Notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "senior-alpha",
   "metadata": {
    "papermill": {
     "duration": 0.034857,
     "end_time": "2021-05-12T09:24:43.263427",
     "exception": false,
     "start_time": "2021-05-12T09:24:43.228570",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<h1> <u>Stroke prediction</u></h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "accessory-quantum",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:43.340114Z",
     "iopub.status.busy": "2021-05-12T09:24:43.339555Z",
     "iopub.status.idle": "2021-05-12T09:24:44.494427Z",
     "shell.execute_reply": "2021-05-12T09:24:44.493797Z"
    },
    "papermill": {
     "duration": 1.198125,
     "end_time": "2021-05-12T09:24:44.494574",
     "exception": false,
     "start_time": "2021-05-12T09:24:43.296449",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 1,
     "metadata": {
      "image/jpeg": {
       "height": 400,
       "width": 700
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "import urllib.request\n",
    "url = \"https://github.com/ashok49473/images/blob/main/brain-stroke.jpg?raw=true\"\n",
    "urllib.request.urlretrieve(url, \"img.jpg\")\n",
    "Image(filename=\"img.jpg\", width= 700, height=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "filled-fireplace",
   "metadata": {
    "papermill": {
     "duration": 0.035264,
     "end_time": "2021-05-12T09:24:44.566375",
     "exception": false,
     "start_time": "2021-05-12T09:24:44.531111",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Problem statement\n",
    "Stroke is sometimes termed as brain attack or a cardiovascular accident (CVA). It is much like a heart attack, only it occurs in the brain.<br>\n",
    "\n",
    "It occurs when the supply of blood to the brain is reduced or blocked completely, which prevents brain tissue from getting oxygen and nutrients.<br>\n",
    "\n",
    "According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible for approximately 11% of total deaths.<br>\n",
    "Early identification of stroke can help doctors to give necessary medication to the patient.\n",
    "\n",
    "\n",
    "## Machine Learning problem\n",
    "Predict whether a patient is likely to get stroke based on the input parameters like gender, age, various diseases, and smoking status.<br>\n",
    "<b>Type</b> : Supervised Learning<br>\n",
    "<b>Task</b> : Binary classification<br>\n",
    "<b>Performance metric</b> : F1 score (since imbalanced classes)<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "endless-daily",
   "metadata": {
    "papermill": {
     "duration": 0.035836,
     "end_time": "2021-05-12T09:24:44.637696",
     "exception": false,
     "start_time": "2021-05-12T09:24:44.601860",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## About Dataset\n",
    "Source : https://www.kaggle.com/fedesoriano/stroke-prediction-dataset\n",
    "\n",
    "### Attribute Information\n",
    "<b>id</b>: unique identifier<br>\n",
    "<b>gender</b>: Male, Female or Other<br>\n",
    "<b>age</b>: age of the patient<br>\n",
    "<b>hypertension</b>: 0 if the patient doesn't have hypertension, 1 if the patient has hypertension<br>\n",
    "<b>heart_disease</b>: 0 if the patient doesn't have any heart diseases, 1 if the patient has a heart disease<br>\n",
    "<b>ever_married</b>: No or Yes<br>\n",
    "<b>work_type</b>: children, Govt_jov, Never_worked, Private or Self-employed<br>\n",
    "<b>Residence_type</b>: Rural or Urban<br>\n",
    "<b>avg_glucose_level</b>: average glucose level in blood<br>\n",
    "<b>bmi</b>: body mass index<br>\n",
    "<b>smoking_status</b>: formerly smoked, never smoked, smokes or Unknown<br>\n",
    "<b>stroke</b>: 1 if the patient had a stroke or 0 if not (target)<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ahead-myrtle",
   "metadata": {
    "papermill": {
     "duration": 0.034901,
     "end_time": "2021-05-12T09:24:44.708713",
     "exception": false,
     "start_time": "2021-05-12T09:24:44.673812",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Libraries\n",
    "Importing all the necessary python modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "broke-noise",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:44.795074Z",
     "iopub.status.busy": "2021-05-12T09:24:44.794510Z",
     "iopub.status.idle": "2021-05-12T09:24:45.946310Z",
     "shell.execute_reply": "2021-05-12T09:24:45.945731Z"
    },
    "papermill": {
     "duration": 1.191319,
     "end_time": "2021-05-12T09:24:45.946445",
     "exception": false,
     "start_time": "2021-05-12T09:24:44.755126",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn.impute import KNNImputer\n",
    "from sklearn.model_selection import train_test_split, RandomizedSearchCV, StratifiedKFold\n",
    "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
    "from sklearn.metrics import f1_score, confusion_matrix\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "import pickle\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# settings\n",
    "sns.set_style('whitegrid')\n",
    "pd.set_option('display.float_format', lambda x: '%.3f' % x)\n",
    "pd.set_option('display.max_columns', None)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "beneficial-investing",
   "metadata": {
    "papermill": {
     "duration": 0.034463,
     "end_time": "2021-05-12T09:24:46.016489",
     "exception": false,
     "start_time": "2021-05-12T09:24:45.982026",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### K-Fold Cross-Validation\n",
    "Step 1: Randomly divide a dataset into k groups, or “folds”, of roughly equal size.<br>\n",
    "Step 2: Choose one of the folds to be the holdout set. Fit the model on the remaining k-1 folds.<br>\n",
    "Step 3: Calculate the test F1-score on the observations in the fold that was held out.<br>\n",
    "Step 4: Repeat this process k times, using a different set each time as the holdout set.<br>\n",
    "Step 5: Calculate the average of the k test F1-scores to get the overall test F1-score."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "differential-observation",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:46.094550Z",
     "iopub.status.busy": "2021-05-12T09:24:46.093166Z",
     "iopub.status.idle": "2021-05-12T09:24:46.095421Z",
     "shell.execute_reply": "2021-05-12T09:24:46.095843Z"
    },
    "papermill": {
     "duration": 0.045413,
     "end_time": "2021-05-12T09:24:46.095990",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.050577",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Below function implements above steps.\n",
    "def run_kfold(model, X_train, y_train, N_SPLITS = 10):\n",
    "    f1_list = []\n",
    "    oofs = np.zeros(len(X_train))\n",
    "    folds = StratifiedKFold(n_splits=N_SPLITS)\n",
    "    for i, (trn_idx, val_idx) in enumerate(folds.split(X_train, y_train)):\n",
    "        \n",
    "        print(f'\\n------------- Fold {i + 1} -------------')\n",
    "        X_trn, y_trn = X_train.iloc[trn_idx], y_train.iloc[trn_idx]\n",
    "        X_val, y_val = X_train.iloc[val_idx], y_train.iloc[val_idx]\n",
    "        \n",
    "        model.fit(X_trn, y_trn)\n",
    "        # Instead of directly predicting the classes we will obtain the probability of positive class.\n",
    "        preds_val = model.predict_proba(X_val)[:,1]\n",
    "        \n",
    "        fold_f1 = f1_score(y_val, preds_val.round())\n",
    "        f1_list.append(fold_f1)\n",
    "        \n",
    "        print(f'\\nf1 score for validation set is {fold_f1}') \n",
    "        \n",
    "        oofs[val_idx] = preds_val\n",
    "        \n",
    "    mean_f1 = sum(f1_list)/N_SPLITS\n",
    "    print(\"\\nMean validation f1 score :\", mean_f1)\n",
    "    \n",
    "    oofs_score = f1_score(y_train, oofs.round())\n",
    "    print(f'\\nF1 score for oofs is {oofs_score}')\n",
    "    return oofs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "later-truth",
   "metadata": {
    "papermill": {
     "duration": 0.034457,
     "end_time": "2021-05-12T09:24:46.165673",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.131216",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Data preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "motivated-mexican",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:46.244626Z",
     "iopub.status.busy": "2021-05-12T09:24:46.244130Z",
     "iopub.status.idle": "2021-05-12T09:24:46.269805Z",
     "shell.execute_reply": "2021-05-12T09:24:46.270763Z"
    },
    "papermill": {
     "duration": 0.070649,
