvJZQpYag4g0F8Og4ocfcB4+TOS0aRAZqdOqxEs/CVKLUd23OpMyZnGI+RxTKIu0AFdqKsWvvorz4EGzSxEL0YhZanBjUIGbb8lkK/m6tIRICzPKyij9+GNCR48m/PLLwWbT6DnAKZgF+PF6yJvJYwknKNMIWaRVVa5fjzM1lcibbsIeG6twDmD6zgsGBjlU8BaH+YrjCmURk7izsih+/XUc27ebXYqYSCPmAOYZJa8ih6WcwKWJaxHzORyUzZuH6/hxwqdMUb/tAKRgDlDu6nOSPyedo7ousojlVK5fj/vkSSJvukkNSQKMPoYFGHf1qHgTebxKikJZxMKchw5R/OabuAsLdb5zAFEwBxA3BqU4+YAjfM1xKnWFZBHLc+fkUDJrFq7UVAxDy02BQMEcADznJe+ggFc4qCtAifgYo7yckg8/pHLjRrNLkVagNWY/56pupzmfDPaolaaI73K7Kf/mG9wnThB+5ZUA2hTmpxTMfszA4AglzCFdnbtE/ETlxo24cnKIuvlmbQrzU/q45Yc8U9crOMmHpCqURfyM6/Bhit98E6O0FMOlf9/+RsHsZ1wYODD4mDS+54TOTBbxU+6cHIr/9S+MoiKFs59RMPsRNwZ5VPIGKezTerKI3zMKCij+179w5+YqnP2IgtmP7KWIWRwih0qzSxGRVmIUF1Pyzju4srJ0rrOfUDD7ODcGBgbfkslnHNW5ySIByCgro+S993AdPapw9gMKZh/mqr5E4/ukspocs8sRETNVVlLy4Yc4U1IUzj5Oweyj3BhkUc5rHOSwGoaICIDTSeknn+DYu1ddwnyYgtkHGRjso4i3OUwhTrPLERErcbspmz0bx5YtZlciTaQGIz5oI3l8w3GdCiUidTMMyr78EoCQYcOw2WwmFySNoWD2EQYGNmx8zwmWk212OSLiA8q++grCwwnp31/tO32IvlM+wNPJaz7HFMoi0nCGQdnnn+M8fFgbwnyIgtni3Bi4MPiEo2wmz+xyRMTXuN2UfvoprowMhbOPUDBbmLv6ylDvcUSdvESk6RwOSv79b9zZ2eoQ5gMUzBblwqAEJ//iMEcpM7scEfF1FRWUfPAB7sJChbPFKZgtyI1BLpW8ySGyqTC7HBHxE0ZJCSXvvqurUlmcgtli3BicoELnKItIizAKCyl57z2MykqtOVuUgtlCXBjkUMF7HKFM11AWkRbizsmh5P33weVShzALUjBbhAuDfCp5V6EsIq3AnZlJ6eefq/mIBSmYLcCFQSEO3uUIJQplEWklzn37KP/+e7PLkNMomE3mwqAYB+9wmCKtKYtIK6tYsYLKnTu13mwhCmYTuTAoxck7HNFGLxExTdm8ebhPnNBO7UaaM2cOycnJzJkzp1mPq17ZJnFhUI6LdzhCPg6zyxGRQOZ0UvLRR0T/4hcQEWFKX+309HQmTZpU47bw8HBiYmLo06cPw4cP54YbbiAxMbHVa2ttCmYTuDGowMU7HCaXSrPLERHBKCqi9OOPibr7bgzDMG1TWGJiItdeey0AlZWV5OTksGPHDl599VXeeOMN7r33Xh555BG/3rSmYG5lVaHs5l2OcFKhLCIW4srIoGz+fCJvuMG0GhITE/nVr35V6/aNGzfy2GOP8cYbb2C32/n1r3/d+sW1Eq0xtyKj+jpR/yaVE+roJSIW5Ni+nYrVqy13fvPIkSN56623CA0N5a233uL48eM17l+8eDF33XUXo0aN4vzzz+eaa67hX//6F67T1s2LioqYNWsWt99+O+PGjWPQoEGMGzeOxx57jLS0tDpfOz8/n2eeeYYLL7yQIUOGcOONN/Ldd9+12HtVMLciGzbmkE66el+LiIWVL16M89Ahy+3U7t27N1deeSUOh4PFixd7b3/hhRd48MEHOXz4MJMnT+bWW28lLCyM559/nkceeaTGMVJSUnj55ZcJCwtj8uTJ3HnnnQwaNIivvvqK//qv/yIjI6PG48vKyrjjjjv49NNPSUxM5M4776RXr1488sgjLFq0qEXep6ayW9H3ZLGLQrPLEBE5M8Og7IsviH7gAQgPN2UzWH1Gjx7NvHnz2LFjBwCrVq1i1qxZjBs3jpkzZxIZGQmAYRj8/ve/55NPPmHRokVcccUVAPTp04eVK1cSGxtb47hr167l7rvv5rXXXuOPf/yj9/a33nqL/fv3c9NNNzFjxgzv7ddddx333ntvi7xH63y1/Zgbg23ks5yTZpciItIgRkkJZXPmWCqUATp06ABAXl7V9ek//PBDAGbMmOENZQCbzcajjz6KzWbj66+/9t4eExNTK5QBLrjgAvr27cvq1atr3D537lxCQkKYPn16jdvHjx/P2LFjm+U9nU4j5hbmxiCdMuZzzOxSREQaxZmSQsWaNYRecIFld0Fv27aNyMhIPv/88zrvDw8P59ChQzVuW7duHe+99x7bt28nLy8Pp/PHPhIhISHe/y8uLiY9PZ2+ffuSkJBQ69gjR45kzZo1zfROfqRgbkEuDIpw8AlpuLDWRgoRkYYoX7KE4N69scfHYwsKMrscTpw4AUC7du0AKCgowOl08sorr9T7nNLSUu//L1iwgEceeYTIyEjGjRtH165diYiIwGaz8cUXX9RYYy4uLq7xWqdr3779Ob+fuiiYW4gbAyduPiCVUvW/FhFf5XJR+p//EP2LX2DY7aaPnNevXw/A+eefD0B0dDRQNQpuiFdeeYWwsDDmzJlDz549a9x36pT3qcfOzc2t81g5OTkNrrsxrLV44CeM6tHxx6SRo3OVRcTHuXNyKFuwwPRQPnz4MAsWLCA0NJTJkycDMHjwYPLz8zly5EiDjpGWlkafPn1qhfKJEydIT0+vcVt0dDTdunUjNTWV7OzsWsfauHFjk97H2SiYW4ANG19yjCOUnv3BIiI+wLFlC5W7d5t2CtWmTZu45557qKys5L777qNjx44A3HHHHQA8+eST3g1hp8rOziYlJcX79y5dupCamsrJkz9uxq2oqOD3v/89Dkft9sjXXXcdDoeDl19+ucbtK1eubJH1ZdBUdrMzMFhLLlvIN7sUEZFmVTZ/PsHdukF0dIvt1k5LS2PmzJkAOBwOcnJy2L59O/v37ycoKIj777+fhx56yPv4CRMm8MADD/Dqq69y+eWXM378eLp06UJ+fj6pqals2rSJX//61/Tp0weoCvIZM2Zw/fXXM2XKFJxOJ6urG6r079+fvXv31qjn3nvv5bvvvuOzzz7jwIEDjBo1iuPHj7Nw4UIuvvhifvjhh2b/GiiYm5ELgyzKWUyW2aWIiDS/igpKZ88m6u67W+wl0tLSvBu5PBex6N27Nw888EC9F7F4+OGHGTVqFO+//z5r1qyhqKiI2NhYunXrxkMPPcTUqVO9j73tttsIDg7mww8/5LPPPqNNmzZMnDiR3/zmNzz88MO1jh0ZGckHH3zAiy++yHfffcfu3bvp27cvf//73ykqKmqRYLYZVuu75qOqNnsZvMZB8nS1KDkHD9KXBMLO6RjFb76J65hO0ZOWEX7ZZYSOHWu5c5z9hb6qzcSOjblkKJRFxO+V//AD7oICy7Xs9BcK5mbgxmADuexWu00RCQROJ2Xz5mnE3EL0VT1HLgxOUsEiMs0uRUSk1bhSU6nctEmj5hagYD4HBgZuDD7lKE519hKRAFP23XcYpaWWu0Skr1MwnwPP+cpqIiIiAamigrJvvjG98Yi/UTA3kRuDLeSxnQKzSxERMY1zzx4cKSkYLrUebi4K5iZwYZBHJd9w3OxSRERMV/7116Dp7GajYG4CG/Af0nFoXVlEBHdeHhXLl2utuZkomBvJjcEqTpJJudmliIhYRsXq1bjz8rRLuxkomBvBjUEBDpZR+yojIiIBzeWifNEindvcDPQVbARPdy+dGiUiUptz/36caWkaNZ8jBXMDuTHYSC6pupSjiEi9yr/9VqPmc6SvXgO4MSjDpatGiYichSsjA8fu3Tp96hwomBvAXt1IpBxNz4iInE35kiWgpiNNpmA+CzcGuylkL0VmlyIi4hPcublUbtyoteYmUjCfgYGBA7caiYiINFLFsmWg6ewmUTCfgQ0bC8mkGKfZpYiI+BSjtJSKlSs1am4CBXM9XBikUsIW8s0uRUTEJ1WsWYNRVqaOYI2kYK6HHVigayyLiDSdw0H599/r6lONpGCuQ9WVo/LVdlNE5Bw5tmzBXVCgUXMjKJjr4MLge06YXYaIiO8zDCpWrTK7Cp+iYD6NgcFysrXhS0SkmVRu2YJRrhnIhlIwn8KNQRFO1pBjdikiIv7D6aRy7Vrt0G4gBfMp7NhYTJYuUiEi0swqN2zQec0NpGCu5sbgBOXsoMDsUkRE/I5RVkblpk0aNTeAgrmaHRvfkqWxsohIC6lYs8bsEnyCgpkfm4kcpNjsUkRE/JZRWIhjxw5deeosFMxAUPVoWUREWlbFqlXYgoLMLsPSAj6YXRjso4gMyswuRUTE77mzs3Hs369R8xkEfDAHYWMF2WaXISISMDRqPrOADmZ39dpyukbLIiKtxpWWhisnR2066xHQwWzHxgpOml2GiEjAqdy4ERTMdQrYYHZjkEW5dmKLiJjAsX27grkeARvMdq0ti4iYxigtxbF3rzaB1SEgg9mNQQGV7KbQ7FJERAKWY/NmbQKrQ7DZBZjBBqzgJGoMJ+IbKlwuXt26lT25uaQXF1NYUUF0aCjdoqO5rk8fruzVi2B71TjD6XazPD2d5RkZ7M7JIau0FBvQq21bru7dmxv69CHI3vAxyYLDh9manc2e3FxS8vNxuN08c8EFXNO7d73PKXY4eHP7dpYePUpOeTnxERFMSkzk3kGDiAwJqfHYXy5ezOYTZ77M7O/HjuWqXr28f5978CD/3ruX7NJSerdty8PDhzMkIaHW89YeP86vf/iBNy67rM77zeY8dAh3YSG2mBhsNpvZ5VhGQAZzGS62km92GSLSQGUOB3MOHmRA+/Zc1KULcWFhFFZWsub4cWasW8e3qam8dMkl2G020ouK+N3KlUQGBzOyUyfGd+1KscPByowMnt+wgdUZGbwwcWKDg+D17ds5XlJCbFgY8RERHC8pOXOtTie/XLyY/Xl5jOnUict79mRfbi4f7tnD5qws3pg8mbBTRonX9O7N8A4dah3HaRi8t2sXdpuNUR07em9fkpbGs+vXMyQhgYu6dGHp0aNMX7qUz66+mo5RUd7HlTud/Hn9em7o29eSoexRuWkTYRMngoLZK+CC2Y3BGnJ0BSkRH9ImLIzvp00j5LRpT6fbza++/551mZmsPnaMcV27EhkSwmMjR3J1795EBP/4K84TmCuPHWPJ0aNclpjYoNd+aswYusfE0Dkqivd27eKf27ad8fEf7N7N/rw87hwwgIeGDvXe/srWrby/ezcf793LzwYO9N5e38j7+7Q0DODCLl1IiIz03j734EF6tGnDG5ddht1m4+bkZG6YP5+FR45w1ynHfW3bNpxuNw+eUoMVVW7dStjFF5tdhqUE3BqzE4MN5Jpdhog0gt1mqxXKAMF2Oxd37w5AelERAB0iI5mWlFQjlAEigoO5tX9/ALZkNbwF7+hOneh8ykj0TAzDYF5KCpHBwdwzaFCN++4ZNIjI4GDmpaQ06Fjzqx93bZ8+NW4/UVpKUmws9uoRZueoKGLDwsgsLfU+ZndODp/t389jo0YRfdrUudUYhYU4Dx7UVadOEVDB7MJgE7mUa3VZxC+4DYM1x44B0Ds29qyP96xDN2aNuTHSiorILitjcEJCnR8MBickkFFcTNZZpsOzSktZm5lJfEQEF3XpUuO+DpGRHMjPx119qlFmSQn5FRV0qh5VO91u/rhuHRO7dWNCt27N+O5aTuXmzdha6HviiwJqKjsIG5vIM7sMEWkih8vFO7t2AVBQUcGGrCyOFBYytXdvRnfqdNbnf1k9Ch3TgMc2xdHqUXv3mJg67+8eE8Pa48dJKyqqsR58uq9SUnAbBlefsqnN47q+fXly5Up+uXgxA9u3Z+nRo4QFBTGlZ08APtizhxOlpbx8ySXN86ZagXP/fozycmzh4WaXYgkBE8xuDDIo4ySVZpciIk3kcLt5a+dO799twO3nnccDQ4ac9blfHDzI6uPHGdmxIxd17doi9RU7HAD1Th9HVd/ueVxdDMPgy0OHgNrT2ACXJSZSMGoUH+/dy5yDB+nTti3/78IL6RgVRWphIW/v3MmjI0cSHxHBe7t28fG+fRRUVDA0IYEnRo8msU2bc32bzc/txrFnDyGDB+v0KQIomG2g0bKIj4sMCWH9rbfiNgyyy8pYkZHBa1u3suPkSf5+8cX1BuKKjAz+unEjnaOi+MOFF7Zy1Y2zISuLYyUlDO/Qod6R9439+nFjv341bjMMg+fWr2dQ+/Zc27s3i44c4dVt27hv8GAGtGvHK1u38tiKFXx01VXe9WkrcezZQ+iwYWaXYQkBM6nvwFBDERE/YbfZ6BgZybR+/XhizBi2ZWfzzikj6VOtysjgiRUraBcezquTJhEfEdFidUWfZURccpYRNfy46eu6OkbLZzI3JYVdOTk8OWYMNpuNT/ftY3SnTtwzaBBju3ThsVGjOFRQwLrjxxt13NbiPHQIo1IzmhAgwezCYAf5VGrTl4jfuaB6vbiuJh0rMzJ4fMUKYsPCeG3SJLpGR7doLZ4Rrmet+XSe2xPrGQkXVlayLD2dmJAQLm3g6VwAJ8vKmLllC/cOGuStIbWwkH5xcd7HJFf/f2qhRQcoLpeu01wtIII5CBub1VBExC9ll1VdtvX0TVIrMzL43YoVtAkL49VJk+qdFm5OiTExJEREsD07mzKns8Z9ZU4n27Oz6RIVVe/GrwWHD1PhcjGlZ88aTUjO5vkNG+gcFcVt551X43bHKSFXWX06kpU7bDn27NEaMwEQzAYG2VSQoWsui/isQwUFlJ8WdFDV3eofmzcDVY04PFYfO8bvVqwgJjSU1yZNOuuGJ6fbzZGCAu+50E1ls9m4rk8fSp1O/nXa1Pq/du6k1Onk+r59631+fecun8nSo0dZkZHBU2PG1Phw0rNtW9ZlZuKsDuTVGRlVt1tx81c154EDGjETIJu/NqqhiIhPW5yaysd79zIkIYHO0dFEhYSQXVrK6uPHvTuOf5qcDMCRggIeW76cSrebER07sujIkVrH6xIdXaPj1onSUm76+ms6R0Ux77rrajx27sGDbMuuuhJdSn4+APNSUthU3aRkSEJCjbC9Y8AAlqWn8/7u3ezLzaV/u3bszc1lXWYmA9q145bqOk+3JzeXA/n59I+LI7lduwZ9XYorK/nrxo3cnJzMgPbta9x3S3IyT61axf1LlpAUF8fXhw7RNzaWUS10qlizcDhwHjxIcL9+AX1es98HsxvYToHZZYjIORjXtSsny8rYfvIkO06epNTpJDo0lL6xsVzeowdTe/f2jhZzysu907bfpqbWebzhHTqc8SIUp9qWnc3Xhw/Xus0T1kCNYI4IDuaNyy5j1o4dLD16lE0nThAfHs5t/ftz7/nnEx5c969d72j5DCPq0728ZQuhdju/HDy41n2Te/Qgs6SET/btY09ODkM7dOCJ0aMtuSP7VI49ewhOSjK7DFPZDMN/r1TtwmAPhcwm3exSRBrsQfqSQNg5HaP4zTdxVXfEEvEltvBwYn7724AeMfv1O6/a9KVzl0VEfIVRXo4zNTWge2f7dTCX4eIwZ+5JKyIi1uLcuzegLwPpt8Hsmcb223l6ERE/5Tx82NKndbU0vw3mIGzsVacvERGf487Oxl0WuKe4+m0wO3BzSNPYIiI+yXnoUMCuM/tlMLswOEARTk1ki4j4JNeRIwG7zuyXwRyEjT2cWwcfERExj/PIkYBdZ/bLYHZXj5hFRMQ3uU+exF1aanYZpvC7YHZjcIQSynUlKRERnxao68x+F8w2YI92Y4uI+LxAXWf2w2C2sVfT2CIiPi9Q15n9KpgNDI5RRhG1Lw8nIiK+xZ2Tg7sk8E579bNg1jS2iIg/cR46FHDXaParYLZj44iaioiI+A3X8eMBt87sV8HsxM0xys0uQ0REmokrMzPgLgHpN+/WwCCdMlzq9iUi4jfcWVlml9Dq/CaY3aBpbBERP2OUlgbcBjC/CeYgbKQSmF1iRET8mevYMQwjcGZD/SaY3RikK5hFRPyOKzMTAqgDmF8Es+f8ZYfWl0VE/I47MxNbUJDZZbQavwhmrS+LiPgvV2am2SW0Kr8IZq0vi4j4L3deHobDYXYZrcYvgtnAIE3BLCLinwwD14kTZlfRavwimE9QQYUu8ygi4rdcx48HTGtOnw9mV/X1l0VExH+5T54MmNacPh/MdiBLbThFRPyau6AgYFpz+vy7tGHjBBVmlyEiIi3InZ9vdgmtxueDGSBbwSwi4tcMBbPvKMShjV8iIn7OKC8PmFOmfDqY3Rhkan1ZRCQguAsKzC6hVfh0MBto45eISKBw5+UFxMUsfDqYg7TxS0QkYLjz8wPiYhY+HcwAJzRiFhEJCO6CgoA4l9mng9mNwUkqzS5DRERagZGfHxDnMvv0O8yjEpcu9SgiEhC0+cvitCNbRCSwKJgtzkCNRUREAolRGhhXEfTZYA7CRgGBcbK5iIgALheG02l2FS3OZ4MZoAj//waJiMiPjHL/X8L06WAu1IhZRCSgGGVlZpfQ4nw6mDViFhEJLApmC3PipgyX2WWIiEgrMkpL/b4tp88Gc7FGyyIiAceorAQFszVpfVlEJPAomC3KjaFTpUREApGC2ZrcGBRqKltEJOAYlZV+fyELnwxmOzaKNGIWEQk4CmaLsmPTiFlEJBCp85d1acQsIhKA/Hy0DD4czBW4zS5BRESk2flsMDsUzCIigUcjZuty4N/b5UXORVDnzmaXINIyFMzWpRGzSN0Mt5uIa64h+v77CRk4MCB+kUkACYCf52CzC2gqBbNI3Wz2qs/b9vh4IqdNw5WXR8Xy5Ti2bwe3/t2IWJ1PjpjdGIplkbPwBnRsLJHXXUfMr39N6OjREOyzn8dFqkbM6vxlPU6tL4s0mK166s8WHU34lCnEPPIIYRddBKGhJlcm0gSayrYmp8bLIo3mCWgiIgi79FLCxo+nYt06KteuDYhr3Ip/8P9Y9tlg1ohZpKlsNlvVqCMsjLBx4wgbO5bKjRupWL0ao7jY7PJEzkwjZmvSxi+R5mGz28FuJ3TMGEJHj6ZyyxYqVq3CyM83uzSRuimYrUnBLNK8PBvFQocPJ3T4cBw7d1KxciXu7GyTKxM5TQDsjfDJYK7UVLZIi/AEdMjAgYQOHoxj714qli/Hdfy4yZWJVLFFRJhdQovzyWA2FMzi5wwMbCZuc7EFBQEQ3K8fIf3740hJqQrotDTTahIBsIeH+/10tk8Gsz0g9uVJoFpDDpfSgSiCMDD3590b0D17EtKnD86jR6lYvhznwYOm1SSBzRYZ6Z3Z8Vc+GcxBCmbxY5vJYxv5DCGWCcQTSyhuDEsEdFDXrkTddhuurCzKly3DuXev3zd7EGuxRUaaXUKLUzCLWJALg83ksZU8BtKWiSQQT5j5Ae3pJpaQQNRNN+HKyaFixQocO3ao3ae0ikBYY7YZhu993M2mgn+iqTQJHDYgmRgmkkBnInBhWOIDqmEY2Gw23IWFVKxYQeXWreB0ml2W+LE2TzyBzc93ZvvkiNm/VxdEajOAvRSxlyJ6E8VEEuhBlOkB7W33GRND+FVXEXbJJVSsWkXlxo