MiningMassiveDataSetsFinal.ipynb

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      "cell_type": "markdown",
      "source": [
        "This project will focus on solving Heart Failure prediction using PySpark and [Heart Failure Prediction - Clinical Records](https://www.kaggle.com/datasets/aadarshvelu/heart-failure-prediction-clinical-records/data) data set from Kaggle\n"
      ],
      "metadata": {
        "id": "nnaBJK726J9x"
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    {
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      "source": [
        "This dataset contains the medical records of 5000 patients who had heart failure, collected during their follow-up period, where each patient profile has 13 clinical features."
      ],
      "metadata": {
        "id": "2tYuyMhQ8QyZ"
      }
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        "Attribute Information:\n",
        "\n",
        "\n",
        "*   age: age of the patient (years)\n",
        "*   anaemia: decrease of red blood cells or hemoglobin (boolean)\n",
        "*   creatinine phosphokinase (CPK): level of the CPK enzyme in the blood (mcg/L)\n",
        "*   diabetes: if the patient has diabetes (boolean)\n",
        "*   ejection fraction: percentage of blood leaving the heart at each contraction (percentage)\n",
        "*   high blood pressure: if the patient has hypertension (boolean)\n",
        "*   platelets: platelets in the blood (kiloplatelets/mL)\n",
        "*   sex: woman or man (binary)\n",
        "*   serum creatinine: level of serum creatinine in the blood (mg/dL)\n",
        "*   serum sodium: level of serum sodium in the blood (mEq/L)\n",
        "*   smoking: if the patient smokes or not (boolean)\n",
        "*   time: follow-up period (days)\n",
        "*   [TARGET] DEATH_EVENT: if the patient died during the follow-up period (boolean)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "bULvwEbH8Tkv"
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    {
      "cell_type": "markdown",
      "source": [
        "This project will focus on finding the model for predicting survival of a patient with heart failure"
      ],
      "metadata": {
        "id": "NJBOcunb-s_B"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "As this is classification problem (binnary classification) I will implement XGBoost Classfier"
      ],
      "metadata": {
        "id": "3xmzIA3O_lxU"
      }
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    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from google.colab import drive"
      ],
      "metadata": {
        "id": "vdUOaGO46QDI"
      },
      "execution_count": null,
      "outputs": []
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    {
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          "text": [
            "Mounted at /content/gdrive\n"
          ]
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    {
      "cell_type": "code",
      "source": [
        "path = 'gdrive/My Drive/data/heart_failure_clinical_records.csv'"
      ],
      "metadata": {
        "id": "Elw3fPEbCRTG"
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      "execution_count": null,
      "outputs": []
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      "cell_type": "code",
      "source": [
        "data = pd.read_csv(path)"
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        "id": "YtWvSTNEA1tU"
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5000 entries, 0 to 4999\n",
            "Data columns (total 13 columns):\n",
            " #   Column                    Non-Null Count  Dtype  \n",
            "---  ------                    --------------  -----  \n",
            " 0   age                       5000 non-null   float64\n",
            " 1   anaemia                   5000 non-null   int64  \n",
            " 2   creatinine_phosphokinase  5000 non-null   int64  \n",
            " 3   diabetes                  5000 non-null   int64  \n",
            " 4   ejection_fraction         5000 non-null   int64  \n",
            " 5   high_blood_pressure       5000 non-null   int64  \n",
            " 6   platelets                 5000 non-null   float64\n",
            " 7   serum_creatinine          5000 non-null   float64\n",
            " 8   serum_sodium              5000 non-null   int64  \n",
            " 9   sex                       5000 non-null   int64  \n",
            " 10  smoking                   5000 non-null   int64  \n",
            " 11  time                      5000 non-null   int64  \n",
            " 12  DEATH_EVENT               5000 non-null   int64  \n",
            "dtypes: float64(3), int64(10)\n",
            "memory usage: 507.9 KB\n"
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        "data.head(10)"
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      "execution_count": null,
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              "    age  anaemia  creatinine_phosphokinase  diabetes  ejection_fraction  \\\n",
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              "3  60.0        1                       754         1                 40   \n",
              "4  95.0        1                       582         0                 30   \n",
              "5  70.0        0                       232         1                 30   \n",
              "6  63.0        1                       122         1                 60   \n",
              "7  70.0        1                       171         0                 50   \n",
              "8  50.0        0                       482         1                 30   \n",
              "9  53.0        1                       446         0                 45   \n",
              "\n",
              "   high_blood_pressure  platelets  serum_creatinine  serum_sodium  sex  \\\n",
              "0                    0  263358.03               1.3           137    1   \n",
              "1                    0  305000.00               5.0           130    1   \n",
              "2                    0  319000.00               0.9           140    0   \n",
              "3                    1  328000.00               1.2           126    1   \n",
              "4                    0  461000.00               2.0           132    1   \n",
              "5                    0  302000.00               1.2           132    1   \n",
              "6                    0  172000.00               1.2           145    0   \n",
              "7                    1  358000.00               0.9           141    0   \n",
              "8                    0  300000.00               0.9           132    1   \n",
              "9                    1  274000.00               1.0           133    1   \n",
              "\n",
              "   smoking  time  DEATH_EVENT  \n",
              "0        1    88            0  \n",
              "1        0   207            0  \n",
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              "4        0    50            1  \n",
              "5        0   210            0  \n",
              "6        0   147            0  \n",
              "7        0   196            0  \n",
              "8        0   109            0  \n",
              "9        0   215            0  "