     "end_time": "2021-05-12T09:24:46.270935",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.200286",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No of columns in the data :  12\n",
      "No of rows in the data :  5110\n"
     ]
    }
   ],
   "source": [
    "# Load data into memory\n",
    "data = pd.read_csv('/kaggle/input/stroke-prediction-dataset/healthcare-dataset-stroke-data.csv')\n",
    "\n",
    "print(\"No of columns in the data : \", len(data.columns))\n",
    "print(\"No of rows in the data : \", len(data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "noble-transfer",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:46.356837Z",
     "iopub.status.busy": "2021-05-12T09:24:46.356199Z",
     "iopub.status.idle": "2021-05-12T09:24:46.365611Z",
     "shell.execute_reply": "2021-05-12T09:24:46.365221Z"
    },
    "papermill": {
     "duration": 0.059097,
     "end_time": "2021-05-12T09:24:46.365717",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.306620",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>hypertension</th>\n",
       "      <th>heart_disease</th>\n",
       "      <th>ever_married</th>\n",
       "      <th>work_type</th>\n",
       "      <th>Residence_type</th>\n",
       "      <th>avg_glucose_level</th>\n",
       "      <th>bmi</th>\n",
       "      <th>smoking_status</th>\n",
       "      <th>stroke</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1375</th>\n",
       "      <td>14241</td>\n",
       "      <td>Male</td>\n",
       "      <td>17.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>85.070</td>\n",
       "      <td>21.100</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>66071</td>\n",
       "      <td>Male</td>\n",
       "      <td>51.000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>112.160</td>\n",
       "      <td>42.500</td>\n",
       "      <td>formerly smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3187</th>\n",
       "      <td>68408</td>\n",
       "      <td>Male</td>\n",
       "      <td>24.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>88.380</td>\n",
       "      <td>20.100</td>\n",
       "      <td>smokes</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4004</th>\n",
       "      <td>54240</td>\n",
       "      <td>Female</td>\n",
       "      <td>30.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Govt_job</td>\n",
       "      <td>Urban</td>\n",
       "      <td>61.290</td>\n",
       "      <td>24.000</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4689</th>\n",
       "      <td>6924</td>\n",
       "      <td>Female</td>\n",
       "      <td>32.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Rural</td>\n",
       "      <td>102.870</td>\n",
       "      <td>26.600</td>\n",
       "      <td>smokes</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         id  gender    age  hypertension  heart_disease ever_married  \\\n",
       "1375  14241    Male 17.000             0              0           No   \n",
       "191   66071    Male 51.000             1              0          Yes   \n",
       "3187  68408    Male 24.000             0              0           No   \n",
       "4004  54240  Female 30.000             0              0          Yes   \n",
       "4689   6924  Female 32.000             0              0          Yes   \n",
       "\n",
       "     work_type Residence_type  avg_glucose_level    bmi   smoking_status  \\\n",
       "1375   Private          Urban             85.070 21.100     never smoked   \n",
       "191    Private          Urban            112.160 42.500  formerly smoked   \n",
       "3187   Private          Urban             88.380 20.100           smokes   \n",
       "4004  Govt_job          Urban             61.290 24.000          Unknown   \n",
       "4689   Private          Rural            102.870 26.600           smokes   \n",
       "\n",
       "      stroke  \n",
       "1375       0  \n",
       "191        1  \n",
       "3187       0  \n",
       "4004       0  \n",
       "4689       0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# random sample of data\n",
    "data.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "global-incidence",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:46.444902Z",
     "iopub.status.busy": "2021-05-12T09:24:46.444247Z",
     "iopub.status.idle": "2021-05-12T09:24:46.468906Z",
     "shell.execute_reply": "2021-05-12T09:24:46.468509Z"
    },
    "papermill": {
     "duration": 0.06792,
     "end_time": "2021-05-12T09:24:46.469041",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.401121",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>age</th>\n",
       "      <th>hypertension</th>\n",
       "      <th>heart_disease</th>\n",
       "      <th>avg_glucose_level</th>\n",
       "      <th>bmi</th>\n",
       "      <th>stroke</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5110.000</td>\n",
       "      <td>5110.000</td>\n",
       "      <td>5110.000</td>\n",
       "      <td>5110.000</td>\n",
       "      <td>5110.000</td>\n",
       "      <td>4909.000</td>\n",
       "      <td>5110.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>36517.829</td>\n",
       "      <td>43.227</td>\n",
       "      <td>0.097</td>\n",
       "      <td>0.054</td>\n",
       "      <td>106.148</td>\n",
       "      <td>28.893</td>\n",
       "      <td>0.049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>21161.722</td>\n",
       "      <td>22.613</td>\n",
       "      <td>0.297</td>\n",
       "      <td>0.226</td>\n",
       "      <td>45.284</td>\n",
       "      <td>7.854</td>\n",
       "      <td>0.215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>67.000</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>55.120</td>\n",
       "      <td>10.300</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>17741.250</td>\n",
       "      <td>25.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>77.245</td>\n",
       "      <td>23.500</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>36932.000</td>\n",
       "      <td>45.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>91.885</td>\n",
       "      <td>28.100</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>54682.000</td>\n",
       "      <td>61.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>114.090</td>\n",
       "      <td>33.100</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>72940.000</td>\n",
       "      <td>82.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>271.740</td>\n",
       "      <td>97.600</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id      age  hypertension  heart_disease  avg_glucose_level  \\\n",
       "count  5110.000 5110.000      5110.000       5110.000           5110.000   \n",
       "mean  36517.829   43.227         0.097          0.054            106.148   \n",
       "std   21161.722   22.613         0.297          0.226             45.284   \n",
       "min      67.000    0.080         0.000          0.000             55.120   \n",
       "25%   17741.250   25.000         0.000          0.000             77.245   \n",
       "50%   36932.000   45.000         0.000          0.000             91.885   \n",
       "75%   54682.000   61.000         0.000          0.000            114.090   \n",
       "max   72940.000   82.000         1.000          1.000            271.740   \n",
       "\n",
       "           bmi   stroke  \n",
       "count 4909.000 5110.000  \n",
       "mean    28.893    0.049  \n",
       "std      7.854    0.215  \n",
       "min     10.300    0.000  \n",
       "25%     23.500    0.000  \n",
       "50%     28.100    0.000  \n",
       "75%     33.100    0.000  \n",
       "max     97.600    1.000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# statistical summary of the data\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "pretty-guyana",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:46.548913Z",
     "iopub.status.busy": "2021-05-12T09:24:46.548120Z",
     "iopub.status.idle": "2021-05-12T09:24:46.555070Z",
     "shell.execute_reply": "2021-05-12T09:24:46.555538Z"
    },
    "papermill": {
     "duration": 0.049402,