1QWWlaXeKnbDa/D2Xw0WAOVjRLADtECYcooTsRTCCBfsRYJqCJiCD8sssIHz+eirVrqVy3DqO83LS6xL/YwsPNLqFV+ORUdglO/so+s8sQsYROhDOeeAbQBjfW2YNhuN3gclG5YQMVa9ao3aecM3u7dsT86ldml9HifHTEbI1fPCJWkEk5/yGd9oQyjniGEIuB+QHtbfd5wQWEjhlD5ebNVe0+CwpMrUt8VyBs/AIfDeYQTWWL1JJDJfM4xg9kcxHtGUE7bJh/3r+33eeIEYSOGIFj+/aqdp85OabWJb4nEE6VAh8NZjs27KCO2SJ1KMDBN2SynJNcQHvG0I4gbJYJ6JDzzydkyBCce/ZQvmIF7sxMU+sS32GPjfWeCeDPfDKYoWrUXKFoFqlXMU4Wk8UqTjKadoylPWHVs02WaPeZnEzMgAE4Dh6savd59KhpNYlvsMfFVZ0vX/0z5K98NpjDFMwiDVKGi2Vks4YcRhLHRcQTaaV2n716EdK3L860NCqWLcN56JBpNYm12ePiwM/bcYKP7soGmEUKx9BpGCKNFYyNocQygQTaEGJ6NzEPw+3GZrfjOn6c8uXLq9p9ipwi+oEHCEpIMLuMFuezI+Zo3y1dxFRODDaSx2byOJ+2TCCB9lZq99mxI1E334zr5Ekqli/HsXOn+nELULXGHAh8csRsYPAVx9lEntmliPg8G9CfGCbSgU6Emx7QHp4RtLug4Md2ny6X2WWJSWyRkbT57W/NLqNV+GQwuzBYTjbLyDa7FBG/0pdoJpJAdyJN7ybm4fkVZZSUVLX73LQJHA6Tq5LWFtS1K9H33mt2Ga3CZ+eDNZUt0vwOUsxBikkkkokk0Ido0wPae2pMVBThl19O2IQJVK5ZQ8X69VBRYVpd0rrscXFml9BqfHLEbGCwjyI+QadXiLSkzoQzgQTOo43pAX0qw+0Gp5OK9eupXLsWo6TE7JKkhYWNH0/YxIne3fz+zCeDGeAYZcxCp1WItIYEwhhHPOfT1hLtPj0Mtxvcbio3baJi9WqMwkKzS5IWEnHttYQMHqxgtrIiHLzAfrPLEAkocYRwIfEMJ84S7T49DLcbDOPHdp+5uWaXJM0s6mc/I7hHD7PLaBU+u1Ab6buli/isPBx8zXGWk81Y2jPKau0+Bw8mZOhQHLt3U7F8Oe4TJ0ytS5pPUIcOZpfQanw23YKwEUEQZej0CZHWVoSTb8liBSe5gHZcQHtCquPZCu0+Q/r3J3TgQBz791e1+8zIMK0mOXe2Nm0C5spS4MPBDFU7sxXMIuYpw8VSsllNDiNpx0W0J4KqcLRCQAf36UNIUhLOI0coX74c1+HDptUkTRfUubPZJbQqn11jBnifIxxCuzFFrCIYG8OJYzzxxFiw3afz2LGqftz7tT/Fl4RdfDFh48YFxMYv8OFgNjBYQCbr0SYPEasJwsb5tGUiCcQRarmAdmVnV7X73LVL7T59QOSttxLct6/fX+7Rw2eD2YWbzeTzNcfNLkVE6mEDBtCGCSTQ0YLtPl15eVSsWIFj27aqywmKJcU8+ij2qCizy2g1PhvMAKmU8A5HzC5DRBqgX3W7z24Wa/dps9lwFxVRsXIllZs3g9NpdllyClt0NG1+8xuzy2hVPh3MpTh5nn1mlyEijdCTSCaQQG8LtPv08PbjLi+ncvVqKjZsULtPiwju14+oW281u4xW5dPBDPA8eynVzmwRn9OVCCYQT7IV2306HFSsW1fV7rOszOySAlrYhAmETZgQMBu/wA+C+W0Ok0ap2WWISBN1OKXdpxuLtft0uX5s91lUZHZJASnyllsI7tfP20QmEPh0MOu6zCL+ox2hXEQ8Q4m1ZrvPrVupWLUKd55+37SmmN/8Bnt0tNlltCqfDmYXBhvIZSGZZpciIs2kDcFcSDwjicNugXafHobLBXY7jh07qvpxZ+t68C0tEDd+gY8Hs4HBYUp4n1SzSxGRZhZJEBfQngtoT7DFAtoWFIRj714qVqzAdeyY2SX5rZDBg4m84Qazy2h1Pt2S04aNjoSbXYaItIBSXHzPCVZzklG040LiCadqndES7T779SOkf38chw5V9eNO1QChuQX36uX9IBRIfHrE7PFn9lCOmgOI+LOQU9p9RlWPKcwMaA9PcDjT06vafR48aHZJfiMQ15fBT4L5XxziKDqlQSQQBGFjCLFMIJ5YK7b7zMqifPlynHv2qN3nObC3b0/MQw+ZXYYpfD6Y3Rh8RxZryDG7FBFpRXZgIG2ZQAIJhFkvoHNzq/px79ihdp9NEDpqFOFXXhkw/bFP5RfBvI8iPuWo2aWIiAlsQBIxTCSBLkRYplmJt91nYWFVu88tW9TusxEib76Z4KSkgDp/2cPngxmqrgn7F/aaXYaImKw3UUwkgR5EWSqgAYyyMipWraJy40aorDS5Kouz2Wjz+OPYwsLMrsQUfhHMAC9zgFz0wy4i0J0IxpNAEjGWC2gqK6lYu5bKdevU7rMeQV26EP3zn5tdhmn8IpgNDOZxjK3km12KiFhIJ8IZTzwDaGPNdp8bNlCxZg1GcbHZJVlK2LhxhF1ySUBOY4OfBLMLg23kMx+d6C8itbUnlHHEM4RYDCwW0IZB5ZYtVKxahZGfb3ZJlhB1550E9ewZkBu/wE+CGSCXSl7mgNlliIiFtSWEC2nPCKu1+6zete1t93nypMkVmSgkpGp9OcCaipzKb4IZdAlIEWmYKIIYS3tGW7DdJ3Y7zr17KV++HHdm4F0HIGTAACL/67/MLsNUfhXMn5DGXnRpNhFpmHDsjKY9F9KeMAu0+/Tw9uNOSaFi2TJcRwPndNDI//ovgpOTNWI2u4jm4MJgHTl8S5bZpYiIjwnFzgjiGEc8kQRhYI3LTnrbfaalUbF8Oc6UFLNLalkhIbT57W+xhYSYXYmp/CaYDQyOUc6bHDK7FBHxUcHYGEos40mgLSHW6yaWmUn5smU49/pn34bg884j6qabzC7DdH4TzFA1av4ze3DgN29JRExgBwbRlokk0N6K7T5zcn5s9+k/v8KJmDaNkP79A3oaG/wsmAE+Jo19WmcWkWZgA/oTw0Q60IlwywW0u6CAihUrqNy6FVw+vvE1OJg2jz0W8NPY4GfBrPOZRaSl9CGKiXQgkUjLdRMzSkt/bPfpcJhcVdNoGvtHfhXMUNU3+3n2ajJbRFpEIpFMIIG+RFsuoKmooGLNGirWr4fycnOLaqSIG28k5LzzAn4aG/wwmAHe4hDpPnR95qPfreXARwvJ230IZ2kFEQlxtB+axNDf3klU53gAPk7+yVmPc+0Ps7yPPxPDMEj/bh37P/iGwsPpOIpKiewUT4cxAxnw8xuI7t6p1nNObtvP7tc/J3vzXpwlZUR2SaDH1eMY8IufEBxes9F84aEM9r49j5ydKZRl5uAoLiWiQxxt+yWS/LOpdBo7uNbx05esZ8fLn1Cclkl0YifOn34L3SaNrvW4ggNpLLzhUcY89xA9p04463sVaSmdCWc8CZxHjPXafTqdVKxfT+XatRglJWaXdHaaxq7B74LZhcFqTrKEE2aXclaGYbDh/14n5dPviE7sROdxQwmOiqDsRC4nNuziwr8+QsLI8wDYMfOTOo9RlJpJ6pfLadO3O1d//VKDXnfzn99h3ztfEpEQR9dJowmJjiBv7xEyV20jODKcyZ88S2xSD+/jj367llWPvIDNbqf75RcQnhDLyc17ydl2gPjh/bn0vf9HUOiP/6DSFq5mw/+9TvzQZKK6JBAcHUlZVg4ZSzbgKC5l8K9vZeD907yPz9l+gG9v+h2xSYl0umgIx1dupfBgOpM/+zPtz+/749fL7ea7nz5JWNtoJs56ulFfa5GWEk8o40hgMG2t1+7T7aZy8+aqdp+FhWaXVK/g/v2Juvlms8uwjGCzC2huQdg4jzY+Ecz73/+alE+/o9+tUxj+9D3YT5vCcTt/3Mxx/q9uqfMYG2e8CUCfaZMa9Jpl2Xnsf+9roromMGXei4TGRHnv2/vul2x57h32vvMlFzz3EADO8go2/N/r2Gw2Jn/8LO0G9QGqPlRsmvEWB/69gH3vfsmA+34c0Xe9dBTdrxhbq89taVYuC2/4DTv/+Rn9bruS0DZVr50yezGhbaK47ONnCYmKYNCDpcy75Bcc+s/iGsG8/8MFFOxP46oGfgARaQ0nqWQuGfzACS4inuHEYcP886BtdjvY7YSOHEnoyJE4tm2raveZm2tqXXUJGTTIe862gF9euiOeMOKw9pSIs7yCnf/8jOjuHRn+VO1QBrAHn/mH1FVRSeqXK7CHBNPzuokNet2SjBMYbjfxw/rXCGWArhePAKAi78dP1ie37KMit5Cuk0Z7QxnAZrMx+Ne3AnDwk0WcOvESFBpSZ/P5yI7tSBjeH7fDScmxHz84lR7PIaZnZ0KiIgAIiY6kTc8ulBz/sV9wybFstv/93wx+5DaiuiQ06L2KtKZ8HHzNcf7OftaQgwM3bgvsdrHZ7djsdkIGDyb6oYeImDYNe8eOZpflZYuM1ClSp/G7ETOAG4NkYliL9T4ZemSu3EZlQTG9fnIJhtvN0W83UHTkGCExUXS6cDAxPTqf9RhHv11LZUEx3a8YS3i7tg163ZgeXbCHBHNyy14cxaWEREd678v4YRMAHS8433tbeXYeANHdOtQ6VmibKELbRlOSkU3x0SxiEmuvTZ+qIq+InG0HCIoII7rbj4+N7NyenO37cZaWExwZjqOkjKLU4ySe18v7mI2/f4O2/bqTdPuVDXqfImYpxsl3ZLGSk4yhHWNpT6gF2n16gi+kf39CBw7EceAAFcuX40pPN60mgJChQyFAryJVH78MZoD+tLF0MOfuqmqtZ7MHsWDqIxQd+fEUL5vdTvLPrmHY4z874zEOzV4CQJ//uqzBrxsWF8OQR+9gy5/f5espv6qxxnxi3U763TqFpNuvOuXxbQAoTq+9NFBZVEJlQdV1ZIsOH6sVzIWHj5H61XIMl5uyE3lkfL+ByqISRv3+F4RER3gf1/vGSaR8tpjvfvoknS4cQuaqrTiKSuld/b6OfLmczNXbuWLOXwP2+qzie8pw8QPZrCGHkcRxEfFEUBWOVgjo4N69CenXD2dqKuXLluE6fNiUesJGjVIwn8Yvg9mOjUQiCcdOOW6zy6lTRU4BAPvenU/cgN5c/p+/0KZPN/L2HGbD/77G3rfnE929E/1unVLn84uPZpG1bieRXeLpdNGQRr12/59NJbJDO9Y9/SoHP1nkvT1hxHn0uGZ8jSn0+OH9CYmOJGPJenJ3H6LdgN7e+3a89OOGtMqi2js/i44cY+crn3n/HhwZzphnH6LXadPu8UOSGDfzt+x4+VMOfrKI6MROjHvlMdqf35eKvCI2P/s25917PbFJPTg053t2vvIppZk5xPbvyajf/4L2g/s16v2LtKYK3Kwih3XkMow4xhNPGwu0+/QEdFC3bkTfeSeuY8coX74c5759rVZDUK9e2GNjW+31fIXf7co+1eeks4MCs8uo0/r/fY2Uz74jKDyUa759lciO7bz35e9PZeF1vyGqWwemfvdqnc/f/o+P2PXabAY9dFO9G8Pqs/OVz9j1+mzOn34LPa+dQEhMFPl7jrD5ubfJ23uEcS//tsapSin/Wcz6p1/FHhpC9yvGEpEQy8kt+8jdmUJ0944UHsrgwr//Dz2uGlfn67kqHZRkZJPy2XfsfWc+SbdfyYin721QrWsee4mc7Qe5cv6L5O5MYfFPnyTpjqvpeulIds/6gvx9R5i6+DXv+rSI1dmBwcQygQTaEWp6QHt4231mZ1e1+9y1q8XbfUbedBPBSUlaXz6N384LujAYQBuzy6iXZ2233aC+NUIZIDapB1HdO1KclkllYe2RqOF2c/iLpdjsdnrf2LDd2B6Zq7exY+Yn9LvtSgbc9xMiO8UTEhVBwsjzmPD6k9iDg9jyl/dqPKfPf13GxFlPEz80mYwl6znw0UJswUFc+u7/I7p6LfxMa9xBoSG06dWFYY/fRb+fXsH+D77h2LLNZ631+MqtHJm/nNF/vJ+g0BD2f/A1MT27MOLpe+h04RAu+PNDVOQVkfrl8kZ9DUTM5Aa2ks9MDvAZR8mmovp2c8dInmUie/v2RN54IzHTpxMyfDi0UGjaoqIC/vKO9fHLqWyoOm0qiRgiCaIU6/WQbdO7CwChMZF13u+53VVeAW1q7p4+vmILpZk5dBo3tNE7lI8trwrEjmMG1bovIiGONr27krf7MI6Sshqj0C4Th9Nl4vBazyl47CVsdjtxA3vXuq8unS4ayoGPFnJi/c46j+fhLKtgw/+9Qd+bJtNh5ACgas06tn9P72MiO8UTFhdD4aGMBr22iJUYwG4K2U0h/YhmIgl0s0C7T09A29q2JeKaawi/5BIqVq6kcvPmZm33GTpsWLMdy9/4bTBD1XTA+bRlnQU3gXUYU7XzuaCOUHE7nBSlZRIcGU5YHSPRlCZs+jr12ADluXU3G6jILcRmt2MPOfuPRvamPZRknKDLxOG1Tr2qT9mJqu+FPfjMx9/+j49wVzoY8ts7atzurnSc9nenNo6IzztAMQcopmd1u8/eFmj36T3lMSqK8CuuIGziRCpXr6ZiwwaoqDjXgxM6cqT+7dbDb6eyPYYTZ3YJdYpJ7ESncUMpTj1Oyn++q3Hf7llzcBSW0O2yMbXOZS7PLeDY0o2EtWtD10tH1Xt8t8NJYUo6RWmZNW5PGF7VSWzfu/Nrbdg68PEiSjNzaD80qUYnL0dxaa3jl2blsv7pV7EFB3H+wz+tcV/uzhTq2rpQknGC3bPmANB5Qv2flnO2H2D/B18z4pl7awR+2z7dyN60B0dxVbvVqv8vpU2fbvUeS8SXHKGU90nlTQ5xoPoqeS6zp7htNmw2G/aICMIuuYQ2//M/hF16KbbIumf7GiK4Tx/sbdvW2e9A/HzEbMNGR8LpRDiZWK+h+8j/u4/vbnmC9U+/Rvri9d5p5Ky1O4jqmsDQx+6s9ZzDc3/A7XDS87qJNcLzdKVZuXx91XSiuiZw7fdveG/vPmUsCR8PIHvDbr664iG6XTqKkJgo8nYfImvtDoLCQxn+xN01jrXv/a85Mn85CSP6E96+LaXHc0hfsh5XeQWj//Qg7Qb2qfH4LX95l6LU47QfklTVu9tuozgti+PLN+N2OOn/39eRMOK8Out2O12sf/pVuk4aTffJF9S4L+mOq0j9agWLb32SDmMGkfbNKsLjY+l5zfizfq1FfEkGZXzCUToQxjjiOZ+2lujHbbPbITSUsIsuImzsWCo3bqRi9WqMosZdajd05Eh1+joDv96VDVWfNjeQy0Iyz/5gE5QcP8mOlz/m+IotVOYXEx4fS9dLRzHowf8ivH1srcd/fdV0ClPSueqbl2l7hpFicfoJvpz0y1rBDFW7pPe9+yVpC1ZRePgYboeT8PZt6TjmfAb88sZax81cs4Pdsz4nf18qjsISQmOj6TBqIOf9/IYap095pC1cTdqC1eTtSqE8pwC3w0lYuza0H5JE35sm03l8/aPlXa/PZs9bc7n6m5eJ6NCu1v2H5y5l5yufUZqZQ9x5vRj5f/fV6Egm4o/iCGEc8Qy1SLtPD8PtBsP4sd1nXt5Zn2Nr25aY6dPVk+AM/D6YoepE/7+xz/QpIRGRc9GGYMYSzyjisGOzTkC7XGC349i5k4oVK3BnZ9f72PArryR05EgF8xkERDADfEoae2jcdIuIiBVFEsQFtGcM7QjBbqmAtgUF4di3r6rd57FjNe63RUYS88gj2M6y+TPQBUQwuzE4SDEfkWZ2KSIizSYMO6Nox0XEE26Bftwe3oA+fLgqoI8cASDs4osJGz9eo+WzCIhgBjAweIH9FOM0uxQRkWYVgo3hxDGOeKKr9/RaIqCru4k509OpWL2ayGuvxRYebnZZlhcwwezGYAlZrCLH7FJERFpEEDaG0JYJJBBrwXafhmHoFKkGCJhgNjDIpZKZHDS7FBGRFmUHBtCGiSSQQLhlAloaJmCC2eMDjpBC7f7TIiL+xgYkEcNEEuhChALaRwRUMLswSKOU9zhidikiIq2qF1FMJIGeRJne7lPOLKCC2eMNUjhuwU5gIiItrRsRTCCBJGIU0BYVcMHswmAXBcxBVyQSkcDVkTDGk8BA2lii3af8KOCCGap2aL/EAQpovkuYiYj4ovaEchHxDCUWsE67z0AWsMG8jlwWWbR/tohIa2tLCBfSnhEWa/cZiAIymAEcuHmBfZTjNrsUERHLiPK2+2xPsALaFAEbzG4MvucEKzlpdikiIpYTjp3RtOdC2hNmoXafgSBgg9nAoBQXL7JfV50SEalHKHaGE8d44okgSCPoVhCwncRt2IgkiMG0NbsUERHLqsTNWnI4SLGGMK0kYIMZwADGEa/PfyIiZ9COUAbTVqdUtZKADmY7NtoTxkDamF2KiIhljSde22RbUUAHM1RtAptMR30SFBGpQxwhDCFWvyNbUcAHsx0bbQhhJHFmlyIiYjnjSdDacisL+GD2uJgO3lMCREQEEghjqEbLrU5JRNUO7TDsXEh7s0sREbGMK+io0bIJFMzV7Ni4kHiiCTa7FBER0/Uhir7EaLRsAgXzKYKwMZEEs8sQETGVHZhCZ9waL5tCwXwKOzZGEEd7Qs0uRUTENMOII4EwdfkyiYL5NAYwiY5mlyEiYoow7EyiA4ZGy6ZRMJ8mCBsDaENXIswuRUSk1Y0jnnCCdMEKEymY6+DC4AqNmkUkwMQSwoXEawrbZArmOgRhI5EoBqlVp4gEkMs0ILEEBXM9DAyupDPh+hKJSADoRgSDdKEKS1Dq1MOGjQiCuJQOZpciItKibMBVdNa16S1CwXwGdmyMoh1dCDe7FBGRFjOadnQhQqNli1Awn4UbmEoX/biKiF+KI4TL6KjToyxEwXwWQdjoRDijaWd2KSIize5aumLHptOjLKTFg/mOO+4gOTm5xm3r1q0jOTmZmTNntvTLNwsbNi6jI7GEmF2KiEizGU4cvYjSFLbFnFMwP/HEEyQnJzNmzBgqKyubqyZLsmPjWrqYXYaISLNoQzBT6KQpbAtqcjAXFxezcOFCbDYb+fn5LF68uMHPHTx4MN988w233XZbU1++1QVhozfRDCXW7FJERM7ZVLpU9/fSaNlqmhzMCxYsoLS0lJ/97GfY7XZmz57d4OdGRETQp08f2rXzrXVbA4MpdCKKILNLERFpssG0pZ8u6WhZTQ7m2bNnExwczL333suYMWNYs2YNGRkZDXpuXWvMkydPZtiwYZSVldX5nF/+8pckJydz+PDhGrcvXryYu+66i1GjRnH++edzzTXX8K9//QuXy9XUt1YvGzZCsXMdXZv92CIirSGaYK6is6awLaxJwXzw4EG2bt3KRRddRHx8PNdffz1ut5s5c+Y0uZBrr72W0tLSOqfEc3NzWblyJUOGDKFXr17e21944QUefPBBDh8+zOTJk7n11lsJCwvj+eef55FHHmlyLWdix0YSMdqlLSI+6So6E1q9D1usqUnB7Jm2vu6664Cq0W5kZCRz5szB7XY3qZBrr70WgPnz59e675tvvsHhcHhfD2DVqlXMmjWLcePGsXDhQp599lmeeOIJZs+ezS233MKiRYtYtGhRk2ppiCvoREfCWuz4IiLNbQBtGEAbXaTC4hodzA6Hg3nz5hEdHc1ll10GQFRUFJdddhnHjh1j9erVTSqkR48eDBs2jNWrV5OTk1Pjvnnz5hESEsKVV17pve3DDz8EYMaMGURGRnpvt9lsPProo9hsNr7++usm1dJQN9GdEP2Ai4gPaEsI19JFU9g+ILixT1iyZAm5ublMmzaNsLAfR4zXX3898+fPZ/bs2YwbN65JxVx77bVs2bKFr776irvuuguAI0eOsH37di655JIam8W2bdtGZGQkn3/+eZ3HCg8P59ChQ02qoyGCsBFHKFfSmfkca7HXERE5V0HYuJnuhGgK2yc0Opg909jXX399jdvHjh1Lx44dWbJkCfn5+cTGxja6mKuuuopnn32W+fPne4N53rx5ADWmsQEKCgpwOp288sor9R6vtLS00TU0hh0bw4kjhWJ2UdiiryUi0lSX0ZHOhCuUfUSjgvn48eOsWrUKgNtvv73ex82fP58777yz0cXExsYyceJEFi9ezKFDh+jduzfz588nJiaGSy+9tMZjo6Ojgaod3mZyY3AtXcigjHwcptYiInK684hhLO3NLkMaoVHB7NncNWLEiBq7oz1cLhdffPEFs2fPblIwQ9XIePHixcyfP5/x48eTnp5ea9ocqpqULF++nCNHjtCzZ88mvVZzsGMjGDvT6MbbHKZpW99ERJpfHCFcT1cMDI2WfUiDg9kwDObMmYPNZuMvf/kL3bt3r/NxR44cYcuWLezYsYPzzz+/0QVdfPHFtG3bli+//JLc3Fyg9jQ2VPXgXr58OU8++ST//Oc/iYuLq3F/dnY2hYWF9OnTp9E1NFYQNroSwcV04HtOtPjriYicTTA2biaRYK0r+5wGB/PatWtJT09n9OjR9YYywE9+8hO2bNnC7NmzmxTMoaGhTJkyhU8//ZQ5c+bQtWtXRo0aVetxEyZM4IEHHuDVV1/l8ssvZ/z48XTp0oX8/HxSU1PZtGkTv/71r1slmKGq+ch44jlEMUdo2bVtEZGzuZxOdCBMp0b5oAafLuXZ9HXDDTec8XFXXXUV4eHhfP3115SXlzepKM8I2eFwcM0112Cz1f2D9fDDD/POO+8wYsQI1qxZw7vvvssPP/yAw+HgoYceYurUqU16/aYyqDqFqk3j99SJiDSbgbRhNO0Uyj7KZhiGTmprRi4MTlLBWxzCofMFRaSVtSeUX9CHYGwKZh/V4tdjDjRB2EggjJ/QTf8kRKRVhWDjJroTpFD2aQrmFmDHRn9iuIQOZpciIgHCBkyjOwmE6apRPk7B3EJs2JhAAoNpa3YpIhIArqATSURrpOwHFMwtyMDgOrrSjQizSxERPzaGdlxAe50W5ScUzC3IVv3P5FYSaUuI2eWIiB9KJoYpdDK7DGlGCuYWZsdGGEHcRiKh+nKLSDPqQjjT6GZ2GdLMlBStIAgb8YRxI1010SQizaItIdxGD4K8c3PiLxTMrcSOjSRimExHs0sRER8Xhp3b6UE4Qdrs5YcUzK3Iho0LiWc88WaXIiI+Kggbt9Cd9oTqtCg/pWA2wSQ6cgHtzC5DRHzQNXSmJ1EaKfsxBbNJptCZEcSd/YEiItWuoBPDiNOasp9TMJvEwOAaOqsBiYg0yOV0ZCztzS5DWoGC2SSeT7zX05XziDG5GhGxssvoyIXamxIwFMwm8oTzNLrTl2iTqxERK5pEB8YplAOKgtlk9up4voXu9CTS7HJExEIuoQPjSTC7DGllCmYLsFdfou02eqivtogAcDEJTFQoByQFs0XYsRGEjTsUziIBbwIJXKzLxgYsm2EYhtlFyI/cGLgw+IQ0UigxuxwRaWXjiWeSOgQGNAWzBbmp+pbMIZ2dFJpcjYi0FoWygILZsozqcF5AJuvJNbkaEWlJNmAKnRij85QFBbNP+IET/EC22WWISAsIxsY0upFMjDp6CaBg9hkbyOUbjqNvloj/iKi+VnsXItT7WrwUzD7CwGA3hcwhA5fiWcTnxRLCnfSgra4SJadRMPsQNwZHKOETjlKJ2+xyRKSJOhPOHfQgjCCFstSiYPYxbgwyKeffpFKCy+xyRKSR+hLNzXQnqLqxkMjpFMw+yIVBGU4+Io1jlJtdjog00FBiuZYuAAplqZeC2Ue5q0+o+pJjbCXf7HJE5CwmksAldMDA0O5rOSMFsw/z/ANfRw6LyNSqs4gFhWPnBrqSTBuzSxEfoWD2AwYGRynlU45q3VnEQjoSxk9JpA0hmrqWBlMw+wkXBqU4+VjrziKWMJRYrqGz9+pxIg2lYPYjnnXn+WSwjQKzyxEJSMHYuJJOjKCd1pOlSRTMfsbzi2AtOXyrdWeRVhVLCLeQSAfCNEqWJlMw+6mqdecyPiedAhxmlyPi9/oRzY10IwS7mobIOVEw+zFX9bWdv+IY2zW1LdIibMDFdGAiCbgxNFKWc6Zg9nOeqe1dFPAVxynTrm2RZtOWEG6gKz2I1FqyNBsFc4BwY1CGizmkk0KJ2eWI+LwhtOVquhCETVPX0qwUzAHEM822jhwWk4VDV6kSabRIgriWLvSnjXZdS4tQMAcgNwZ5VDKbdI7rnGeRBksmhuvoQjhBWkuWFqNgDlDu6tHyUk6wipM6rUrkDCIJ4ko6cT6x2uAlLU7BHOAMDI5RxnyOkUWF2eWIWM5A2nANXQjDrkCWVqFgFlwY2IF15LKUE1Ro/CxCNMFMpTPJWkuWVqZgFi83BuW4WEimznuWgGUHRtGOS+lAsJqFiAkUzFKDZ/0sjVK+4hgnNL0tAaQv0VxJJ9oRCqBRsphCwSx1cmFgA9aSwzKyNb0tfq09oVxBJ5KI0eYuMZ2CWc7I05hkAcfZSaHZ5Yg0qzDsTCSBMbQH0LS1WIKCWc7Ks/HlCCUs4Lh2b4vPswHDiOUyOuqcZLEcBbM0mGf39g4KWMoJ8nTVKvFBiURyFZ3pRLh2W4slKZil0TzrzxvJYznZFOM0uySRs+pIGBNJYABttY4slqZgliZzV19Wci05rCZHV64SS+pMOBNJoD9tcGFoHVksT8Es58yNgbM6oNcooMUiuhLBRBJIIkaBLD5FwSzNRgEtVtCdCCbSgb5EK5DFJymYpdl5AnoDuawnlwJtEpNW0INILiaBXgpk8XEKZmkx7upNYnsoYh05pFJqdkniZ2xAb6KYQAI9iFIgi19QMEuL8/yyzKKcNeSwkwKc6MdOmi6CIIYSy2jaEUeodlmLX1EwS6vx/PIsw8V6cthIHkU61UoaoQvhjKId59PWOzLWecjibxTMYgp39Yh5JwWsI5cMykyuSKwqBBuDaMto2tGZCE1Xi99TMIupPL9kj1HGNvLZSQEl2s0tVF1YYiTtGE4sodgxQNPVEhAUzGIJno1iBnCYEraRz16KqNRVrQJKBEH0J4bBxNKLKK0dS0BSMIvleH4ZO3GzhyJ2kM9BihXRfiocO/1pwyDa0pso7wc0BbIEKgWzWJpnqrsMFzspYDv5HNV6tM8Lw05/YhhIW/oQjR2FsYiHgll8hiekC3CwmwIOUkwqpTr1ykeEYSeJGM6vDuMgbJqqFqmDgll8kieknbg5TAkHKOYgxeRSaXZpcooOhNGbKHoT7Q1j7aoWOTMFs/g8z8YxGzbyqWQ/RRykmMOU4NBoulW1JaQ6iKPoQzSRBHtPjdPIWKRhFMzidzwjMhcGqZRwkGLSKCWTck17N7MIguhVHcR9iSaWUAwM3KBRsUgTKZjFr506WnNjcIJy0igjg1IyKCOHSkV1A9mBBMLoRDidiaAnUXQkDJump0WalYJZAo4LAztVU9+VuMmgjPTqoM6gTG1CgWBsdCS8OoTD6UoEHQj3hq8LN3Zsaocp0gIUzBLwTp96LcZJNuWcpJLc6j85VJCHA5efja+DsNGWEGIJIYEwOhNBNyJoRyh2bJqWFjGBglmkDp5AsvHjpiU3BsU4OUkFOVSSQyW5VJBLJUU4qbBgC5QgbLQhmFhCiSXE+992hBJHKFEEeUe9bgwMFMIiZlMwizRSVWgb2LDV2GnsxqAcF6W4KMVJMS7KcFb/veq2sur/r6xe/Taqw9Dgx2A89TbP/wOEYCe0jj8RBHn/hFf/N5og2hJCFMHe4PXUDTaFr4iFKZhFWsiPQUitEG/+16n6b9Xr6FKIIr5MwSwiImIhdrMLEBERkR8pmEVERCxEwSwiImIhCmYRERELUTCLiIhYiIJZRETEQhTMIiIiFqJgFhERsRAFs4iIiIUomEVERCxEwSwiImIhCmYRERELUTCLiIhYiIJZRETEQhTMIiIiFqJgFhERsRAFs4iIiIUomEVERCxEwSwiImIhCmYRERELUTCLiIhYiIJZRETEQhTMIiIiFqJgFhERsRAFs4iIiIUomEVERCxEwSwiImIhCmYRERELUTCLiIhYiIJZRETEQhTMIiIiFqJgFhERsRAFs4iIiIUomEVERCxEwSwiImIhCmYRERELUTCLiIhYiIJZRETEQhTMIiIiFqJgFhERsRAFs4iIiIUomEVERCxEwSwiImIhCmYRERELUTCLiIhYyP8HhmEx0LQHi1QAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def create_range_series(number_series):\n",
        "    \"\"\"Creates a series with range(group) for the numeric values\n",
        "    provided in another series which is passed as an argument.\n",
        "    This function takes only one argument which is (Pandas) series object,\n",
        "    returns another (Pandas) series object.\n",