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              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-cd8845ad-40b5-4dd9-9d30-cd6afd595982 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 5000,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 11.697242810508323,\n        \"min\": 40.0,\n        \"max\": 95.0,\n        \"num_unique_values\": 48,\n        \"samples\": [\n          41.0,\n          62.0,\n          56.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"anaemia\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"creatinine_phosphokinase\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 976,\n        \"min\": 23,\n        \"max\": 7861,\n        \"num_unique_values\": 290,\n        \"samples\": [\n          280,\n          7861\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"diabetes\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ejection_fraction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 11,\n        \"min\": 14,\n        \"max\": 80,\n        \"num_unique_values\": 17,\n        \"samples\": [\n          45,\n          25\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"high_blood_pressure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"platelets\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 97999.75862160046,\n        \"min\": 25100.0,\n        \"max\": 850000.0,\n        \"num_unique_values\": 203,\n        \"samples\": [\n          70000.0,\n          274000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"serum_creatinine\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.0097500778945063,\n        \"min\": 0.5,\n        \"max\": 9.4,\n        \"num_unique_values\": 43,\n        \"samples\": [\n          3.8,\n          2.2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"serum_sodium\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4,\n        \"min\": 113,\n        \"max\": 148,\n        \"num_unique_values\": 27,\n        \"samples\": [\n          136,\n          135\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"smoking\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"time\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 77,\n        \"min\": 4,\n        \"max\": 285,\n        \"num_unique_values\": 155,\n        \"samples\": [\n          145,\n          105\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DEATH_EVENT\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Check for null values\n",
        "null_values_count = data.isnull().sum()\n",
        "\n",
        "null_values_count"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5LVOqom0QgrH",
        "outputId": "15c31432-2f62-4057-a9ff-5b20f8a79623"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age                         0\n",
              "anaemia                     0\n",
              "creatinine_phosphokinase    0\n",
              "diabetes                    0\n",
              "ejection_fraction           0\n",
              "high_blood_pressure         0\n",
              "platelets                   0\n",
              "serum_creatinine            0\n",
              "serum_sodium                0\n",
              "sex                         0\n",
              "smoking                     0\n",
              "time                        0\n",
              "DEATH_EVENT                 0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "RYDMsR17RMlP",
        "outputId": "d2678c92-42da-42ea-d55e-1af25e789cc9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               age      anaemia  creatinine_phosphokinase     diabetes  \\\n",
              "count  5000.000000  5000.000000               5000.000000  5000.000000   \n",
              "mean     60.288736     0.474400                586.760600     0.439400   \n",
              "std      11.697243     0.499394                976.733979     0.496364   \n",
              "min      40.000000     0.000000                 23.000000     0.000000   \n",
              "25%      50.000000     0.000000                121.000000     0.000000   \n",
              "50%      60.000000     0.000000                248.000000     0.000000   \n",
              "75%      68.000000     1.000000                582.000000     1.000000   \n",
              "max      95.000000     1.000000               7861.000000     1.000000   \n",
              "\n",
              "       ejection_fraction  high_blood_pressure      platelets  \\\n",
              "count        5000.000000          5000.000000    5000.000000   \n",
              "mean           37.734600             0.364800  265075.404370   \n",
              "std            11.514855             0.481422   97999.758622   \n",
              "min            14.000000             0.000000   25100.000000   \n",
              "25%            30.000000             0.000000  215000.000000   \n",
              "50%            38.000000             0.000000  263358.030000   \n",
              "75%            45.000000             1.000000  310000.000000   \n",
              "max            80.000000             1.000000  850000.000000   \n",
              "\n",
              "       serum_creatinine  serum_sodium          sex      smoking         time  \\\n",
              "count       5000.000000   5000.000000  5000.000000  5000.000000  5000.000000   \n",
              "mean           1.369106    136.808200     0.645600     0.311800   130.678800   \n",
              "std            1.009750      4.464236     0.478379     0.463275    77.325928   \n",
              "min            0.500000    113.000000     0.000000     0.000000     4.000000   \n",
              "25%            0.900000    134.000000     0.000000     0.000000    74.000000   \n",
              "50%            1.100000    137.000000     1.000000     0.000000   113.000000   \n",
              "75%            1.400000    140.000000     1.000000     1.000000   201.000000   \n",
              "max            9.400000    148.000000     1.000000     1.000000   285.000000   \n",
              "\n",
              "       DEATH_EVENT  \n",
              "count  5000.000000  \n",
              "mean      0.313600  \n",
              "std       0.464002  \n",
              "min       0.000000  \n",
              "25%       0.000000  \n",
              "50%       0.000000  \n",
              "75%       1.000000  \n",
              "max       1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1da7fe7f-e103-463e-aff0-e2a4615561b3\" class=\"colab-df-container\">\n",
              "    <div>\n",
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              "<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>creatinine_phosphokinase</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>time</th>\n",
              "      <th>DEATH_EVENT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>5000.000000</td>\n",
              "      <td>5000.000000</td>\n",
              "      <td>5000.000000</td>\n",
              "      <td>5000.000000</td>\n",
              "      <td>5000.000000</td>\n",
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              "      <td>5000.000000</td>\n",
              "      <td>5000.000000</td>\n",
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              "      <td>5000.000000</td>\n",
              "      <td>5000.000000</td>\n",
              "      <td>5000.000000</td>\n",
              "      <td>5000.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>60.288736</td>\n",
              "      <td>0.474400</td>\n",
              "      <td>586.760600</td>\n",
              "      <td>0.439400</td>\n",
              "      <td>37.734600</td>\n",
              "      <td>0.364800</td>\n",
              "      <td>265075.404370</td>\n",
              "      <td>1.369106</td>\n",
              "      <td>136.808200</td>\n",
              "      <td>0.645600</td>\n",
              "      <td>0.311800</td>\n",
              "      <td>130.678800</td>\n",
              "      <td>0.313600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>11.697243</td>\n",
              "      <td>0.499394</td>\n",
              "      <td>976.733979</td>\n",
              "      <td>0.496364</td>\n",
              "      <td>11.514855</td>\n",
              "      <td>0.481422</td>\n",
              "      <td>97999.758622</td>\n",
              "      <td>1.009750</td>\n",
              "      <td>4.464236</td>\n",
              "      <td>0.478379</td>\n",
              "      <td>0.463275</td>\n",
              "      <td>77.325928</td>\n",
              "      <td>0.464002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>40.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>25100.000000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>113.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>121.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>215000.000000</td>\n",
              "      <td>0.900000</td>\n",