     "end_time": "2021-05-12T09:24:46.555656",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.506254",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Null count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gender</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypertension</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>heart_disease</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ever_married</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>work_type</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Residence_type</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>avg_glucose_level</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bmi</th>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smoking_status</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stroke</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Null count\n",
       "id                          0\n",
       "gender                      0\n",
       "age                         0\n",
       "hypertension                0\n",
       "heart_disease               0\n",
       "ever_married                0\n",
       "work_type                   0\n",
       "Residence_type              0\n",
       "avg_glucose_level           0\n",
       "bmi                       201\n",
       "smoking_status              0\n",
       "stroke                      0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# null values\n",
    "data.isna().sum().to_frame(name=\"Null count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "suspected-torture",
   "metadata": {
    "papermill": {
     "duration": 0.03632,
     "end_time": "2021-05-12T09:24:46.628408",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.592088",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Variable separation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "attractive-vitamin",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:46.706736Z",
     "iopub.status.busy": "2021-05-12T09:24:46.705944Z",
     "iopub.status.idle": "2021-05-12T09:24:46.708157Z",
     "shell.execute_reply": "2021-05-12T09:24:46.708562Z"
    },
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     "duration": 0.043401,
     "end_time": "2021-05-12T09:24:46.708686",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.665285",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# features\n",
    "features = ['gender', 'age', 'hypertension', 'heart_disease', 'ever_married','work_type','Residence_type',\n",
    "            'avg_glucose_level', 'bmi','smoking_status']\n",
    "\n",
    "#target\n",
    "target = 'stroke'\n",
    "\n",
    "numerical_features = ['age', 'avg_glucose_level', 'bmi']\n",
    "\n",
    "categorical_features = ['gender', 'hypertension', 'heart_disease', 'ever_married', 'work_type', \n",
    "                        'Residence_type', 'smoking_status']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "controversial-bryan",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:46.837271Z",
     "iopub.status.busy": "2021-05-12T09:24:46.830858Z",
     "iopub.status.idle": "2021-05-12T09:24:46.858867Z",
     "shell.execute_reply": "2021-05-12T09:24:46.859858Z"
    },
    "papermill": {
     "duration": 0.094383,
     "end_time": "2021-05-12T09:24:46.860075",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.765692",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Converting features into required datatypes\n",
    "data[numerical_features] = data[numerical_features].astype(np.float64)\n",
    "\n",
    "data[categorical_features] = data[categorical_features].astype('category')\n",
    "\n",
    "# Replace Other label in gender with Female\n",
    "data.gender.replace({'Other':\"Female\"}, inplace=True)\n",
    "\n",
    "# Remove id column\n",
    "data.drop('id', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "saved-reporter",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:46.988649Z",
     "iopub.status.busy": "2021-05-12T09:24:46.987822Z",
     "iopub.status.idle": "2021-05-12T09:24:46.994458Z",
     "shell.execute_reply": "2021-05-12T09:24:46.995077Z"
    },
    "papermill": {
     "duration": 0.078118,
     "end_time": "2021-05-12T09:24:46.995270",
     "exception": false,
     "start_time": "2021-05-12T09:24:46.917152",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Data type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>gender</th>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypertension</th>\n",
       "      <td>category</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>heart_disease</th>\n",
       "      <td>category</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ever_married</th>\n",
       "      <td>category</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>work_type</th>\n",
       "      <td>category</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Residence_type</th>\n",
       "      <td>category</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>avg_glucose_level</th>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bmi</th>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smoking_status</th>\n",
       "      <td>category</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stroke</th>\n",
       "      <td>int64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Data type\n",
       "gender               object\n",
       "age                 float64\n",
       "hypertension       category\n",
       "heart_disease      category\n",
       "ever_married       category\n",
       "work_type          category\n",
       "Residence_type     category\n",
       "avg_glucose_level   float64\n",
       "bmi                 float64\n",
       "smoking_status     category\n",
       "stroke                int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data types\n",
    "data[features+[target]].dtypes.to_frame(name=\"Data type\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "competitive-cancellation",
   "metadata": {
    "papermill": {
     "duration": 0.060896,
     "end_time": "2021-05-12T09:24:47.116825",
     "exception": false,
     "start_time": "2021-05-12T09:24:47.055929",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Train Test Split\n",
    "- Dividing the total dataset into training and testing sets\n",
    "- For Training 75% of data\n",
    "- For Testing 25% of data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "neural-edward",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:47.248548Z",
     "iopub.status.busy": "2021-05-12T09:24:47.247757Z",
     "iopub.status.idle": "2021-05-12T09:24:47.263852Z",
     "shell.execute_reply": "2021-05-12T09:24:47.263246Z"
    },
    "papermill": {
     "duration": 0.086853,
     "end_time": "2021-05-12T09:24:47.264014",
     "exception": false,
     "start_time": "2021-05-12T09:24:47.177161",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No. of data points in training set :  3832\n",
      "No. of data points in testing set :  1278\n"
     ]
    }
   ],
   "source": [
    "train, test = train_test_split(data, random_state=1, test_size=0.25, stratify=data.stroke)\n",
    "\n",
    "print(\"No. of data points in training set : \", len(train))\n",
    "print(\"No. of data points in testing set : \", len(test))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "charming-rochester",
   "metadata": {
    "papermill": {
     "duration": 0.038024,
     "end_time": "2021-05-12T09:24:47.341120",
     "exception": false,
     "start_time": "2021-05-12T09:24:47.303096",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Fill Missing values\n",
    "Using K-nearest neighbors imputation to fill missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ethical-literacy",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:47.424450Z",
     "iopub.status.busy": "2021-05-12T09:24:47.423737Z",
     "iopub.status.idle": "2021-05-12T09:24:47.503533Z",
     "shell.execute_reply": "2021-05-12T09:24:47.504348Z"
    },
    "papermill": {
     "duration": 0.125595,
     "end_time": "2021-05-12T09:24:47.504578",
     "exception": false,
     "start_time": "2021-05-12T09:24:47.378983",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "imputer = KNNImputer(n_neighbors = 5)\n",
    "\n",
    "train[numerical_features] = imputer.fit_transform(train[numerical_features])\n",
    "test[numerical_features] = imputer.transform(test[numerical_features])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cognitive-madrid",
   "metadata": {
    "papermill": {
     "duration": 0.059811,
     "end_time": "2021-05-12T09:24:47.634183",
     "exception": false,
     "start_time": "2021-05-12T09:24:47.574372",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Exploratory Data Analysis\n",
    "Exploratory data analysis (EDA) is used to analyze and investigate data sets and summarize their main characteristics, often employing data visualization methods.\n",
    "\n",
    "Performing EDA on Training set only (best practice to avoid overfitting)\n",