        "\n",
        "    Argument:\n",
        "        number_series - A column in pandas data frame with numeric values.\n",
        "    \"\"\"\n",
        "    condition = [\n",
        "    (number_series >= 0) & (number_series < 5),\n",
        "    (number_series >= 5) & (number_series < 10),\n",
        "    (number_series >= 10) & (number_series < 15),\n",
        "    (number_series >= 15) & (number_series < 20),\n",
        "    (number_series >= 20) & (number_series < 25),\n",
        "    (number_series >= 25) & (number_series < 30),\n",
        "    (number_series >= 30) & (number_series < 35),\n",
        "    (number_series >= 35) & (number_series < 40),\n",
        "    (number_series >= 40) & (number_series < 45),\n",
        "    (number_series >= 45) & (number_series < 50),\n",
        "    (number_series >= 50) & (number_series < 55),\n",
        "    (number_series >= 55) & (number_series < 60),\n",
        "    (number_series >= 60) & (number_series < 65),\n",
        "    (number_series >= 65) & (number_series < 70),\n",
        "    (number_series >= 70) & (number_series < 75),\n",
        "    (number_series >= 75) & (number_series < 80),\n",
        "    (number_series >= 80) & (number_series < 85),\n",
        "    (number_series >= 85) & (number_series < 90),\n",
        "    (number_series >= 90) & (number_series < 95),\n",
        "    (number_series >= 95) & (number_series < 100)\n",
        "    ]\n",
        "\n",
        "    output = ['0-5',\n",
        "              '5-10',\n",
        "              '10-15',\n",
        "              '15-20',\n",
        "              '20-25',\n",
        "              '25-30',\n",
        "              '30-35',\n",
        "              '35-40',\n",
        "              '40-45',\n",
        "              '45-50',\n",
        "              '50-55',\n",
        "              '55-60',\n",
        "              '60-65',\n",
        "              '65-70',\n",
        "              '70-75',\n",
        "              '75-80',\n",
        "              '80-85',\n",
        "              '85-90',\n",
        "              '90-95',\n",
        "              '95-100'\n",
        "              ]\n",
        "    result = np.select(condition, output, '>100')\n",
        "    return pd.Series(result)\n",
        "#to create a column with age group\n",
        "heart_failure_df['age_group'] = create_range_series(heart_failure_df.age)\n",
        "heart_failure_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "o8jc55ig_W-7",
        "outputId": "c8ba77ae-1178-4d3d-dcb5-0edaeca375b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     age  anaemia  diabetes  ejection_fraction  high_blood_pressure  \\\n",
              "0     75    False     False                 20                 True   \n",
              "1     55    False     False                 38                False   \n",
              "2     65    False     False                 20                False   \n",
              "3     50     True     False                 20                False   \n",
              "4     65     True      True                 20                False   \n",
              "..   ...      ...       ...                ...                  ...   \n",
              "294   62    False      True                 38                 True   \n",
              "295   55    False     False                 38                False   \n",
              "296   45    False      True                 60                False   \n",
              "297   45    False     False                 38                False   \n",
              "298   50    False     False                 45                False   \n",
              "\n",
              "     platelets  serum_creatinine  serum_sodium     sex  smoking  patient_dead  \\\n",
              "0          265               1.9           130    Male    False          True   \n",
              "1          263               1.1           136    Male    False          True   \n",
              "2          162               1.3           129    Male     True          True   \n",
              "3          210               1.9           137    Male    False          True   \n",
              "4          327               2.7           116  Female    False          True   \n",
              "..         ...               ...           ...     ...      ...           ...   \n",
              "294        155               1.1           143    Male     True         False   \n",
              "295        270               1.2           139  Female    False         False   \n",
              "296        742               0.8           138  Female    False         False   \n",
              "297        140               1.4           140    Male     True         False   \n",