              "      <td>134.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>74.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>60.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>248.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>263358.030000</td>\n",
              "      <td>1.100000</td>\n",
              "      <td>137.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>113.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>68.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>582.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>45.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>310000.000000</td>\n",
              "      <td>1.400000</td>\n",
              "      <td>140.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>201.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>95.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>7861.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>850000.000000</td>\n",
              "      <td>9.400000</td>\n",
              "      <td>148.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>285.000000</td>\n",
              "      <td>1.000000</td>\n",
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              "        if (!dataTable) return;\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
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              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-17f5029e-e492-4117-ba25-f54c008f10f6 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1748.4834779108014,\n        \"min\": 11.697242810508323,\n        \"max\": 5000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          60.288736400000005,\n          60.0,\n          5000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"anaemia\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1767.6168026198684,\n        \"min\": 0.0,\n        \"max\": 5000.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.4744,\n          1.0,\n          0.499394151851802\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"creatinine_phosphokinase\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2899.9953658878185,\n        \"min\": 23.0,\n        \"max\": 7861.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          586.7606,\n          248.0,\n          5000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"diabetes\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1767.6187233311093,\n        \"min\": 0.0,\n        \"max\": 5000.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.4394,\n          1.0,\n          0.4963636926519471\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ejection_fraction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1754.952246013878,\n        \"min\": 11.514854806563703,\n        \"max\": 5000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          37.7346,\n          38.0,\n          5000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"high_blood_pressure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1767.6232458344928,\n        \"min\": 0.0,\n        \"max\": 5000.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.3648,\n          1.0,\n          0.4814221779921367\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"platelets\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 266944.4820233389,\n        \"min\": 5000.0,\n        \"max\": 850000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          265075.40437,\n          263358.03,\n          5000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"serum_creatinine\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1766.977491393267,\n        \"min\": 0.5,\n        \"max\": 5000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1.369106,\n          1.1,\n          5000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"serum_sodium\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1727.3211034849526,\n        \"min\": 4.464235504510032,\n        \"max\": 5000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          136.8082,\n          137.0,\n          5000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1767.5587097168686,\n        \"min\": 0.0,\n        \"max\": 5000.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.6456,\n          1.0,\n          0.47837893900323036\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"smoking\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1767.6268394786903,\n        \"min\": 0.0,\n        \"max\": 5000.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.3118,\n          1.0,\n          0.46327495587064427\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"time\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1725.1825231497426,\n        \"min\": 4.0,\n        \"max\": 5000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          130.6788,\n          113.0,\n          5000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DEATH_EVENT\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1767.6267118221629,\n        \"min\": 0.0,\n        \"max\": 5000.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.3136,\n          1.0,\n          0.46400226251595367\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Data visualization\n",
        "for column in data.columns:\n",
        "  data[column].plot(kind='hist', bins=20, title=column)\n",
        "  plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "F9maHOXaVD7n",
        "outputId": "3f8b028b-63ab-4027-bb9e-2aaff1ee4b83"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "deceased_df = data[data['DEATH_EVENT'] == 1]\n",
        "for column in data.columns:\n",
        "  plt.figure(figsize=(10,5))\n",
        "  sns.histplot(data=deceased_df, x=column, bins=20)\n",
        "  plt.title(f'Number of deaths per {column} distribution')\n",
        "  plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "v8Tk2XEVU9V1",
        "outputId": "42a1de17-e865-4b25-a410-67b2cf12af08"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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1Up06ddS5c2c98MADuvPOO/O1D2d+nvlx/vx5hzBo16pVq7+cIOPtt9+Wj4+PbrnlFh09elTSn2GpZs2aWrVqlbp3717gelxdXRUZGVng9W7Ex8cnX9uMjo7WSy+9pLi4OD311FP69ddftWvXLo0ZMybXAFGtWrUC1erq6qpJkyYpJiZG69evdwgaReGXX36RlPOcc3d31y233HLDdT09PfX888/r8ccfV1BQkFq3bq0ePXpo8ODBCg4OzncNBTk369Spk+Pnzz6T4/Hjxwu034Kwv0/X/w6SpPr16+u///2vQ5uXl5eqVKni0FaxYsW/FUqBmw1hC0CubrnlFg0cOFBLly7N9fmCvCZ+uNGD0bn9oyyvv/QW5q/b9qscL7zwQp7TmV8fbK5/1qQksh/XE088oaioqFzH2KcRnzlzpiZPnqx//etfeuaZZxQQECAXFxeNHTs2x1WgG8nP59KgQQMdPnxYGzZs0KZNm/T+++9r8eLFmjJliqZPn57vfeXFmZ9nZmamfvzxx0J9t5xhGFq9erUuXLighg0b5uhPSUnR+fPnb/i9WSVN8+bNVb9+fa1evVpPPfWUVq9eLcMwcsxC+HdER0frmWee0YwZM9S7d+8i225RGDt2rHr27Kn169dr8+bNmjx5smbNmqVt27bp9ttvz9c2ivp3TWF+Bxc1Z86kCJQWhC0AeZo0aZLefvttPf/88zn67FcTrn9g2v6XUSvYr3TYGYaho0ePmlNo165dW9Kft9wU9RWAGjVq6PDhwznaf/jhB7O/MNvcunVrjn94X78f+1/e3d3d//K43nvvPXXo0EFvvPGGQ3tqaqrDFcS/miUxv3x8fNS/f3/1799fV65cUZ8+ffTcc88pNjb2L6eUdubn+Vfee+89Xbp0Kc9weyM7duzQr7/+qhkzZjh8B5T058Qjw4cP1/r164t1iveiEB0drcmTJ2v//v2Ki4tT3bp1zVkti4L96taDDz6oDz74oMi2K/3fz+eRI0ccvjstMzNTx44dU9OmTf9yG7Vr19bjjz+uxx9/XEeOHFGzZs304osv6u2335ZUdD9T0v9dzb52mz/++KOkP2/9lBx/B1/7VRO5/Q7Ob2329+nw4cM5vmPu8OHDhfo9B5R1PLMFIE+1a9fWwIED9dprr+V4TsDX11eVK1fOMWvg4sWLLavnzTffdHiG5r333tP//vc/de3aVdKff32vXbu25s6dq/Pnz+dY//fffy/0vrt166a9e/cqPj7ebLtw4YKWLl2qmjVr5noFIz/bvHr1ql599VWzLSsrK8cXSgcGBqp9+/Z67bXXcn2G7trjcnV1zXFVcM2aNTmmbbZ//1Re08znx/W3enp4eKhhw4YyDEOZmZl/ub4zP88b+fbbbzV27FhVrFhRI0eOLPD69lsIx48fr379+jksw4YNU926df/2rITOYL+KNWXKFCUmJhbpVS27gQMHqk6dOkVyZfRaLVq0UJUqVbRkyRKHGRFXrFjxlz8DFy9e1OXLlx3aateurQoVKigjI8Ns8/Hx+Vs/T9c6deqUwyyj6enpevPNN9WsWTPzFkL7HyOu/R184cIFrVy5Msf28ltbixYtFBgYqCVLljgc2yeffKJDhw4V6vZXoKzjyhaAG3r66af11ltv6fDhw2rUqJFD30MPPaTZs2froYceUosWLbRz507zr69WCAgIUJs2bTRkyBAlJydr/vz5qlOnjjnFt4uLi/7f//t/6tq1qxo1aqQhQ4aoatWq+u233/T555/L19dXH330UaH2PXHiRK1evVpdu3bVmDFjFBAQoJUrV+rYsWN6//33zUkpCqJnz5668847NXHiRB0/ftz8Lp20tLQcYxctWqQ2bdqocePGGjZsmG655RYlJycrPj5ev/76q/k9Wj169NCMGTM0ZMgQ3XHHHTpw4IBWrVqV47mU2rVry9/fX0uWLFGFChXk4+Oj8PDwAj1X0rlzZwUHB+vOO+9UUFCQDh06pFdeeUXdu3fP9Vmn6znz87TbtWuXLl++bE4m8sUXX+jDDz+Un5+f1q1bl+uzMZ988ol5RfNad9xxh6pWrar3339fnTp1yvPK3j333KMFCxYoJSVFgYGBf6v+vystLc28MnO966+81apVS3fccYd51elGYevHH3/MdbtBQUE5vqD4Wq6urnr66ac1ZMiQ/JSfb+7u7nr22Wf18MMP6+6771b//v117NgxLV++/C+f2frxxx/VsWNH3XfffWrYsKHc3Ny0bt06JScna8CAAea45s2b69VXX9Wzzz6rOnXqKDAwMMfVofy69dZbNXToUO3bt09BQUFatmyZkpOTtXz5cnNM586dVb16dQ0dOlTjx4+Xq6urli1bpipVqphT0he0Nnd3dz3//PMaMmSI2rVrp/vvv1/JyclasGCBatasqccee6xQxwOUac6ZBBFASXPt1O/Xs0/xe/003xcvXjSGDh1q+Pn5GRUqVDDuu+8+IyUlJc+p33///fcc27VP/Xyt66eZt09PvHr1aiM2NtYIDAw0vL29je7duxu//PJLjvW/+eYbo0+fPkalSpUMT09Po0aNGsZ9991nbN269S9rupGffvrJ6Nevn+Hv7294eXkZrVq1MjZs2JBjnAowDfcff/xhDBo0yPD19TX8/PyMQYMGGd98802u07L/9NNPxuDBg43g4GDD3d3dqFq1qtGjRw/jvffeM8dcvnzZePzxx42QkBDD29vbuPPOO434+HijXbt2OaZ+/uCDD4yGDRsabm5uDvu7/v23i4mJMWrUqGG+fu2114y2bdua73Pt2rWN8ePHG2lpaTc85pLwedprsC/u7u5GlSpVjLZt2xrPPfeckZKSkmOdG039bn//3n//fUOS8cYbb+S57+3btztMcW8Y+Zv6PbefFbuCnHN2N5r6Pa9/HixatMiQZLRq1eqGteS1XHsO5nVMmZmZRu3atYt06ne7xYsXG7Vq1TI8PT2NFi1aGDt37szxs3H91O+nT582Ro4cadSvX9/w8fEx/Pz8jPDwcOPdd9912HZSUpLRvXt3o0KFCg7HeqPfrXlN/d69e3dj8+bNRpMmTQxPT0+jfv36uX5NQUJCghEeHm54eHgY1atXN+bNm5frNvOq7fqp3+3eeecd4/bbbzc8PT2NgIAAIzo62vj1118dxuT1+eU1JT1QVtkMw8JvEAQA4Drbt29Xhw4dtGbNGvXr18/Z5QAAYBme2QIAAAAAC/DMFgAAN5Hff//9htN/e3h4KCAgoBgrAoCyi7AFAMBNpGXLljf8CoZ27dpp+/btxVcQAJRhPLMFAMBN5IsvvtClS5fy7K9YsaKaN29ejBUBQNlF2AIAAAAACzBBBgAAAABYgGe28ik7O1unTp1ShQoVZLPZnF0OAAAAACcxDEPnzp1TaGioXFzyvn5F2MqnU6dOKSwszNllAAAAACghTp48qWrVquXZT9jKpwoVKkj68w319fV1cjUAAAAAnCU9PV1hYWFmRsgLYSuf7LcO+vr6ErYAAAAA/OXjRUyQAQAAAAAWIGwBAAAAgAUIWwAAAABgAcIWAAAAAFjAqWFr586d6tmzp0JDQ2Wz2bR+/focYw4dOqR77rlHfn5+8vHxUcuWLXXixAmz//Llyxo5cqQqVaqk8uXLq2/fvkpOTnbYxokTJ9S9e3eVK1dOgYGBGj9+vK5evWr14QEAAAAow5wati5cuKCmTZtq0aJFufb/9NNPatOmjerXr6/t27dr//79mjx5sry8vMwxjz32mD766COtWbNGO3bs0KlTp9SnTx+zPysrS927d9eVK1e0e/durVy5UitWrNCUKVMsPz4AAAAAZZfNMAzD2UVIf06buG7dOvXu3dtsGzBggNzd3fXWW2/luk5aWpqqVKmiuLg49evXT5L0ww8/qEGDBoqPj1fr1q31ySefqEePHjp16pSCgoIkSUuWLNGECRP0+++/y8PDI1/1paeny8/PT2lpaUz9DgAAAJRh+c0GJfaZrezsbH388ce69dZbFRUVpcDAQIWHhzvcapiQkKDMzExFRkaabfXr11f16tUVHx8vSYqPj1fjxo3NoCVJUVFRSk9P18GDB/Pcf0ZGhtLT0x0WAAAAAMivEhu2UlJSdP78ec2ePVtdunTRp59+qnvvvVd9+vTRjh07JElJSUny8PCQv7+/w7pBQUFKSkoyx1wbtOz99r68zJo1S35+fuYSFhZWhEcHAAAA4GZXYsNWdna2JKlXr1567LHH1KxZM02cOFE9evTQkiVLLN9/bGys0tLSzOXkyZOW7xMAAADAzaPEhq3KlSvLzc1NDRs2dGhv0KCBORthcHCwrly5otTUVIcxycnJCg4ONsdcPzuh/bV9TG48PT3l6+vrsAAAAABAfpXYsOXh4aGWLVvq8OHDDu0//vijatSoIUlq3ry53N3dtXXrVrP/8OHDOnHihCIiIiRJEREROnDggFJSUswxW7Zska+vb44gBwAAAABFxc2ZOz9//ryOHj1qvj527JgSExMVEBCg6tWra/z48erfv7/atm2rDh06aNOmTfroo4+0fft2SZKfn5+GDh2qcePGKSAgQL6+vho9erQiIiLUunVrSVLnzp3VsGFDDRo0SHPmzFFSUpImTZqkkSNHytPT0xmHDQAAAKAMcOrU79u3b1eHDh1ytMfExGjFihWSpGXLlmnWrFn69ddfVa9ePU2fPl29evUyx16+fFmPP/64Vq9erYyMDEVFRWnx4sUOtwj+8ssvGjFihLZv3y4fHx/FxMRo9uzZcnPLf9Zk6ncAAAAAUv6zQYn5nq2SjrAFAJCkEydO6PTp084uQ9KfzzdXr17d2WUAQJmT32zg1NsIAQAoTU6cOKH69Rvo0qWLzi5FkuTtXU4//HCIwAUAJRRhCwCAfDp9+rQuXbqo8H9NlW9ITafWkv6/49qzbLpOnz5N2AKAEoqwBQBAAfmG1FRA9XrOLgMAUMKV2KnfAQAAAKA0I2wBAAAAgAUIWwAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFCFsAAAAAYAHCFgAAAABYgLAFAAAAABYgbAEAAACABQhbAAAAAGABwhYAAAAAWICwBQAAAAAWIGwBAAAAgAUIWwAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFCFsAAAAAYAHCFgAAAABYgLAFAAAAABYgbAEAAACABQhbAAAAAGABwhYAAAAAWICwBQAAAAAWIGwBAAAAgAUIWwAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFCFsAAAAAYAHCFgAAAABYwKlha+fOnerZs6dCQ0Nls9m0fv36PMc+8sgjstlsmj9/vkP7mTNnFB0dLV9fX/n7+2vo0KE6f/68w5j9+/frrrvukpeXl8LCwjRnzhwLjgYAAAAA/o9Tw9aFCxfUtGlTLVq06Ibj1q1bpy+//FKhoaE5+qKjo3Xw4EFt2bJFGzZs0M6dOzV8+HCzPz09XZ07d1aNGjWUkJCgF154QdOmTdPSpUuL/HgAAAAAwM7NmTvv2rWrunbtesMxv/32m0aPHq3Nmzere/fuDn2HDh3Spk2btG/fPrVo0UKS9PLLL6tbt26aO3euQkNDtWrVKl25ckXLli2Th4eHGjVqpMTERM2bN88hlAEAAABAUSrRz2xlZ2dr0KBBGj9+vBo1apSjPz4+Xv7+/mbQkqTIyEi5uLhoz5495pi2bdvKw8PDHBMVFaXDhw/r7Nmzee47IyND6enpDgsAAAAA5FeJDlvPP/+83NzcNGbMmFz7k5KSFBgY6NDm5uamgIAAJSUlmWOCgoIcxthf28fkZtasWfLz8zOXsLCwv3MoAAAAAMqYEhu2EhIStGDBAq1YsUI2m63Y9x8bG6u0tDRzOXnyZLHXAAAAAKD0KrFha9euXUpJSVH16tXl5uYmNzc3/fLLL3r88cdVs2ZNSVJwcLBSUlIc1rt69arOnDmj4OBgc0xycrLDGPtr+5jceHp6ytfX12EBAAAAgPwqsWFr0KBB2r9/vxITE80lNDRU48eP1+bNmyVJERERSk1NVUJCgrnetm3blJ2drfDwcHPMzp07lZmZaY7ZsmWL6tWrp4oVKxbvQQEAAAAoM5w6G+H58+d19OhR8/WxY8eUmJiogIAAVa9eXZUqVXIY7+7uruDgYNWrV0+S1KBBA3Xp0kXDhg3TkiVLlJmZqVGjRmnAgAHmNPEPPPCApk+frqFDh2rChAn67rvvtGDBAr300kvFd6AAAAAAyhynhq2vvvpKHTp0MF+PGzdOkhQTE6MVK1bkaxurVq3SqFGj1LFjR7m4uKhv375auHCh2e/n56dPP/1UI0eOVPPmzVW5cmVNmTKFad8BAAAAWMqpYat9+/YyDCPf448fP56jLSAgQHFxcTdcr0mTJtq1a1dBywMAAACAQiuxz2wBAAAAQGlG2AIAAAAACxC2AAAAAMAChC0AAAAAsABhCwAAAAAsQNgCAAAAAAsQtgAAAADAAoQtAAAAALAAYQsAAAAALEDYAgAAAAALELYAAAAAwAKELQAAAACwAGELAAAAACxA2AIAAAAACxC2AAAAAMAChC0AAAAAsABhCwAAAAAsQNgCAAAAAAsQtgAAAADAAoQtAAAAALAAYQsAAAAALEDYAgAAAAALELYAAAAAwAKELQAAAACwAGELAAAAACxA2AIAAAAACxC2AAAAAMAChC0AAAAAsABhCwAAAAAsQNgCAAAAAAsQtgAAAADAAoQtAAAAALAAYQsAAAAALEDYAgAAAAALELYAAAAAwAKELQAAAACwgFPD1s6dO9WzZ0+FhobKZrNp/fr1Zl9mZqYmTJigxo0by8fHR6GhoRo8eLBOnTrlsI0zZ84oOjpavr6+8vf319ChQ3X+/HmHMfv379ddd90lLy8vhYWFac6cOcVxeAAAAADKMKeGrQsXLqhp06ZatGhRjr6LFy/q66+/1uTJk/X1119r7dq1Onz4sO655x6HcdHR0Tp48KC2bNmiDRs2aOfOnRo+fLjZn56ers6dO6tGjRpKSEjQCy+8oGnTpmnp0qWWHx8AAACAssvNmTvv2rWrunbtmmufn5+ftmzZ4tD2yiuvqFWrVjpx4oSqV6+uQ4cOadOmTdq3b59atGghSXr55ZfVrVs3zZ07V6GhoVq1apWuXLmiZcuWycPDQ40aNVJiYqLmzZvnEMoAAAAAoCiVqme20tLSZLPZ5O/vL0mKj4+Xv7+/GbQkKTIyUi4uLtqzZ485pm3btvLw8DDHREVF6fDhwzp79mye+8rIyFB6errDAgAAAAD5VWrC1uXLlzVhwgTdf//98vX1lSQlJSUpMDDQYZybm5sCAgKUlJRkjgkKCnIYY39tH5ObWbNmyc/Pz1zCwsKK8nAAAAAA3ORKRdjKzMzUfffdJ8Mw9OqrrxbLPmNjY5WWlmYuJ0+eLJb9AgAAALg5OPWZrfywB61ffvlF27ZtM69qSVJwcLBSUlIcxl+9elVnzpxRcHCwOSY5OdlhjP21fUxuPD095enpWVSHAQAAAKCMKdFXtuxB68iRI/rss89UqVIlh/6IiAilpqYqISHBbNu2bZuys7MVHh5ujtm5c6cyMzPNMVu2bFG9evVUsWLF4jkQAAAAAGWOU8PW+fPnlZiYqMTEREnSsWPHlJiYqBMnTigzM1P9+vXTV199pVWrVikrK0tJSUlKSkrSlStXJEkNGjRQly5dNGzYMO3du1dffPGFRo0apQEDBig0NFSS9MADD8jDw0NDhw7VwYMH9c4772jBggUaN26csw4bAAAAQBng1NsIv/rqK3Xo0MF8bQ9AMTExmjZtmj788ENJUrNmzRzW+/zzz9W+fXtJ0qpVqzRq1Ch17NhRLi4u6tu3rxYuXGiO9fPz06effqqRI0eqefPmqly5sqZMmcK07wAAAAAs5dSw1b59exmGkWf/jfrsAgICFBcXd8MxTZo00a5duwpcHwAAAAAUVol+ZgsAAAAASivCFgAAAABYgLAFAAAAABYgbAEAAACABQhbAAAAAGABwhYAAAAAWICwBQAAAAAWIGwBAAAAgAUIWwAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFCFsAAAAAYAHCFgAAAABYgLAFAAAAABYgbAEAAACABQhbAAAAAGABwhYAAAAAWICwBQAAAAAWIGwBAAAAgAUIWwAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFCFsAAAAAYAHCFgAAAABYgLAFAAAAABYgbAEAAACABQhbAAAAAGABwhYAAAAAWICwBQAAAAAWIGwBAAAAgAUIWwAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFnBq2du7cqZ49eyo0NFQ2m03r16936DcMQ1OmTFFISIi8vb0VGRmpI0eOOIw5c+aMoqOj5evrK39/fw0dOlTnz593GLN//37ddddd8vLyUlhYmObMmWP1oQEAAAAo45wati5cuKCmTZtq0aJFufbPmTNHCxcu1JIlS7Rnzx75+PgoKipKly9fNsdER0fr4MGD2rJlizZs2KCdO3dq+PDhZn96ero6d+6sGjVqKCEhQS+88IKmTZumpUuXWn58AAAAAMouN2fuvGvXruratWuufYZhaP78+Zo0aZJ69eolSXrzzTcVFBSk9evXa8CAATp06JA2bdqkffv2qUWLFpKkl19+Wd26ddPcuXMVGhqqVatW6cqVK1q2bJk8PDzUqFEjJSYmat68eQ6hDAAAAACKUol9ZuvYsWNKSkpSZGSk2ebn56fw8HDFx8dLkuLj4+Xv728GLUmKjIyUi4uL9uzZY45p27atPDw8zDFRUVE6fPiwzp49m+f+MzIylJ6e7rAAAAAAQH6V2LCVlJQkSQoKCnJoDwoKMvuSkpIUGBjo0O/m5qaAgACHMblt49p95GbWrFny8/Mzl7CwsL93QAAAAADKlBIbtpwtNjZWaWlp5nLy5ElnlwQAAACgFCmxYSs4OFiSlJyc7NCenJxs9gUHByslJcWh/+rVqzpz5ozDmNy2ce0+cuPp6SlfX1+HBQAAAADyq8SGrVq1aik4OFhbt24129LT07Vnzx5FRERIkiIiIpSamqqEhARzzLZt25Sdna3w8HBzzM6dO5WZmWmO2bJli+rVq6eKFSsW09EAAAAAKGucGrbOnz+vxMREJSYmSvpzUozExESdOHFCNptNY8eO1bPPPqsPP/xQBw4c0ODBgxUaGqrevXtLkho0aKAuXbpo2LBh2rt3r7744guNGjVKAwYMUGhoqCTpgQcekIeHh4YOHaqDBw/qnXfe0YIFCzRu3DgnHTUAAACAssCpU79/9dVX6tChg/naHoBiYmK0YsUKPfnkk7pw4YKGDx+u1NRUtWnTRps2bZKXl5e5zqpVqzRq1Ch17NhRLi4u6tu3rxYuXGj2+/n56dNPP9XIkSPVvHlzVa5cWVOmTGHadwAAAACWcmrYat++vQzDyLPfZrNpxowZmjFjRp5jAgICFBcXd8P9NGnSRLt27Sp0nQAAAABQUCX2mS0AAAAAKM0IWwAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFCFsAAAAAYAHCFgAAAABYgLAFAAAAABYgbAEAAACABQhbAAAAAGABwhYAAAAAWICwBQAAAAAWIGwBAAAAgAUIWwAAAABgAcIWAAAAAFiAsAUAAAAAFihU2Lrlllv0xx9/5GhPTU3VLbfc8reLAgAAAIDSrlBh6/jx48rKysrRnpGRod9+++1vFwUAAAAApZ1bQQZ/+OGH5n9v3rxZfn5+5uusrCxt3bpVNWvWLLLiAAAAAKC0KlDY6t27tyTJZrMpJibGoc/d3V01a9bUiy++WGTFAQAAAEBpVaCwlZ2dLUmqVauW9u3bp8qVK1tSFAAAAACUdgUKW3bHjh0r6joAAAAA4KZSqLAlSVu3btXWrVuVkpJiXvGyW7Zs2d8uDAAAAABKs0KFrenTp2vGjBlq0aKFQkJCZLPZirouAAAAACjVChW2lixZohUrVmjQoEFFXQ8AAAAA3BQK9T1bV65c0R133FHUtQAAAADATaNQYeuhhx5SXFxcUdcCAAAAADeNQt1GePnyZS1dulSfffaZmjRpInd3d4f+efPmFUlxAAAAAFBaFSps7d+/X82aNZMkfffddw59TJYBAAAAAIUMW59//nlR1wEAAAAAN5VCPbMFAAAAALixQl3Z6tChww1vF9y2bVuhCwIAAACAm0Ghwpb9eS27zMxMJSYm6rvvvlNMTExR1AUAAAAApVqhwtZLL72Ua/u0adN0/vz5v1UQAAAAANwMivSZrYEDB2rZsmVFuUkAAAAAKJWKNGzFx8fLy8urKDcJAAAAAKVSocJWnz59HJZ7771XrVu31pAhQ/Twww8XWXFZWVmaPHmyatWqJW9vb9WuXVvPPPOMDMMwxxiGoSlTpigkJETe3t6KjIzUkSNHHLZz5swZRUdHy9fXV/7+/ho6dCi3OwIAAACwVKGe2fLz83N47eLionr16mnGjBnq3LlzkRQmSc8//7xeffVVrVy5Uo0aNdJXX32lIUOGyM/PT2PGjJEkzZkzRwsXLtTKlStVq1YtTZ48WVFRUfr+++/Nq2zR0dH63//+py1btigzM1NDhgzR8OHDFRcXV2S1AgAAAMC1ChW2li9fXtR15Gr37t3q1auXunfvLkmqWbOmVq9erb1790r686rW/PnzNWnSJPXq1UuS9OabbyooKEjr16/XgAEDdOjQIW3atEn79u1TixYtJEkvv/yyunXrprlz5yo0NLRYjgUAAABA2fK3ntlKSEjQ22+/rbffflvffPNNUdVkuuOOO7R161b9+OOPkqRvv/1W//3vf9W1a1dJ0rFjx5SUlKTIyEhzHT8/P4WHhys+Pl7Sn8+R+fv7m0FLkiIjI+Xi4qI9e/bkue+MjAylp6c7LAAAAACQX4W6spWSkqIBAwZo+/bt8vf3lySlpqaqQ4cO+s9//qMqVaoUSXETJ05Uenq66tevL1dXV2VlZem5555TdHS0JCkpKUmSFBQU5LBeUFCQ2ZeUlKTAwECHfjc3NwUEBJhjcjNr1ixNnz69SI4DAAAAQNlTqCtbo0eP1rlz53Tw4EGdOXNGZ86c0Xfffaf09HTzWaqi8O6772rVqlWKi4vT119/rZUrV2ru3LlauXJlke0jL7GxsUpLSzOXkydPWr5PAAAAADePQl3Z2rRpkz777DM1aNDAbGvYsKEWLVpUpBNkjB8/XhMnTtSAAQMkSY0bN9Yvv/yiWbNmKSYmRsHBwZKk5ORkhYSEmOslJyerWbNmkqTg4GClpKQ4bPfq1as6c+aMuX5uPD095enpWWTHAgAAAKBsKdSVrezsbLm7u+dod3d3V3Z29t8uyu7ixYtycXEs0dXV1dxHrVq1FBwcrK1bt5r96enp2rNnjyIiIiRJERERSk1NVUJCgjlm27Ztys7OVnh4eJHVCgAAAADXKlTYuvvuu/Xvf/9bp06dMtt+++03PfbYY+rYsWORFdezZ08999xz+vjjj3X8+HGtW7dO8+bN07333itJstlsGjt2rJ599ll9+OGHOnDggAYPHqzQ0FD17t1bktSgQQN16dJFw4YN0969e/XFF19o1KhRGjBgADMRAgAAALBMoW4jfOWVV3TPPfeoZs2aCgsLkySdPHlSt912m95+++0iK+7ll1/W5MmT9eijjyolJUWhoaF6+OGHNWXKFHPMk08+qQsXLmj48OFKTU1VmzZttGnTJvM7tiRp1apVGjVqlDp27CgXFxf17dtXCxcuLLI6AQAAAOB6NsMwjMKsaBiGPvvsM/3www+S/ryCdO0U7Deb9PR0+fn5KS0tTb6+vs4uBwDgBF9//bWaN2+uTk8vV0D1ek6t5cyJw9ry3BAlJCToH//4h1NrAYCyJr/ZoEC3EW7btk0NGzZUenq6bDabOnXqpNGjR2v06NFq2bKlGjVqpF27dv3t4gEAAACgtCtQ2Jo/f76GDRuWa3rz8/PTww8/rHnz5hVZcQAAAABQWhUobH377bfq0qVLnv2dO3d2mPUPAAAAAMqqAoWt5OTkXKd8t3Nzc9Pvv//+t4sCAAAAgNKuQGGratWq+u677/Ls379/v8OXCwMAAABAWVWgsNWtWzdNnjxZly9fztF36dIlTZ06VT169Ciy4gAAAACgtCrQ92xNmjRJa9eu1a233qpRo0apXr0/p7394YcftGjRImVlZenpp5+2pFAAAAAAKE0KFLaCgoK0e/dujRgxQrGxsbJ/RZfNZlNUVJQWLVqkoKAgSwoFAAAAgNKkQGFLkmrUqKGNGzfq7NmzOnr0qAzDUN26dVWxYkUr6gMAAACAUqnAYcuuYsWKatmyZVHWAgAAAAA3jQJNkAEAAAAAyB/CFgAAAABYgLAFAAAAABYgbAEAAACABQhbAAAAAGABwhYAAAAAWICwBQAAAAAWIGwBAAAAgAUIWwAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFCFsAAAAAYAHCFgAAAABYgLAFAAAAABYgbAEAAACABQhbAAAAAGABwhYAAAAAWICwBQAAAAAWIGwBAAAAgAUIWwAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFCFsAAAAAYAHCFgAAAABYoMSHrd9++00DBw5UpUqV5O3trcaNG+urr74y+w3D0JQpUxQSEiJvb29FRkbqyJEjDts4c+aMoqOj5evrK39/fw0dOlTnz58v7kMBAAAAUIaU6LB19uxZ3XnnnXJ3d9cnn3yi77//Xi+++KIqVqxojpkzZ44WLlyoJUuWaM+ePfLx8VFUVJQuX75sjomOjtbBgwe1ZcsWbdiwQTt37tTw4cOdcUgAAAAAygg3ZxdwI88//7zCwsK0fPlys61WrVrmfxuGofnz52vSpEnq1auXJOnNN99UUFCQ1q9frwEDBujQoUPatGmT9u3bpxYtWkiSXn75ZXXr1k1z585VaGhorvvOyMhQRkaG+To9Pd2KQwQAAABwkyrRV7Y+/PBDtWjRQv/85z8VGBio22+/Xa+//rrZf+zYMSUlJSkyMtJs8/PzU3h4uOLj4yVJ8fHx8vf3N4OWJEVGRsrFxUV79uzJc9+zZs2Sn5+fuYSFhVlwhAAAAABuViU6bP3888969dVXVbduXW3evFkjRozQmDFjtHLlSklSUlKSJCkoKMhhvaCgILMvKSlJgYGBDv1ubm4KCAgwx+QmNjZWaWlp5nLy5MmiPDQAAAAAN7kSfRthdna2WrRooZkzZ0qSbr/9dn333XdasmSJYmJiLN23p6enPD09Ld0HAAAAgJtXib6yFRISooYNGzq0NWjQQCdOnJAkBQcHS5KSk5MdxiQnJ5t9wcHBSklJcei/evWqzpw5Y44BAAAAgKJWosPWnXfeqcOHDzu0/fjjj6pRo4akPyfLCA4O1tatW83+9PR07dmzRxEREZKkiIgIpaamKiEhwRyzbds2ZWdnKzw8vBiOAgAAAEBZVKJvI3zsscd0xx13aObMmbrvvvu0d+9eLV26VEuXLpUk2Ww2jR07Vs8++6zq1q2rWrVqafLkyQoNDVXv3r0l/XklrEuXLho2bJiWLFmizMxMjRo1SgMGDMhzJkIAAAAA+LtKdNhq2bKl1q1bp9jYWM2YMUO1atXS/PnzFR0dbY558skndeHCBQ0fPlypqalq06aNNm3aJC8vL3PMqlWrNGrUKHXs2FEuLi7q27evFi5c6IxDAgAAAFBGlOiwJUk9evRQjx498uy32WyaMWOGZsyYkeeYgIAAxcXFWVEeAAAAAOSqRD+zBQAAAAClFWELAAAAACxA2AIAAAAACxC2AAAAAMAChC0AAAAAsABhCwAAAAAsQNgCAAAAAAsQtgAAAADAAoQtAAAAALAAYQsAAAAALEDYAgAAAAALELYAAAAAwAKELQAAAACwAGELAAAAACxA2AIAAAAACxC2AAAAAMAChC0AAAAAsABhCwAAAAAsQNgCAAAAAAsQtgAAAADAAoQtAAAAALAAYQsAAAAALEDYAgAAAAALELYAAAAAwAKELQAAAACwAGELAAAAACxA2AIAAAAACxC2AAAAAMAChC0AAAAAsABhCwAAAAAsQNgCAAAAAAsQtgAAAADAAoQtAAAAALAAYQsAAAAALEDYAgAAAAALlKqwNXv2bNlsNo0dO9Zsu3z5skaOHKlKlSqpfPny6tu3r5KTkx3WO3HihLp3765y5copMDBQ48eP19WrV4u5egAAAABlSakJW/v27dNrr72mJk2aOLQ/9thj+uijj7RmzRrt2LFDp06dUp8+fcz+rKwsde/eXVeuXNHu3bu1cuVKrVixQlOmTCnuQwAAAABQhpSKsHX+/HlFR0fr9ddfV8WKFc32tLQ0vfHGG5o3b57uvvtuNW/eXMuXL9fu3bv15ZdfSpI+/fRTff/993r77bfVrFkzde3aVc8884wWLVqkK1euOOuQAAAAANzkSkXYGjlypLp3767IyEiH9oSEBGVmZjq0169fX9WrV1d8fLwkKT4+Xo0bN1ZQUJA5JioqSunp6Tp48GCe+8zIyFB6errDAgAAAAD55ebsAv7Kf/7zH3399dfat29fjr6kpCR5eHjI39/foT0oKEhJSUnmmGuDlr3f3peXWbNmafr06X+zegAAAABlVYm+snXy5En9+9//1qpVq+Tl5VWs+46NjVVaWpq5nDx5slj3DwAAAKB0K9FhKyEhQSkpKfrHP/4hNzc3ubm5aceOHVq4cKHc3NwUFBSkK1euKDU11WG95ORkBQcHS5KCg4NzzE5of20fkxtPT0/5+vo6LAAAAACQXyU6bHXs2FEHDhxQYmKiubRo0ULR0dHmf7u7u2vr1q3mOocPH9aJEycUEREhSYqIiNCBAweUkpJijtmyZYt8fX3VsGHDYj8mAAAAAGVDiX5mq0KFCrrtttsc2nx8fFSpUiWzfejQoRo3bpwCAgL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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.corr()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 477
        },
        "id": "OYXOmJWwY2u6",
        "outputId": "898ca7d1-b0a6-415f-f70e-db1616f572d6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                               age   anaemia  creatinine_phosphokinase  \\\n",
              "age                       1.000000  0.123102                 -0.064637   \n",
              "anaemia                   0.123102  1.000000                 -0.181922   \n",
              "creatinine_phosphokinase -0.064637 -0.181922                  1.000000   \n",
              "diabetes                 -0.099938  0.002214                 -0.019987   \n",
              "ejection_fraction         0.069380  0.023465                 -0.021007   \n",
              "high_blood_pressure       0.092656  0.047172                 -0.045821   \n",
              "platelets                -0.024959 -0.046343                  0.024809   \n",
              "serum_creatinine          0.178194  0.032343                 -0.004032   \n",
              "serum_sodium             -0.026182  0.020723                  0.051404   \n",
              "sex                       0.072581 -0.081526                  0.069679   \n",
              "smoking                   0.023534 -0.105996                 -0.014294   \n",
              "time                     -0.220182 -0.111049                 -0.013789   \n",
              "DEATH_EVENT               0.249442  0.054508                  0.079706   \n",
              "\n",
              "                          diabetes  ejection_fraction  high_blood_pressure  \\\n",
              "age                      -0.099938           0.069380             0.092656   \n",
              "anaemia                   0.002214           0.023465             0.047172   \n",
              "creatinine_phosphokinase -0.019987          -0.021007            -0.045821   \n",
              "diabetes                  1.000000          -0.049101            -0.034712   \n",
              "ejection_fraction        -0.049101           1.000000             0.021474   \n",
              "high_blood_pressure      -0.034712           0.021474             1.000000   \n",
              "platelets                 0.072198           0.060289             0.048044   \n",
              "serum_creatinine         -0.019072          -0.038473            -0.007362   \n",
              "serum_sodium             -0.107393           0.212627             0.065884   \n",
              "sex                      -0.153649          -0.112841            -0.089096   \n",
              "smoking                  -0.167046          -0.021421            -0.025762   \n",
              "time                      0.027454           0.068472            -0.183450   \n",
              "DEATH_EVENT              -0.011273          -0.292702             0.094023   \n",
              "\n",
              "                          platelets  serum_creatinine  serum_sodium       sex  \\\n",
              "age                       -0.024959          0.178194     -0.026182  0.072581   \n",
              "anaemia                   -0.046343          0.032343      0.020723 -0.081526   \n",
              "creatinine_phosphokinase   0.024809         -0.004032      0.051404  0.069679   \n",