    "## Univariate analysis\n",
    "- Univariate analysis refers to the analysis of one variable.\n",
    "- The purpose of univariate analysis is to understand the distribution of values for a single variable.\n",
    "\n",
    "### A. Target distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "determined-ozone",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:47.729134Z",
     "iopub.status.busy": "2021-05-12T09:24:47.728239Z",
     "iopub.status.idle": "2021-05-12T09:24:48.041970Z",
     "shell.execute_reply": "2021-05-12T09:24:48.041537Z"
    },
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     "duration": 0.369909,
     "end_time": "2021-05-12T09:24:48.042092",
     "exception": false,
     "start_time": "2021-05-12T09:24:47.672183",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(ncols=2,figsize=(12, 4))\n",
    "train[target].value_counts(normalize=True).plot.bar(width=0.2, color=('red','green'), ax=axes[0], title=\"Train\")\n",
    "test[target].value_counts(normalize=True).plot.bar(width=0.2, color=('red','green'), ax=axes[1], title=\"Test\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acting-library",
   "metadata": {
    "papermill": {
     "duration": 0.037979,
     "end_time": "2021-05-12T09:24:48.119010",
     "exception": false,
     "start_time": "2021-05-12T09:24:48.081031",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### B. Histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "leading-stockholm",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:48.217309Z",
     "iopub.status.busy": "2021-05-12T09:24:48.216387Z",
     "iopub.status.idle": "2021-05-12T09:24:48.987580Z",
     "shell.execute_reply": "2021-05-12T09:24:48.986826Z"
    },
    "papermill": {
     "duration": 0.830786,
     "end_time": "2021-05-12T09:24:48.987702",
     "exception": false,
     "start_time": "2021-05-12T09:24:48.156916",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=3,figsize=(8, 8))\n",
    "\n",
    "for i, c in enumerate(numerical_features):\n",
    "    hist = train[c].plot(kind = 'hist', ax=axes[i], title=c, color='blue', bins=30)\n",
    "    \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sticky-beach",
   "metadata": {
    "papermill": {
     "duration": 0.041752,
     "end_time": "2021-05-12T09:24:49.069356",
     "exception": false,
     "start_time": "2021-05-12T09:24:49.027604",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Boxplot (Outliers)\n",
    "An outlier is a data point that differs significantly from other observations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "upset-lawyer",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:49.171220Z",
     "iopub.status.busy": "2021-05-12T09:24:49.170326Z",
     "iopub.status.idle": "2021-05-12T09:24:49.655882Z",
     "shell.execute_reply": "2021-05-12T09:24:49.654990Z"
    },
    "papermill": {
     "duration": 0.547073,
     "end_time": "2021-05-12T09:24:49.656048",
     "exception": false,
     "start_time": "2021-05-12T09:24:49.108975",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x504 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=3, figsize=(8, 7))\n",
    "\n",
    "for i, c in enumerate(numerical_features):\n",
    "    box = train[c].plot(kind = 'box', ax=axes[i], vert=False, color='blue')\n",
    "    \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acknowledged-jenny",
   "metadata": {
    "papermill": {
     "duration": 0.039898,
     "end_time": "2021-05-12T09:24:49.736687",
     "exception": false,
     "start_time": "2021-05-12T09:24:49.696789",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### KDE Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "stable-intention",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:49.829330Z",
     "iopub.status.busy": "2021-05-12T09:24:49.828511Z",
     "iopub.status.idle": "2021-05-12T09:24:50.406494Z",
     "shell.execute_reply": "2021-05-12T09:24:50.406869Z"
    },
    "papermill": {
     "duration": 0.629789,
     "end_time": "2021-05-12T09:24:50.407031",
     "exception": false,
     "start_time": "2021-05-12T09:24:49.777242",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x504 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=3, figsize=(8, 7))\n",
    "\n",
    "for i, c in enumerate(numerical_features):\n",
    "    plot = sns.kdeplot(data=train, x=c, ax=axes[i], fill=True, color='blue')\n",
    "    \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "convinced-despite",
   "metadata": {
    "papermill": {
     "duration": 0.041064,
     "end_time": "2021-05-12T09:24:50.489517",
     "exception": false,
     "start_time": "2021-05-12T09:24:50.448453",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Pie-Charts\n",
    "Percentage of labels in categorical features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "listed-simulation",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:50.611235Z",
     "iopub.status.busy": "2021-05-12T09:24:50.610404Z",
     "iopub.status.idle": "2021-05-12T09:24:51.473588Z",
     "shell.execute_reply": "2021-05-12T09:24:51.472701Z"
    },
    "papermill": {
     "duration": 0.942955,
     "end_time": "2021-05-12T09:24:51.473717",
     "exception": false,
     "start_time": "2021-05-12T09:24:50.530762",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1152 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(4, 2, figsize=(12,16))\n",
    "axes = [ax for axes_row in axes for ax in axes_row]\n",
    "\n",
    "for i,c in enumerate(categorical_features):\n",
    "    train[c].value_counts().plot(kind='pie', ax=axes[i], title=c, autopct=\"%.2f\", fontsize=14)\n",
    "    axes[i].set_ylabel('')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "convinced-diagram",
   "metadata": {
    "papermill": {
     "duration": 0.044209,
     "end_time": "2021-05-12T09:24:51.563233",
     "exception": false,
     "start_time": "2021-05-12T09:24:51.519024",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#  Bivariate analysis\n",
    "It involves the analysis of two variables, for the purpose of determining the empirical relationship between them.\n",
    "\n",
    "We perform bivariate analysis of features with respect to target.\n",
    "\n",
    "### Box plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "arbitrary-particular",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:51.672732Z",
     "iopub.status.busy": "2021-05-12T09:24:51.671821Z",
     "iopub.status.idle": "2021-05-12T09:24:52.078367Z",
     "shell.execute_reply": "2021-05-12T09:24:52.077925Z"
    },
    "papermill": {
     "duration": 0.471039,
     "end_time": "2021-05-12T09:24:52.078487",
     "exception": false,
     "start_time": "2021-05-12T09:24:51.607448",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=3, figsize=(8, 8))\n",
    "for i, c in enumerate(numerical_features): \n",
    "    plot = sns.boxplot(x=train[target], y=train[c], ax=axes[i])\n",
    "    axes[i].set_ylabel(c, fontsize=13)\n",
    "    axes[i].set_xlabel(target, fontsize=13)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "confidential-shirt",
   "metadata": {
    "papermill": {
     "duration": 0.045243,
     "end_time": "2021-05-12T09:24:52.169173",
     "exception": false,
     "start_time": "2021-05-12T09:24:52.123930",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Target vs Mean of Numerical features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "infinite-diagram",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:52.315732Z",
     "iopub.status.busy": "2021-05-12T09:24:52.301362Z",
     "iopub.status.idle": "2021-05-12T09:24:52.694528Z",
     "shell.execute_reply": "2021-05-12T09:24:52.693751Z"
    },
    "papermill": {
     "duration": 0.480067,
     "end_time": "2021-05-12T09:24:52.694661",
     "exception": false,
     "start_time": "2021-05-12T09:24:52.214594",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(ncols=3, figsize=(20, 5))\n",
    "for i, c in enumerate(numerical_features):\n",
    "    train.groupby(target)[c].mean().plot(kind = 'bar', ax=axes[i], color=('red','green'))\n",
    "    axes[i].set_ylabel(f'Mean_{c}', fontsize=14)\n",
    "    axes[i].set_xlabel('stroke', fontsize=14)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "governing-franklin",
   "metadata": {
    "papermill": {
     "duration": 0.046018,
     "end_time": "2021-05-12T09:24:52.786910",
     "exception": false,
     "start_time": "2021-05-12T09:24:52.740892",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Target vs categorical features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "perceived-pointer",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:53.012436Z",
     "iopub.status.busy": "2021-05-12T09:24:53.011318Z",
     "iopub.status.idle": "2021-05-12T09:24:54.201025Z",
     "shell.execute_reply": "2021-05-12T09:24:54.200548Z"
    },
    "papermill": {
     "duration": 1.368389,
     "end_time": "2021-05-12T09:24:54.201155",
     "exception": false,
     "start_time": "2021-05-12T09:24:52.832766",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 4, figsize=(20,10))\n",
    "axes = [ax for axes_row in axes for ax in axes_row]\n",
    "\n",
    "for i, c in enumerate(categorical_features):\n",
    "    df = train[[c,target]].groupby(c).mean().reset_index()\n",
    "    sns.barplot(df[c], df[target], ax=axes[i])\n",
    "    axes[i].set_ylabel('Target mean', fontsize=14)\n",
    "    axes[i].set_xlabel(c, fontsize=14)\n",
    "    \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "extended-methodology",
   "metadata": {
    "papermill": {
     "duration": 0.052244,
     "end_time": "2021-05-12T09:24:54.303125",
     "exception": false,
     "start_time": "2021-05-12T09:24:54.250881",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Feature Engineering\n",
    "Feature engineering is the process of using domain knowledge to extract features from raw data. These features can be used to improve the performance of machine learning algorithms."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "vocational-prize",
   "metadata": {
    "papermill": {
     "duration": 0.048452,
     "end_time": "2021-05-12T09:24:54.402219",
     "exception": false,
     "start_time": "2021-05-12T09:24:54.353767",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## New Features with Discretization\n",
    "Discretization is the process of replacing the continuous values with a finite set of values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "absent-cycling",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:54.516626Z",
     "iopub.status.busy": "2021-05-12T09:24:54.515825Z",
     "iopub.status.idle": "2021-05-12T09:24:54.518379Z",
     "shell.execute_reply": "2021-05-12T09:24:54.517983Z"
    },
    "papermill": {
     "duration": 0.066578,
     "end_time": "2021-05-12T09:24:54.518485",
     "exception": false,
     "start_time": "2021-05-12T09:24:54.451907",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def age_group(x):\n",
    "    if x<13: return \"Child\"\n",
    "    elif 13<x<20: return \"Teenager\"\n",
    "    elif 20<x<=60: return \"Adult\"\n",
    "    else: return \"Elder\"\n",
    "    \n",
    "train[\"age_group\"] = train.age.apply(age_group)\n",
    "test['age_group'] = test.age.apply(age_group)\n",
    "\n",
    "def bmi_group(x):\n",
    "    if x<18.5 : return \"UnderWeight\"\n",
    "    elif 18.5<x<25: return \"Healthy\"\n",
    "    elif 25<x<30: return \"OverWeight\"\n",
    "    else: return \"Obese\"\n",
    "\n",
    "train[\"bmi_group\"] = train.bmi.apply(age_group)\n",
    "test['bmi_group'] = test.bmi.apply(age_group)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "second-preparation",
   "metadata": {
    "papermill": {
     "duration": 0.048506,
     "end_time": "2021-05-12T09:24:54.615247",
     "exception": false,
     "start_time": "2021-05-12T09:24:54.566741",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## OneHot encoding\n",
    "- Replaces categorical column(s) with the binary value for each category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "continued-optimum",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:54.728299Z",
     "iopub.status.busy": "2021-05-12T09:24:54.727475Z",
     "iopub.status.idle": "2021-05-12T09:24:54.796012Z",
     "shell.execute_reply": "2021-05-12T09:24:54.795564Z"
    },
    "papermill": {
     "duration": 0.131016,
     "end_time": "2021-05-12T09:24:54.796191",
     "exception": false,
     "start_time": "2021-05-12T09:24:54.665175",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# add new features\n",
    "categorical_features.extend([\"bmi_group\", \"age_group\"])\n",
    "\n",
    "encoder = OneHotEncoder(drop='first', sparse=False)\n",
    "encoder.fit(train[categorical_features])\n",
    "\n",
    "cols = encoder.get_feature_names(categorical_features)\n",
    "\n",
    "train.loc[:, cols] = encoder.transform(train[categorical_features])\n",
    "test.loc[:, cols] = encoder.transform(test[categorical_features])\n",
    "\n",
    "# Drop categorical features\n",
    "train.drop(categorical_features, axis=1, inplace=True)\n",
    "test.drop(categorical_features, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "prescribed-persian",
   "metadata": {
    "papermill": {
     "duration": 0.048654,
     "end_time": "2021-05-12T09:24:54.893845",
     "exception": false,
     "start_time": "2021-05-12T09:24:54.845191",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Feature Scaling\n",
    "Standardize the numerical features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "animated-retention",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:55.004668Z",
     "iopub.status.busy": "2021-05-12T09:24:55.003753Z",
     "iopub.status.idle": "2021-05-12T09:24:55.016368Z",
     "shell.execute_reply": "2021-05-12T09:24:55.016817Z"
    },
    "papermill": {
     "duration": 0.071324,
     "end_time": "2021-05-12T09:24:55.016977",
     "exception": false,
     "start_time": "2021-05-12T09:24:54.945653",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "scaler.fit(train[numerical_features])\n",
    "\n",
    "train.loc[:, numerical_features] = scaler.transform(train[numerical_features])\n",
    "test.loc[:, numerical_features] = scaler.transform(test[numerical_features])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "therapeutic-cycling",
   "metadata": {
    "papermill": {
     "duration": 0.04964,
     "end_time": "2021-05-12T09:24:55.117885",
     "exception": false,
     "start_time": "2021-05-12T09:24:55.068245",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    " ## Correlation\n",
    " Relationship between features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "hindu-burke",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:55.221582Z",
     "iopub.status.busy": "2021-05-12T09:24:55.220949Z",
     "iopub.status.idle": "2021-05-12T09:24:57.365331Z",
     "shell.execute_reply": "2021-05-12T09:24:57.365728Z"
    },
    "papermill": {
     "duration": 2.198685,
     "end_time": "2021-05-12T09:24:57.365869",
     "exception": false,
     "start_time": "2021-05-12T09:24:55.167184",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr = train.corr()\n",
    "plt.figure(figsize=(16,9))\n",
    "sns.heatmap(corr, cmap='Blues', cbar=False, annot=True, fmt='.2f')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "cheap-patch",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:57.487416Z",
     "iopub.status.busy": "2021-05-12T09:24:57.486502Z",
     "iopub.status.idle": "2021-05-12T09:24:57.856680Z",
     "shell.execute_reply": "2021-05-12T09:24:57.857154Z"
    },
    "papermill": {
     "duration": 0.435272,
     "end_time": "2021-05-12T09:24:57.857319",
     "exception": false,
     "start_time": "2021-05-12T09:24:57.422047",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 144x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation with Target\n",
    "\n",
    "corr = train.corr()[target].sort_values(ascending=False).to_frame()\n",
    "plt.figure(figsize=(2,8))\n",
    "sns.heatmap(corr, cmap='Blues', cbar=False, annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "prepared-interest",
   "metadata": {
    "papermill": {
     "duration": 0.09084,
     "end_time": "2021-05-12T09:24:58.036836",
     "exception": false,
     "start_time": "2021-05-12T09:24:57.945996",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Preprocessed data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "accredited-hello",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:58.232211Z",
     "iopub.status.busy": "2021-05-12T09:24:58.231370Z",
     "iopub.status.idle": "2021-05-12T09:24:58.249424Z",
     "shell.execute_reply": "2021-05-12T09:24:58.248983Z"
    },
    "papermill": {
     "duration": 0.120626,
     "end_time": "2021-05-12T09:24:58.249536",
     "exception": false,
     "start_time": "2021-05-12T09:24:58.128910",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>avg_glucose_level</th>\n",
       "      <th>bmi</th>\n",
       "      <th>gender_Male</th>\n",
       "      <th>hypertension_1</th>\n",
       "      <th>heart_disease_1</th>\n",
       "      <th>ever_married_Yes</th>\n",