              "298        395               1.6           136    Male     True         False   \n",
              "\n",
              "    age_group  \n",
              "0       75-80  \n",
              "1       55-60  \n",
              "2       65-70  \n",
              "3       50-55  \n",
              "4       65-70  \n",
              "..        ...  \n",
              "294     60-65  \n",
              "295     55-60  \n",
              "296     45-50  \n",
              "297     45-50  \n",
              "298     50-55  \n",
              "\n",
              "[299 rows x 12 columns]"
            ],
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              "      <td>270</td>\n",
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              "<p>299 rows × 12 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-eea5b906-743d-4151-858a-51d087088da7')\"\n",
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            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dead_patients=heart_failure_df[heart_failure_df.patient_dead==True].groupby('age_group').count()\n",
        "alive_patients=heart_failure_df[heart_failure_df.patient_dead==False].groupby('age_group').count()"
      ],
      "metadata": {
        "id": "itmwiPzA_sp5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,10))\n",
        "sns.barplot(x=dead_patients.index,y=dead_patients.patient_dead,alpha=1,palette=['red'])\n",
        "sns.barplot(x=alive_patients.index,y=alive_patients.patient_dead,alpha=0.5,palette=['aquamarine'],estimator=sum,ci=None)\n",
        "plt.title(\"Dead or Alive\")\n",
        "plt.xlabel('Age group of Patients')\n",
        "dead=mpatches.Patch(color='red',label='Dead')\n",
        "alive= mpatches.Patch(color='aquamarine',label='Alive')\n",
        "plt.legend(handles=[dead,alive])\n",
        "plt.ylabel('Number of Patients');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 680
        },
        "id": "0A3K35JuDR2Y",
        "outputId": "1a6e928b-acd8-4dea-d2e1-e662c2d3c5b4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-62-64480c701d0e>:3: FutureWarning: \n",
            "\n",
            "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
            "\n",
            "  sns.barplot(x=alive_patients.index,y=alive_patients.patient_dead,alpha=0.5,palette=['aquamarine'],estimator=sum,ci=None)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1000 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(x=heart_failure_df.patient_dead,hue=heart_failure_df.sex, palette=['lightskyblue','plum'])\n",
        "plt.title('Dead or Alive')\n",
        "plt.xlabel('Patient Dead')\n",
        "plt.ylabel('Number of Patients');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 413
        },
        "id": "qLMQumZBEsCl",
        "outputId": "cddc0a05-92cd-4dc1-aef0-b8927696d315"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "heart_failure_df['abnormal_ef']= np.where(((heart_failure_df.ejection_fraction>=55)& (heart_failure_df.ejection_fraction<=70)), 'Normal', 'Abnormal')\n",
        "heart_failure_df['abnormal_platelets'] = np.where(((heart_failure_df.platelets >= 150) & (heart_failure_df.platelets <= 400)) , 'Normal', 'Abnormal')\n",
        "heart_failure_df['abnormal_creatinine'] = np.where(((heart_failure_df.serum_creatinine >= 0.6) & (heart_failure_df.serum_creatinine <= 1.2)), 'Normal','Abnormal')\n",
        "heart_failure_df['abnormal_sodium'] = np.where(((heart_failure_df.serum_sodium >= 135) & (heart_failure_df.serum_sodium <= 145)) , 'Normal', 'Abnormal')"
      ],
      "metadata": {
        "id": "1Vhz3w5KFPav"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axis=plt.subplots(2,4,figsize=(24,12))\n",
        "#axis(0,0) use this axis for Anaemia\n",
        "axis[0,0].set_title(\" Patients with Anaemia\")\n",
        "sns.countplot(x = heart_failure_df.anaemia, ax=axis[0,0], palette=['aquamarine', 'lightcoral'] )\n",
        "axis[0,0].set_xlabel(\"\")\n",
        "axis[0,0].set_ylabel(\"Number of Patients\")\n",
        "axis[0,0].set_ylim([0, 220])\n",
        "\n",
        "#axis(0,1) use this axis for Diabetes\n",
        "axis[0,1].set_title(\" Patients with Diabetes\")\n",
        "sns.countplot(x = heart_failure_df.diabetes, ax=axis[0,1], palette=['aquamarine', 'lightcoral'])\n",
        "axis[0,1].set_xlabel(\"\")\n",
        "axis[0,1].set_ylabel(\"Number of Patients\")\n",
        "axis[0,1].set_ylim([0, 220])\n",
        "\n",
        "\n",
        "#axis(0,2) use this axis for High blood pressure\n",
        "axis[0,2].set_title(\" Patients with High Blood Pressure\")\n",
        "sns.countplot(x = heart_failure_df.high_blood_pressure, ax=axis[0,2], palette=['aquamarine', 'lightcoral'])\n",
        "axis[0,2].set_xlabel(\"\")\n",
        "axis[0,2].set_ylabel(\"Number of Patients\")\n",