              "diabetes                   0.072198         -0.019072     -0.107393 -0.153649   \n",
              "ejection_fraction          0.060289         -0.038473      0.212627 -0.112841   \n",
              "high_blood_pressure        0.048044         -0.007362      0.065884 -0.089096   \n",
              "platelets                  1.000000         -0.005178      0.041101 -0.095209   \n",
              "serum_creatinine          -0.005178          1.000000     -0.229683  0.042409   \n",
              "serum_sodium               0.041101         -0.229683      1.000000 -0.053848   \n",
              "sex                       -0.095209          0.042409     -0.053848  1.000000   \n",
              "smoking                    0.065018          0.003029     -0.013830  0.434621   \n",
              "time                      -0.001025         -0.190489      0.109712 -0.008616   \n",
              "DEATH_EVENT               -0.031521          0.311281     -0.227355  0.055604   \n",
              "\n",
              "                           smoking      time  DEATH_EVENT  \n",
              "age                       0.023534 -0.220182     0.249442  \n",
              "anaemia                  -0.105996 -0.111049     0.054508  \n",
              "creatinine_phosphokinase -0.014294 -0.013789     0.079706  \n",
              "diabetes                 -0.167046  0.027454    -0.011273  \n",
              "ejection_fraction        -0.021421  0.068472    -0.292702  \n",
              "high_blood_pressure      -0.025762 -0.183450     0.094023  \n",
              "platelets                 0.065018 -0.001025    -0.031521  \n",
              "serum_creatinine          0.003029 -0.190489     0.311281  \n",
              "serum_sodium             -0.013830  0.109712    -0.227355  \n",
              "sex                       0.434621 -0.008616     0.055604  \n",
              "smoking                   1.000000 -0.013660     0.009397  \n",
              "time                     -0.013660  1.000000    -0.527234  \n",
              "DEATH_EVENT               0.009397 -0.527234     1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-194ddbbe-b14c-4a53-bcf4-594d8bddcb1d\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
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              "        vertical-align: top;\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>creatinine_phosphokinase</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>time</th>\n",
              "      <th>DEATH_EVENT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>age</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.123102</td>\n",
              "      <td>-0.064637</td>\n",
              "      <td>-0.099938</td>\n",
              "      <td>0.069380</td>\n",
              "      <td>0.092656</td>\n",
              "      <td>-0.024959</td>\n",
              "      <td>0.178194</td>\n",
              "      <td>-0.026182</td>\n",
              "      <td>0.072581</td>\n",
              "      <td>0.023534</td>\n",
              "      <td>-0.220182</td>\n",
              "      <td>0.249442</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>anaemia</th>\n",
              "      <td>0.123102</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.181922</td>\n",
              "      <td>0.002214</td>\n",
              "      <td>0.023465</td>\n",
              "      <td>0.047172</td>\n",
              "      <td>-0.046343</td>\n",
              "      <td>0.032343</td>\n",
              "      <td>0.020723</td>\n",
              "      <td>-0.081526</td>\n",
              "      <td>-0.105996</td>\n",
              "      <td>-0.111049</td>\n",
              "      <td>0.054508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>creatinine_phosphokinase</th>\n",
              "      <td>-0.064637</td>\n",
              "      <td>-0.181922</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.019987</td>\n",
              "      <td>-0.021007</td>\n",
              "      <td>-0.045821</td>\n",
              "      <td>0.024809</td>\n",
              "      <td>-0.004032</td>\n",
              "      <td>0.051404</td>\n",
              "      <td>0.069679</td>\n",
              "      <td>-0.014294</td>\n",
              "      <td>-0.013789</td>\n",
              "      <td>0.079706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>diabetes</th>\n",
              "      <td>-0.099938</td>\n",
              "      <td>0.002214</td>\n",
              "      <td>-0.019987</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.049101</td>\n",
              "      <td>-0.034712</td>\n",
              "      <td>0.072198</td>\n",
              "      <td>-0.019072</td>\n",
              "      <td>-0.107393</td>\n",
              "      <td>-0.153649</td>\n",
              "      <td>-0.167046</td>\n",
              "      <td>0.027454</td>\n",
              "      <td>-0.011273</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ejection_fraction</th>\n",
              "      <td>0.069380</td>\n",
              "      <td>0.023465</td>\n",
              "      <td>-0.021007</td>\n",
              "      <td>-0.049101</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.021474</td>\n",
              "      <td>0.060289</td>\n",
              "      <td>-0.038473</td>\n",
              "      <td>0.212627</td>\n",
              "      <td>-0.112841</td>\n",
              "      <td>-0.021421</td>\n",
              "      <td>0.068472</td>\n",
              "      <td>-0.292702</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>high_blood_pressure</th>\n",
              "      <td>0.092656</td>\n",
              "      <td>0.047172</td>\n",
              "      <td>-0.045821</td>\n",
              "      <td>-0.034712</td>\n",
              "      <td>0.021474</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.048044</td>\n",
              "      <td>-0.007362</td>\n",
              "      <td>0.065884</td>\n",
              "      <td>-0.089096</td>\n",
              "      <td>-0.025762</td>\n",
              "      <td>-0.183450</td>\n",
              "      <td>0.094023</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>platelets</th>\n",
              "      <td>-0.024959</td>\n",
              "      <td>-0.046343</td>\n",
              "      <td>0.024809</td>\n",
              "      <td>0.072198</td>\n",
              "      <td>0.060289</td>\n",
              "      <td>0.048044</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.005178</td>\n",
              "      <td>0.041101</td>\n",
              "      <td>-0.095209</td>\n",
              "      <td>0.065018</td>\n",
              "      <td>-0.001025</td>\n",
              "      <td>-0.031521</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>serum_creatinine</th>\n",
              "      <td>0.178194</td>\n",
              "      <td>0.032343</td>\n",
              "      <td>-0.004032</td>\n",
              "      <td>-0.019072</td>\n",
              "      <td>-0.038473</td>\n",
              "      <td>-0.007362</td>\n",
              "      <td>-0.005178</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.229683</td>\n",
              "      <td>0.042409</td>\n",
              "      <td>0.003029</td>\n",
              "      <td>-0.190489</td>\n",
              "      <td>0.311281</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>serum_sodium</th>\n",
              "      <td>-0.026182</td>\n",
              "      <td>0.020723</td>\n",
              "      <td>0.051404</td>\n",
              "      <td>-0.107393</td>\n",
              "      <td>0.212627</td>\n",
              "      <td>0.065884</td>\n",
              "      <td>0.041101</td>\n",
              "      <td>-0.229683</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.053848</td>\n",
              "      <td>-0.013830</td>\n",
              "      <td>0.109712</td>\n",
              "      <td>-0.227355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <td>0.072581</td>\n",
              "      <td>-0.081526</td>\n",