       "      <th>work_type_Never_worked</th>\n",
       "      <th>work_type_Private</th>\n",
       "      <th>work_type_Self-employed</th>\n",
       "      <th>work_type_children</th>\n",
       "      <th>Residence_type_Urban</th>\n",
       "      <th>smoking_status_formerly smoked</th>\n",
       "      <th>smoking_status_never smoked</th>\n",
       "      <th>smoking_status_smokes</th>\n",
       "      <th>bmi_group_Child</th>\n",
       "      <th>bmi_group_Elder</th>\n",
       "      <th>bmi_group_Teenager</th>\n",
       "      <th>age_group_Child</th>\n",
       "      <th>age_group_Elder</th>\n",
       "      <th>age_group_Teenager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2045</th>\n",
       "      <td>-1.798</td>\n",
       "      <td>-0.436</td>\n",
       "      <td>-1.412</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4671</th>\n",
       "      <td>-1.050</td>\n",
       "      <td>-0.590</td>\n",
       "      <td>1.020</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3539</th>\n",
       "      <td>-1.402</td>\n",
       "      <td>-0.833</td>\n",
       "      <td>-1.386</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>1.633</td>\n",
       "      <td>-0.351</td>\n",
       "      <td>0.695</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5086</th>\n",
       "      <td>0.358</td>\n",
       "      <td>1.023</td>\n",
       "      <td>-0.918</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        age  avg_glucose_level    bmi  gender_Male  hypertension_1  \\\n",
       "2045 -1.798             -0.436 -1.412        1.000           0.000   \n",
       "4671 -1.050             -0.590  1.020        1.000           0.000   \n",
       "3539 -1.402             -0.833 -1.386        1.000           0.000   \n",
       "2002  1.633             -0.351  0.695        0.000           0.000   \n",
       "5086  0.358              1.023 -0.918        0.000           0.000   \n",
       "\n",
       "      heart_disease_1  ever_married_Yes  work_type_Never_worked  \\\n",
       "2045            0.000             0.000                   0.000   \n",
       "4671            0.000             0.000                   0.000   \n",
       "3539            0.000             0.000                   0.000   \n",
       "2002            0.000             1.000                   0.000   \n",
       "5086            0.000             1.000                   0.000   \n",
       "\n",
       "      work_type_Private  work_type_Self-employed  work_type_children  \\\n",
       "2045              0.000                    0.000               1.000   \n",
       "4671              1.000                    0.000               0.000   \n",
       "3539              0.000                    0.000               1.000   \n",
       "2002              0.000                    1.000               0.000   \n",
       "5086              1.000                    0.000               0.000   \n",
       "\n",
       "      Residence_type_Urban  smoking_status_formerly smoked  \\\n",
       "2045                 0.000                           0.000   \n",
       "4671                 0.000                           0.000   \n",
       "3539                 0.000                           0.000   \n",
       "2002                 0.000                           0.000   \n",
       "5086                 1.000                           0.000   \n",
       "\n",
       "      smoking_status_never smoked  smoking_status_smokes  bmi_group_Child  \\\n",
       "2045                        0.000                  0.000            0.000   \n",
       "4671                        0.000                  0.000            0.000   \n",
       "3539                        0.000                  0.000            0.000   \n",
       "2002                        1.000                  0.000            0.000   \n",
       "5086                        0.000                  0.000            0.000   \n",
       "\n",
       "      bmi_group_Elder  bmi_group_Teenager  age_group_Child  age_group_Elder  \\\n",
       "2045            0.000               1.000            1.000            0.000   \n",
       "4671            0.000               0.000            0.000            0.000   \n",
       "3539            0.000               1.000            1.000            0.000   \n",
       "2002            0.000               0.000            0.000            1.000   \n",
       "5086            0.000               0.000            0.000            0.000   \n",
       "\n",
       "      age_group_Teenager  \n",
       "2045               0.000  \n",
       "4671               1.000  \n",
       "3539               0.000  \n",
       "2002               0.000  \n",
       "5086               0.000  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = ['age', 'avg_glucose_level', 'bmi', 'gender_Male','hypertension_1', 'heart_disease_1', 'ever_married_Yes',\n",
    "            'work_type_Never_worked', 'work_type_Private','work_type_Self-employed', 'work_type_children', \n",
    "            'Residence_type_Urban','smoking_status_formerly smoked', 'smoking_status_never smoked','smoking_status_smokes',\n",
    "            'bmi_group_Child', 'bmi_group_Elder', 'bmi_group_Teenager', 'age_group_Child', 'age_group_Elder', 'age_group_Teenager']\n",
    "\n",
    "X_train = train[features]\n",
    "y_train = train[target]\n",
    "\n",
    "X_test = test[features]\n",
    "y_test = test[target]\n",
    "\n",
    "X_train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "working-hands",
   "metadata": {
    "papermill": {
     "duration": 0.057409,
     "end_time": "2021-05-12T09:24:58.364201",
     "exception": false,
     "start_time": "2021-05-12T09:24:58.306792",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Machine Learning\n",
    "## Decision tree classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "crucial-writing",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:58.485449Z",
     "iopub.status.busy": "2021-05-12T09:24:58.484723Z",
     "iopub.status.idle": "2021-05-12T09:24:58.506762Z",
     "shell.execute_reply": "2021-05-12T09:24:58.506340Z"
    },
    "papermill": {
     "duration": 0.085857,
     "end_time": "2021-05-12T09:24:58.506870",
     "exception": false,
     "start_time": "2021-05-12T09:24:58.421013",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train f1 Score : 1.0\n",
      "Test f1 Score : 0.14285714285714285\n"
     ]
    }
   ],
   "source": [
    "# Base model\n",
    "clf = DecisionTreeClassifier(random_state=1)\n",
    "clf.fit(X_train, y_train)\n",
    "train_preds = clf.predict(X_train)\n",
    "test_preds = clf.predict(X_test)\n",
    "print(\"Train f1 Score :\", f1_score(y_train, train_preds))\n",
    "print(\"Test f1 Score :\", f1_score(y_test, test_preds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "lonely-expert",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:24:58.636679Z",
     "iopub.status.busy": "2021-05-12T09:24:58.635740Z",
     "iopub.status.idle": "2021-05-12T09:25:00.749408Z",
     "shell.execute_reply": "2021-05-12T09:25:00.749951Z"
    },
    "papermill": {
     "duration": 2.18563,
     "end_time": "2021-05-12T09:25:00.750161",
     "exception": false,
     "start_time": "2021-05-12T09:24:58.564531",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 50 candidates, totalling 250 fits\n",
      "\n",
      "Best f1-score: 0.2688928913954958\n",
      "\n",
      "Best params: {'min_samples_split': 40, 'max_leaf_nodes': 8, 'max_features': 0.8, 'max_depth': 10, 'criterion': 'gini', 'class_weight': {0: 1, 1: 7}}\n"
     ]
    }
   ],
   "source": [
    "# Hyperparameter tuning\n",
    "params = {\n",
    "    'max_depth': [4, 6, 8, 10, 12, 14, 16, 20],\n",
    "    'criterion': ['gini', 'entropy'],\n",
    "    'min_samples_split': [5, 10, 20, 30, 40, 50],\n",
    "    'max_features': [0.2, 0.4, 0.6, 0.8, 1],\n",
    "    'max_leaf_nodes': [8, 16, 32, 64, 128,256],\n",
    "    'class_weight': [{0: 1, 1: 9}, {0: 1, 1: 4}, {0: 1, 1: 5}, {0: 1, 1: 6}, {0: 1, 1: 7}, {0: 1, 1: 8}]\n",
    "}\n",
    "\n",
    "clf = RandomizedSearchCV(DecisionTreeClassifier(random_state=1),\n",
    "                         params,\n",
    "                         scoring='f1',\n",
    "                         verbose=1,\n",
    "                         random_state=1,\n",
    "                         cv=5,\n",
    "                         n_iter=50)\n",
    "\n",
    "search = clf.fit(X_train, y_train)\n",
    "\n",
    "print(\"\\nBest f1-score:\",search.best_score_)\n",