        "axis[0,2].set_ylim([0, 220])\n",
        "\n",
        "#axis(0,3) use this axis for smoking habit\n",
        "axis[0,3].set_title(\" Patients with Smoking Habit\")\n",
        "sns.countplot(x = heart_failure_df.smoking, ax=axis[0,3], palette=['aquamarine', 'lightcoral'])\n",
        "axis[0,3].set_xlabel(\"\")\n",
        "axis[0,3].set_ylabel(\"Number of Patients\")\n",
        "axis[0,3].set_ylim([0, 220])\n",
        "\n",
        "\n",
        "#axis(1,0) use this axis for Ejection Fraction\n",
        "axis[1,0].set_title(\" Patients with Abnormal EF\")\n",
        "sns.countplot(x = heart_failure_df.abnormal_ef.sort_values(ascending =False) , ax=axis[1,0], palette=['aquamarine', 'lightcoral'])\n",
        "axis[1,0].set_xlabel(\"\")\n",
        "axis[1,0].set_ylabel(\"Number of Patients\")\n",
        "axis[1,0].set_ylim([0, 270])\n",
        "\n",
        "#axis(1,1) use this axis for Platelets count\n",
        "axis[1,1].set_title(\" Patients with Abnormal Platelets Count\")\n",
        "sns.countplot(x = heart_failure_df.abnormal_platelets.sort_values(ascending =False) , ax=axis[1,1], palette=['aquamarine', 'lightcoral'])\n",
        "axis[1,1].set_xlabel(\"\")\n",
        "axis[1,1].set_ylabel(\"Number of Patients\")\n",
        "axis[1,1].set_ylim([0, 270])\n",
        "\n",
        "#axis(1,2) use this axis for Creatinine level\n",
        "axis[1,2].set_title(\" Patients with Abnormal Creatinine level\")\n",
        "sns.countplot(x = heart_failure_df.abnormal_creatinine.sort_values(ascending =False), ax=axis[1,2], palette=['aquamarine', 'lightcoral'])\n",
        "axis[1,2].set_xlabel(\"\")\n",
        "axis[1,2].set_ylabel(\"Number of Patients\")\n",
        "axis[1,2].set_ylim([0, 270])\n",
        "\n",
        "#axis(1,3) use this axis for sodium level\n",
        "axis[1,3].set_title(\" Patients with Abnormal Sodium level\")\n",
        "sns.countplot(x = heart_failure_df.abnormal_sodium.sort_values(ascending =False), ax=axis[1,3], palette=['aquamarine', 'lightcoral'])\n",
        "axis[1,3].set_xlabel(\"\")\n",
        "axis[1,3].set_ylabel(\"Number of Patients\")\n",
        "axis[1,3].set_ylim([0, 270])\n",
        "\n",
        "#to provide spacing between adjacent plots\n",
        "plt.tight_layout(pad=2);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
        },
        "id": "CqCDWejhGJXy",
        "outputId": "266c4f2c-df4c-4b83-ff61-c0291ca407c5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2400x1200 with 8 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#pair wise relationship\n",
        "#filter columns with numeric value\n",
        "numeric_column= heart_failure_df[['age','ejection_fraction','platelets','serum_creatinine','serum_sodium']]\n",
        "sns.pairplot(numeric_column);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 662
        },
        "id": "9VzRjsCsGb3W",
        "outputId": "91d03851-0ecc-42a3-9706-80b91533148d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1250x1250 with 30 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.title(\"Distribution of Ejection Fraction\")\n",
        "sns.histplot(heart_failure_df.ejection_fraction, kde= True, color='purple')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "qVUm_OebHEaY",
        "outputId": "0bc634e3-f379-48ed-c74a-5eeaca088bcf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': 'Distribution of Ejection Fraction'}, xlabel='ejection_fraction', ylabel='Count'>"
            ]
          },
          "metadata": {},
          "execution_count": 68
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.title(\"Distribution of Platelets count\")\n",
        "sns.histplot(heart_failure_df.platelets, kde= True, color='purple')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 454
        },
        "id": "EDxhsFwYHkjL",
        "outputId": "f1b1d607-88b7-444c-de45-d7a6fa365805"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': 'Distribution of Platelets count'}, xlabel='platelets', ylabel='Count'>"
            ]
          },
          "metadata": {},
          "execution_count": 69
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.title(\"Distribution of Creatinine Level in the blood\")\n",
        "sns.histplot(heart_failure_df.serum_creatinine, kde= True,bins=30, color='purple');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "id": "nriiuZk4HxkO",
        "outputId": "f9e5d9b2-0726-486d-9235-750d2ab5405a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.title(\"Distribution of Sodium Level in the blood\")\n",
        "sns.histplot(heart_failure_df.serum_sodium, kde= True, color='purple');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 420
        },
        "id": "8F-tB2WrH6R9",
        "outputId": "42af2908-3d5b-4bd3-e48c-221362a4eaf3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}