              "      <td>0.069679</td>\n",
              "      <td>-0.153649</td>\n",
              "      <td>-0.112841</td>\n",
              "      <td>-0.089096</td>\n",
              "      <td>-0.095209</td>\n",
              "      <td>0.042409</td>\n",
              "      <td>-0.053848</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.434621</td>\n",
              "      <td>-0.008616</td>\n",
              "      <td>0.055604</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>smoking</th>\n",
              "      <td>0.023534</td>\n",
              "      <td>-0.105996</td>\n",
              "      <td>-0.014294</td>\n",
              "      <td>-0.167046</td>\n",
              "      <td>-0.021421</td>\n",
              "      <td>-0.025762</td>\n",
              "      <td>0.065018</td>\n",
              "      <td>0.003029</td>\n",
              "      <td>-0.013830</td>\n",
              "      <td>0.434621</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.013660</td>\n",
              "      <td>0.009397</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>time</th>\n",
              "      <td>-0.220182</td>\n",
              "      <td>-0.111049</td>\n",
              "      <td>-0.013789</td>\n",
              "      <td>0.027454</td>\n",
              "      <td>0.068472</td>\n",
              "      <td>-0.183450</td>\n",
              "      <td>-0.001025</td>\n",
              "      <td>-0.190489</td>\n",
              "      <td>0.109712</td>\n",
              "      <td>-0.008616</td>\n",
              "      <td>-0.013660</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.527234</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DEATH_EVENT</th>\n",
              "      <td>0.249442</td>\n",
              "      <td>0.054508</td>\n",
              "      <td>0.079706</td>\n",
              "      <td>-0.011273</td>\n",
              "      <td>-0.292702</td>\n",
              "      <td>0.094023</td>\n",
              "      <td>-0.031521</td>\n",
              "      <td>0.311281</td>\n",
              "      <td>-0.227355</td>\n",
              "      <td>0.055604</td>\n",
              "      <td>0.009397</td>\n",
              "      <td>-0.527234</td>\n",
              "      <td>1.000000</td>\n",
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            }
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (12, 5))\n",
        "sns.heatmap(data.corr(), annot=True, cmap='bone')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 520
        },
        "id": "8YMw0JLYY_Rn",
        "outputId": "eb0f9b58-3eff-4d33-85c5-49aa80ea500c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 59
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "By looking at the heathmap we can see that DEATH_EVENT has the highest correlation with age, serum_creatinine and higehest negative correlation with ejection_fraction, serum_sodium, time"
      ],
      "metadata": {
        "id": "ShunZqmVbvSu"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Pyspark"
      ],
      "metadata": {
        "id": "wSo4ZxjuccOZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pip install pyspark"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rBWaP6EOcRRi",
        "outputId": "bba9441a-2e6d-49c6-a4b0-08c80490233b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pyspark\n",
            "  Downloading pyspark-3.5.1.tar.gz (317.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m317.0/317.0 MB\u001b[0m \u001b[31m2.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: py4j==0.10.9.7 in /usr/local/lib/python3.10/dist-packages (from pyspark) (0.10.9.7)\n",
            "Building wheels for collected packages: pyspark\n",
            "  Building wheel for pyspark (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pyspark: filename=pyspark-3.5.1-py2.py3-none-any.whl size=317488491 sha256=776d63d7bbb16173be5122ed2944e0663895d4ec9384b0d8d0d8e1919d9c9a1a\n",
            "  Stored in directory: /root/.cache/pip/wheels/80/1d/60/2c256ed38dddce2fdd93be545214a63e02fbd8d74fb0b7f3a6\n",
            "Successfully built pyspark\n",
            "Installing collected packages: pyspark\n",
            "Successfully installed pyspark-3.5.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# SparkSession\n",
        "from pyspark.sql import SparkSession\n",
        "\n",
        "spark = SparkSession.builder.appName(\"HeartFailure\").getOrCreate()"
      ],
      "metadata": {
        "id": "77bTQ66Cc8To"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# converting pandas dataframe into spark dataframe\n",
        "\n",
        "df = spark.createDataFrame(data)"
      ],
      "metadata": {
        "id": "ea1Hz2RCaJ9i"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.printSchema()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vJ9jj5DsdqqP",
        "outputId": "2bcf2e3e-e871-4245-e9d7-104c6545dd9f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "root\n",
            " |-- age: double (nullable = true)\n",
            " |-- anaemia: long (nullable = true)\n",
            " |-- creatinine_phosphokinase: long (nullable = true)\n",
            " |-- diabetes: long (nullable = true)\n",
            " |-- ejection_fraction: long (nullable = true)\n",
            " |-- high_blood_pressure: long (nullable = true)\n",
            " |-- platelets: double (nullable = true)\n",
            " |-- serum_creatinine: double (nullable = true)\n",
            " |-- serum_sodium: long (nullable = true)\n",
            " |-- sex: long (nullable = true)\n",
            " |-- smoking: long (nullable = true)\n",
            " |-- time: long (nullable = true)\n",
            " |-- DEATH_EVENT: long (nullable = true)\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(f'Number of columns: {len(df.columns)}\\nNumber of rows: {df.count()}')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l5tLBoATd7gi",
        "outputId": "d0a5d9f8-b469-4257-e850-352c7d6803d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of columns: 13\n",
            "Number of rows: 5000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pyspark.ml.feature import VectorAssembler\n",
        "\n",
        "# when assembling feature vector I will ignore columns with correlation in range from 0.05 to -0.05 because our model wont draw much from them\n",
        "\n",
        "assembler = VectorAssembler(inputCols = [\n",
        "    'age',\n",
        "    'anaemia',\n",
        "    'creatinine_phosphokinase',\n",
        "    'ejection_fraction',\n",
        "    'high_blood_pressure',\n",
        "    'serum_creatinine',\n",
        "    'serum_sodium',\n",
        "    'sex',\n",
        "    'time'\n",
        "  ], outputCol='features')\n",
        "\n",
        "\n",
        "df = assembler.transform(df)"
      ],
      "metadata": {
        "id": "w_YN3_5BdvN3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.show(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5Hg0bVzWk2YW",
        "outputId": "43b9f8e2-4d28-421d-d1a3-17e9015b22ad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----+-------+------------------------+--------+-----------------+-------------------+---------+----------------+------------+---+-------+----+-----------+--------------------+\n",
            "| age|anaemia|creatinine_phosphokinase|diabetes|ejection_fraction|high_blood_pressure|platelets|serum_creatinine|serum_sodium|sex|smoking|time|DEATH_EVENT|            features|\n",
            "+----+-------+------------------------+--------+-----------------+-------------------+---------+----------------+------------+---+-------+----+-----------+--------------------+\n",
            "|55.0|      0|                     748|       0|               45|                  0|263358.03|             1.3|         137|  1|      1|  88|          0|[55.0,0.0,748.0,4...|\n",
            "|65.0|      0|                      56|       0|               25|                  0| 305000.0|             5.0|         130|  1|      0| 207|          0|[65.0,0.0,56.0,25...|\n",
            "|45.0|      0|                     582|       1|               38|                  0| 319000.0|             0.9|         140|  0|      0| 244|          0|[45.0,0.0,582.0,3...|\n",