    "print(\"\\nBest params:\",search.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "computational-single",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:00.877780Z",
     "iopub.status.busy": "2021-05-12T09:25:00.876907Z",
     "iopub.status.idle": "2021-05-12T09:25:00.933948Z",
     "shell.execute_reply": "2021-05-12T09:25:00.934575Z"
    },
    "papermill": {
     "duration": 0.122266,
     "end_time": "2021-05-12T09:25:00.934768",
     "exception": false,
     "start_time": "2021-05-12T09:25:00.812502",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "------------- Fold 1 -------------\n",
      "\n",
      "f1 score for validation set is 0.24836601307189543\n",
      "\n",
      "------------- Fold 2 -------------\n",
      "\n",
      "f1 score for validation set is 0.21100917431192662\n",
      "\n",
      "------------- Fold 3 -------------\n",
      "\n",
      "f1 score for validation set is 0.29714285714285715\n",
      "\n",
      "------------- Fold 4 -------------\n",
      "\n",
      "f1 score for validation set is 0.30065359477124187\n",
      "\n",
      "------------- Fold 5 -------------\n",
      "\n",
      "f1 score for validation set is 0.287292817679558\n",
      "\n",
      "Mean validation f1 score : 0.2688928913954958\n",
      "\n",
      "F1 score for oofs is 0.2659090909090909\n"
     ]
    }
   ],
   "source": [
    "# Cross validation\n",
    "clf = DecisionTreeClassifier(random_state = 1, **search.best_params_)\n",
    "oofs = run_kfold(clf, X_train, y_train, N_SPLITS=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "intensive-mortality",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:01.062510Z",
     "iopub.status.busy": "2021-05-12T09:25:01.061761Z",
     "iopub.status.idle": "2021-05-12T09:25:01.197379Z",
     "shell.execute_reply": "2021-05-12T09:25:01.196685Z"
    },
    "papermill": {
     "duration": 0.202077,
     "end_time": "2021-05-12T09:25:01.197565",
     "exception": false,
     "start_time": "2021-05-12T09:25:00.995488",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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suLg43X333brhhhuCPVa/QNgAmMOrKABzCBsAcwgbAHMIGwBzCBsAcwgbAHMIGwBzCBsAc/4HoyVfaLo8essAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Final Decision tree classifier\n",
    "clf = DecisionTreeClassifier(random_state = 1, **search.best_params_)\n",
    "clf.fit(X_train, y_train)\n",
    "\n",
    "preds_test = clf.predict_proba(X_test)[:, 1]\n",
    "    \n",
    "cm = confusion_matrix(y_test, preds_test.round(), normalize='true')\n",
    "plt.figure(figsize=(5,5))\n",
    "sns.heatmap(cm, annot=True, cmap='Blues', cbar=False,fmt='.2f')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "faced-motorcycle",
   "metadata": {
    "papermill": {
     "duration": 0.061523,
     "end_time": "2021-05-12T09:25:01.335347",
     "exception": false,
     "start_time": "2021-05-12T09:25:01.273824",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "vocational-slope",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:01.463488Z",
     "iopub.status.busy": "2021-05-12T09:25:01.462699Z",
     "iopub.status.idle": "2021-05-12T09:25:01.551714Z",
     "shell.execute_reply": "2021-05-12T09:25:01.552486Z"
    },
    "papermill": {
     "duration": 0.156256,
     "end_time": "2021-05-12T09:25:01.552722",
     "exception": false,
     "start_time": "2021-05-12T09:25:01.396466",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train f1 Score : 0.24349157733537521\n",
      "Test f1 Score : 0.22377622377622378\n"
     ]
    }
   ],
   "source": [
    "# Base model\n",
    "clf = LogisticRegression(random_state=1, class_weight='balanced')\n",
    "clf.fit(X_train, y_train)\n",
    "train_preds = clf.predict(X_train)\n",
    "test_preds = clf.predict(X_test)\n",
    "print(\"Train f1 Score :\", f1_score(y_train, train_preds))\n",
    "print(\"Test f1 Score :\", f1_score(y_test, test_preds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "representative-reset",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:01.737496Z",
     "iopub.status.busy": "2021-05-12T09:25:01.736692Z",
     "iopub.status.idle": "2021-05-12T09:25:05.720019Z",
     "shell.execute_reply": "2021-05-12T09:25:05.720993Z"
    },
    "papermill": {
     "duration": 4.057928,
     "end_time": "2021-05-12T09:25:05.721217",
     "exception": false,
     "start_time": "2021-05-12T09:25:01.663289",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 20 candidates, totalling 100 fits\n",
      "\n",
      "Best f1-score: 0.235615072173141\n",
      "\n",
      "Best params: {'solver': 'newton-cg', 'penalty': 'l2', 'fit_intercept': True, 'C': 1}\n"
     ]
    }
   ],
   "source": [
    "# Hyperparameter tuning\n",
    "params = {\n",
    "    'penalty': ['l1', 'l2','elasticnet'],\n",
    "    'C':[0.0001, 0.001, 0.1, 1, 10, 100,1000],\n",
    "    'fit_intercept':[True, False],\n",
    "    'solver' : ['newton-cg', 'lbfgs', 'liblinear', 'sag', 'saga']\n",
    "}\n",
    "\n",
    "clf = RandomizedSearchCV(LogisticRegression(random_state=1, class_weight='balanced'),\n",
    "                         params,\n",
    "                         scoring='f1',\n",
    "                         verbose=1,\n",
    "                         random_state=1,\n",
    "                         cv=5,\n",
    "                         n_iter=20)\n",
    "\n",
    "search = clf.fit(X_train, y_train)\n",
    "\n",
    "print(\"\\nBest f1-score:\",search.best_score_)\n",
    "print(\"\\nBest params:\",search.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "elegant-sodium",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:05.907551Z",
     "iopub.status.busy": "2021-05-12T09:25:05.906645Z",
     "iopub.status.idle": "2021-05-12T09:25:06.197585Z",
     "shell.execute_reply": "2021-05-12T09:25:06.198487Z"
    },
    "papermill": {
     "duration": 0.367183,
     "end_time": "2021-05-12T09:25:06.198761",
     "exception": false,
     "start_time": "2021-05-12T09:25:05.831578",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "------------- Fold 1 -------------\n",
      "\n",
      "f1 score for validation set is 0.2274509803921569\n",
      "\n",
      "------------- Fold 2 -------------\n",
      "\n",
      "f1 score for validation set is 0.22137404580152675\n",
      "\n",
      "------------- Fold 3 -------------\n",
      "\n",
      "f1 score for validation set is 0.2222222222222222\n",
      "\n",
      "------------- Fold 4 -------------\n",
      "\n",
      "f1 score for validation set is 0.25702811244979923\n",
      "\n",
      "------------- Fold 5 -------------\n",
      "\n",
      "f1 score for validation set is 0.25\n",
      "\n",
      "Mean validation f1 score : 0.235615072173141\n",
      "\n",
      "F1 score for oofs is 0.23529411764705885\n"
     ]
    }
   ],
   "source": [
    "# Cross validation\n",
    "clf = LogisticRegression(random_state = 1, class_weight='balanced', **search.best_params_)\n",
    "oofs = run_kfold(clf, X_train, y_train, N_SPLITS=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "appropriate-infrared",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:06.386469Z",
     "iopub.status.busy": "2021-05-12T09:25:06.385672Z",
     "iopub.status.idle": "2021-05-12T09:25:06.586905Z",
     "shell.execute_reply": "2021-05-12T09:25:06.588110Z"
    },
    "papermill": {
     "duration": 0.275267,
     "end_time": "2021-05-12T09:25:06.588384",
     "exception": false,
     "start_time": "2021-05-12T09:25:06.313117",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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OYQNgDmEDYM7/AYHBFP6cJJP4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Final Logistic regression\n",
    "\n",
    "clf = LogisticRegression(random_state = 1,class_weight='balanced', **search.best_params_)\n",
    "clf.fit(X_train, y_train)\n",
    "\n",
    "preds_test = clf.predict_proba(X_test)[:, 1]\n",
    "\n",
    "cm = confusion_matrix(y_test, preds_test.round(), normalize='true')\n",
    "plt.figure(figsize=(5,5))\n",
    "sns.heatmap(cm, annot=True, cmap='Blues', cbar=False, fmt='.2f')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "gentle-tsunami",
   "metadata": {
    "papermill": {
     "duration": 0.065118,
     "end_time": "2021-05-12T09:25:06.732304",
     "exception": false,
     "start_time": "2021-05-12T09:25:06.667186",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Feature importance or coefficents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "olive-cabinet",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:06.876966Z",
     "iopub.status.busy": "2021-05-12T09:25:06.876389Z",
     "iopub.status.idle": "2021-05-12T09:25:06.879583Z",
     "shell.execute_reply": "2021-05-12T09:25:06.879986Z"
    },
    "papermill": {
     "duration": 0.078377,
     "end_time": "2021-05-12T09:25:06.880115",
     "exception": false,
     "start_time": "2021-05-12T09:25:06.801738",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature</th>\n",
       "      <th>coeff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>work_type_children</td>\n",
       "      <td>2.623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>age</td>\n",
       "      <td>2.469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>age_group_Teenager</td>\n",
       "      <td>0.698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>hypertension_1</td>\n",
       "      <td>0.534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>heart_disease_1</td>\n",
       "      <td>0.384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>smoking_status_formerly smoked</td>\n",
       "      <td>0.236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>smoking_status_smokes</td>\n",
       "      <td>0.216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>bmi</td>\n",
       "      <td>0.201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>avg_glucose_level</td>\n",
       "      <td>0.149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>work_type_Private</td>\n",
       "      <td>0.144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>age_group_Child</td>\n",
       "      <td>-0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>work_type_Self-employed</td>\n",
       "      <td>-0.012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Residence_type_Urban</td>\n",
       "      <td>-0.030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>bmi_group_Teenager</td>\n",
       "      <td>-0.049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>bmi_group_Child</td>\n",
       "      <td>-0.058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>gender_Male</td>\n",
       "      <td>-0.061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>work_type_Never_worked</td>\n",
       "      <td>-0.132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>smoking_status_never smoked</td>\n",
       "      <td>-0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ever_married_Yes</td>\n",
       "      <td>-0.273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>age_group_Elder</td>\n",
       "      <td>-0.689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>bmi_group_Elder</td>\n",
       "      <td>-1.344</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           feature  coeff\n",
       "0               work_type_children  2.623\n",
       "1                              age  2.469\n",
       "2               age_group_Teenager  0.698\n",
       "3                   hypertension_1  0.534\n",
       "4                  heart_disease_1  0.384\n",
       "5   smoking_status_formerly smoked  0.236\n",
       "6            smoking_status_smokes  0.216\n",
       "7                              bmi  0.201\n",
       "8                avg_glucose_level  0.149\n",
       "9                work_type_Private  0.144\n",
       "10                 age_group_Child -0.003\n",
       "11         work_type_Self-employed -0.012\n",
       "12            Residence_type_Urban -0.030\n",
       "13              bmi_group_Teenager -0.049\n",
       "14                 bmi_group_Child -0.058\n",
       "15                     gender_Male -0.061\n",
       "16          work_type_Never_worked -0.132\n",
       "17     smoking_status_never smoked -0.246\n",
       "18                ever_married_Yes -0.273\n",
       "19                 age_group_Elder -0.689\n",
       "20                 bmi_group_Elder -1.344"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp = pd.DataFrame([features, clf.coef_[0]]).T.sort_values(1, ascending=False).reset_index(drop=True)\n",
    "imp.columns=['feature', 'coeff']\n",
    "imp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "peripheral-fraction",
   "metadata": {
    "papermill": {
     "duration": 0.061848,
     "end_time": "2021-05-12T09:25:07.008286",
     "exception": false,
     "start_time": "2021-05-12T09:25:06.946438",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Save all the transformers\n",
    "One hot encoder<br>\n",
    "Standard scaler<br>\n",
    "Logistic regression<br>\n",
    "<b> Logistic regression is performing better at predicting the likelihood of Stroke. Which is what we want.!! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "blond-photograph",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:07.141631Z",
     "iopub.status.busy": "2021-05-12T09:25:07.140918Z",
     "iopub.status.idle": "2021-05-12T09:25:07.144449Z",
     "shell.execute_reply": "2021-05-12T09:25:07.143930Z"
    },
    "papermill": {
     "duration": 0.07327,
     "end_time": "2021-05-12T09:25:07.144590",
     "exception": false,
     "start_time": "2021-05-12T09:25:07.071320",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "with open(\"onehotencoder.pkl\", 'wb') as f:\n",
    "    pickle.dump(encoder, f)\n",
    "\n",
    "with open(\"scaler.pkl\", 'wb') as f:\n",
    "    pickle.dump(scaler, f)\n",
    "\n",
    "with open(\"model.pkl\", 'wb') as f:\n",
    "    pickle.dump(clf, f)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "swiss-turner",
   "metadata": {
    "papermill": {
     "duration": 0.06762,
     "end_time": "2021-05-12T09:25:07.280940",
     "exception": false,
     "start_time": "2021-05-12T09:25:07.213320",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Replicate the total pipeline for deployment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "handled-safety",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:07.412343Z",
     "iopub.status.busy": "2021-05-12T09:25:07.411537Z",
     "iopub.status.idle": "2021-05-12T09:25:07.414173Z",
     "shell.execute_reply": "2021-05-12T09:25:07.413758Z"
    },
    "papermill": {
     "duration": 0.070236,
     "end_time": "2021-05-12T09:25:07.414282",
     "exception": false,
     "start_time": "2021-05-12T09:25:07.344046",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Random data point\n",
    "X = [['Male', 67.0, 0, 1, 'Yes', 'Private', 'Urban', 228.69, 36.6, 'formerly smoked']]\n",
    "y_true = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "vietnamese-breath",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-12T09:25:07.563343Z",
     "iopub.status.busy": "2021-05-12T09:25:07.562413Z",
     "iopub.status.idle": "2021-05-12T09:25:07.573772Z",
     "shell.execute_reply": "2021-05-12T09:25:07.574447Z"
    },
    "papermill": {
     "duration": 0.097308,
     "end_time": "2021-05-12T09:25:07.574660",
     "exception": false,
     "start_time": "2021-05-12T09:25:07.477352",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "y_pred : 1\n"
     ]
    }
   ],
   "source": [
    "columns = ['gender', 'age', 'hypertension', 'heart_disease', 'ever_married','work_type', 'Residence_type','avg_glucose_level', 'bmi', 'smoking_status']\n",
    "\n",
    "X = pd.DataFrame(X, columns=columns)\n",
    "X[\"age_group\"] = X.age.apply(age_group)\n",
    "X[\"bmi_group\"] = X.age.apply(age_group)\n",
    "\n",
    "numerical = ['age', 'avg_glucose_level', 'bmi']\n",
    "categorical = ['gender', 'hypertension', 'heart_disease', 'ever_married', 'work_type', 'Residence_type', 'smoking_status','age_group','bmi_group']\n",
    "\n",
    "# Categorical encoding\n",
    "cols = encoder.get_feature_names(categorical)\n",
    "X.loc[:, cols] = encoder.transform(X[categorical])\n",
    "\n",
    "# Drop categorical features\n",
    "X.drop(categorical, axis=1, inplace=True)\n",
    "\n",
    "# Feature scaling\n",
    "X.loc[:, numerical] = scaler.transform(X[numerical])\n",
    "\n",
    "print('y_pred :', clf.predict(X)[0])"
   ]
  },
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   "id": "inner-institute",
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     "start_time": "2021-05-12T09:25:07.641351",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Thanks for reading!! Please upvote if you like this kernel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "different-nation",
   "metadata": {
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     "end_time": "2021-05-12T09:25:07.833310",
     "exception": false,
     "start_time": "2021-05-12T09:25:07.769935",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
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