            "|60.0|      1|                     754|       1|               40|                  1| 328000.0|             1.2|         126|  1|      0|  90|          0|[60.0,1.0,754.0,4...|\n",
            "|95.0|      1|                     582|       0|               30|                  0| 461000.0|             2.0|         132|  1|      0|  50|          1|[95.0,1.0,582.0,3...|\n",
            "+----+-------+------------------------+--------+-----------------+-------------------+---------+----------------+------------+---+-------+----+-----------+--------------------+\n",
            "only showing top 5 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_ready = df.select(['features', 'DEATH_EVENT'])"
      ],
      "metadata": {
        "id": "d7-91ASflumY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_ready.show(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BmcNZ_VLl8-M",
        "outputId": "8fb0f7cd-eae3-4283-981f-ccda13e611c3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+--------------------+-----------+\n",
            "|            features|DEATH_EVENT|\n",
            "+--------------------+-----------+\n",
            "|[55.0,0.0,748.0,4...|          0|\n",
            "|[65.0,0.0,56.0,25...|          0|\n",
            "|[45.0,0.0,582.0,3...|          0|\n",
            "|[60.0,1.0,754.0,4...|          0|\n",
            "|[95.0,1.0,582.0,3...|          1|\n",
            "+--------------------+-----------+\n",
            "only showing top 5 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_df, test_df = df_ready.randomSplit([0.7, 0.3], 45)"
      ],
      "metadata": {
        "id": "_Ho9xyIDwpqH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "For my problem I decided to use XGBoost algorithm. XGBoost (Extreme Gradient Boosting) is a popular algorithm for classification (can be used for regression) due to its efficiency, accuracy, and flexibility.\n",
        "\n",
        "XGBoost is known for its superior performance and accuracy, often outperforming other algorithms in various machine learning competitions and practical applications. XGBoost builds an ensemble of trees sequentially, where each tree tries to correct the errors of the previous ones. This iterative approach helps in improving the model’s accuracy.\n",
        "\n"
      ],
      "metadata": {
        "id": "JOyQwPj50Y9E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from xgboost.spark import SparkXGBClassifier\n",
        "\n",
        "xgb_classifier = SparkXGBClassifier(features_col='features', label_col='DEATH_EVENT')\n",
        "\n",
        "model = xgb_classifier.fit(train_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zqn3rDd0mDut",
        "outputId": "4aa4dc75-023b-4a65-f2de-2d2b18a0d98c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:XGBoost-PySpark:Running xgboost-2.0.3 on 1 workers with\n",
            "\tbooster params: {'objective': 'binary:logistic', 'device': 'cpu', 'nthread': 1}\n",
            "\ttrain_call_kwargs_params: {'verbose_eval': True, 'num_boost_round': 100}\n",
            "\tdmatrix_kwargs: {'nthread': 1, 'missing': nan}\n",
            "INFO:XGBoost-PySpark:Finished xgboost training!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "predictions_df = model.transform(test_df)\n",
        "predictions_df.show(30)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e7OTldZMxKto",
        "outputId": "1eccae53-b751-4f1c-f3cd-effaa9c6532a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+--------------------+-----------+--------------------+----------+--------------------+\n",
            "|            features|DEATH_EVENT|       rawPrediction|prediction|         probability|\n",
            "+--------------------+-----------+--------------------+----------+--------------------+\n",
            "|[40.0,0.0,90.0,35...|          0|[8.51672554016113...|       0.0|[0.99979996681213...|\n",
            "|[40.0,0.0,90.0,35...|          0|[8.51672554016113...|       0.0|[0.99979996681213...|\n",
            "|[40.0,0.0,280.0,3...|          0|[5.56204938888549...|       0.0|[0.99617379903793...|\n",
            "|[40.0,0.0,582.0,3...|          0|[6.96620893478393...|       0.0|[0.99905765056610...|\n",
            "|[40.0,1.0,80.0,35...|          0|[7.35684537887573...|       0.0|[0.99936217069625...|\n",
            "|[40.0,1.0,100.0,3...|          0|[8.55236053466796...|       0.0|[0.99980694055557...|\n",
            "|[40.0,1.0,129.0,3...|          0|[8.51702022552490...|       0.0|[0.99980002641677...|\n",
            "|[40.0,1.0,129.0,3...|          0|[8.51702022552490...|       0.0|[0.99980002641677...|\n",
            "|[40.0,1.0,129.0,3...|          0|[8.51702022552490...|       0.0|[0.99980002641677...|\n",
            "|[40.0,1.0,315.0,2...|          0|[5.81844377517700...|       0.0|[0.99703657627105...|\n",
            "|[41.0,0.0,148.0,4...|          0|[6.42604351043701...|       0.0|[0.99838376045227...|\n",
            "|[41.0,0.0,148.0,4...|          0|[6.42604351043701...|       0.0|[0.99838376045227...|\n",
            "|[41.0,0.0,624.0,3...|          0|[10.1431617736816...|       0.0|[0.99996066093444...|\n",
            "|[42.0,0.0,64.0,35...|          0|[8.89000797271728...|       0.0|[0.99986225366592...|\n",
            "|[42.0,0.0,64.0,40...|          0|[8.77737236022949...|       0.0|[0.99984586238861...|\n",
            "|[42.0,0.0,64.0,40...|          0|[8.77737236022949...|       0.0|[0.99984586238861...|\n",
            "|[42.0,0.0,64.0,40...|          0|[8.77737236022949...|       0.0|[0.99984586238861...|\n",
            "|[42.0,0.0,64.0,40...|          0|[8.77737236022949...|       0.0|[0.99984586238861...|\n",
            "|[42.0,0.0,64.0,40...|          0|[8.77737236022949...|       0.0|[0.99984586238861...|\n",
            "|[42.0,0.0,64.0,40...|          0|[8.77737236022949...|       0.0|[0.99984586238861...|\n",
            "|[42.0,0.0,64.0,40...|          0|[8.77737236022949...|       0.0|[0.99984586238861...|\n",
            "|[42.0,0.0,64.0,40...|          0|[8.77737236022949...|       0.0|[0.99984586238861...|\n",
            "|[42.0,0.0,64.0,40...|          0|[8.77737236022949...|       0.0|[0.99984586238861...|\n",
            "|[42.0,0.0,64.0,45...|          0|[8.06098937988281...|       0.0|[0.99968451261520...|\n",
            "|[42.0,0.0,66.0,40...|          0|[8.33715534210205...|       0.0|[0.99976062774658...|\n",
            "|[42.0,0.0,102.0,2...|          0|[4.16844558715820...|       0.0|[0.98475956916809...|\n",
            "|[42.0,0.0,102.0,2...|          0|[5.54004335403442...|       0.0|[0.99608898162841...|\n",
            "|[42.0,0.0,102.0,3...|          0|[9.46663761138916...|       0.0|[0.99992263317108...|\n",
            "|[42.0,0.0,102.0,4...|          0|[9.99463176727295...|       0.0|[0.99995434284210...|\n",
            "|[42.0,0.0,102.0,4...|          0|[9.99463176727295...|       0.0|[0.99995434284210...|\n",
            "+--------------------+-----------+--------------------+----------+--------------------+\n",
            "only showing top 30 rows\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pyspark.ml.evaluation import BinaryClassificationEvaluator\n",
        "\n",
        "evaluator = BinaryClassificationEvaluator(labelCol='DEATH_EVENT')\n",
        "\n",
        "print(evaluator.evaluate(predictions_df))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tdioSp8txqO-",
        "outputId": "5d5f3b8b-29a4-4b0a-80c1-85db7417daa9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.9998522379238086\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Evaluator calculates AUC (Area Under the ROC). AUC is the common evaluation metric used for binary classification, value close to 1 means great classification, value of 0.5 would mean that our model is no better than random guessing, and lower values than 0.5 mean that model is worse than random guess. This model performed exceptionaly well having AUC of 0.999 (test set was used for predictions)"
      ],
      "metadata": {
        "id": "iHRPL0ZVHgng"
      }
    }
  ]
}