2024-05-08 08:48:17 +02:00
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{
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"cells": [
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{
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"cell_type": "code",
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2024-06-07 11:20:34 +02:00
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"execution_count": 1,
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2024-05-08 08:48:17 +02:00
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"id": "37d611da-6f56-46d8-905a-62026750150c",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>age</th>\n",
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" <th>sex</th>\n",
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" <th>cp</th>\n",
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" <th>trestbps</th>\n",
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" <th>chol</th>\n",
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" <th>fbs</th>\n",
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" <th>restecg</th>\n",
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" <th>thalach</th>\n",
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" <th>exang</th>\n",
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" <th>oldpeak</th>\n",
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" <th>slope</th>\n",
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" <th>ca</th>\n",
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" <th>thal</th>\n",
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" <th>goal</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>63</td>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
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" <td>145</td>\n",
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" <td>233</td>\n",
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" <td>1</td>\n",
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" <td>2</td>\n",
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" <td>150</td>\n",
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" <td>0</td>\n",
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" <td>2.3</td>\n",
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" <td>3</td>\n",
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" <td>0.0</td>\n",
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" <td>6.0</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>67</td>\n",
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" <td>1</td>\n",
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" <td>4</td>\n",
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" <td>160</td>\n",
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" <td>286</td>\n",
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" <td>0</td>\n",
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" <td>2</td>\n",
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" <td>108</td>\n",
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" <td>1</td>\n",
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" <td>1.5</td>\n",
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" <td>2</td>\n",
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" <td>3.0</td>\n",
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" <td>3.0</td>\n",
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" <td>2</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>67</td>\n",
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" <td>1</td>\n",
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" <td>4</td>\n",
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" <td>120</td>\n",
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" <td>229</td>\n",
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" <td>0</td>\n",
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" <td>2</td>\n",
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" <td>129</td>\n",
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" <td>1</td>\n",
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" <td>2.6</td>\n",
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" <td>2</td>\n",
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" <td>2.0</td>\n",
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" <td>7.0</td>\n",
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" <td>1</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>37</td>\n",
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" <td>1</td>\n",
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" <td>3</td>\n",
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" <td>130</td>\n",
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" <td>250</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>187</td>\n",
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" <td>0</td>\n",
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" <td>3.5</td>\n",
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" <td>3</td>\n",
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" <td>0.0</td>\n",
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" <td>3.0</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>41</td>\n",
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" <td>0</td>\n",
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" <td>2</td>\n",
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" <td>130</td>\n",
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" <td>204</td>\n",
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" <td>0</td>\n",
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" <td>2</td>\n",
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" <td>172</td>\n",
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" <td>0</td>\n",
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" <td>1.4</td>\n",
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" <td>1</td>\n",
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" <td>0.0</td>\n",
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" <td>3.0</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" age sex cp trestbps chol fbs restecg thalach exang oldpeak slope \\\n",
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"0 63 1 1 145 233 1 2 150 0 2.3 3 \n",
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"1 67 1 4 160 286 0 2 108 1 1.5 2 \n",
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"2 67 1 4 120 229 0 2 129 1 2.6 2 \n",
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"3 37 1 3 130 250 0 0 187 0 3.5 3 \n",
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"4 41 0 2 130 204 0 2 172 0 1.4 1 \n",
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"\n",
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" ca thal goal \n",
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"0 0.0 6.0 0 \n",
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"1 3.0 3.0 2 \n",
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"2 2.0 7.0 1 \n",
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"3 0.0 3.0 0 \n",
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"4 0.0 3.0 0 "
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]
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},
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2024-06-07 11:20:34 +02:00
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"execution_count": 1,
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2024-05-08 08:48:17 +02:00
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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2024-06-07 11:20:34 +02:00
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"import pandas as pd\n",
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"import numpy as np\n",
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"\n",
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"df = pd.read_csv('./data/dataset_cleaned.csv')\n",
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"\n",
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"# extract all columns except 'goal' --> X\n",
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"X = df.loc[:, df.columns != 'goal']\n",
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"# extract only the column 'goal' --> y\n",
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"y = df.loc[:, 'goal']\n",
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"\n",
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"male=1\n",
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"female=0\n",
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2024-05-08 08:48:17 +02:00
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"\n",
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"df.head()"
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]
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},
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2024-06-05 11:20:55 +02:00
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{
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"cell_type": "code",
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2024-06-07 11:20:34 +02:00
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"execution_count": 2,
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2024-05-08 08:48:17 +02:00
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"id": "6b3e5424-4a7e-4e53-82b9-d78e38939834",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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2024-06-07 11:20:34 +02:00
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2024-05-08 08:48:17 +02:00
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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"\n",
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2024-06-07 11:20:34 +02:00
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"counts_male = sum(X['sex'] == male)\n",
|
|
|
|
|
"counts_female = sum(X['sex'] == female)\n",
|
|
|
|
|
"\n",
|
|
|
|
|
"counts_male_sick = sum(np.all([X['sex'] == male,\n",
|
|
|
|
|
" y > 0], axis=0))\n",
|
|
|
|
|
"counts_female_sick = sum(np.all([X['sex'] == female,\n",
|
|
|
|
|
" y > 0], axis=0))\n",
|
2024-05-08 08:48:17 +02:00
|
|
|
"\n",
|
|
|
|
|
"plt.bar([male, female], [counts_male, counts_female])\n",
|
2024-06-07 11:20:34 +02:00
|
|
|
"plt.bar([male, female], [counts_male_sick, counts_female_sick])\n",
|
|
|
|
|
"plt.xticks([male, female],['male', 'female'])\n",
|
2024-05-08 08:48:17 +02:00
|
|
|
"plt.title('Age distribution')\n",
|
2024-06-07 11:20:34 +02:00
|
|
|
"plt.legend(['healthy', 'sick'])\n",
|
2024-05-08 08:48:17 +02:00
|
|
|
"plt.show()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2024-06-07 11:20:34 +02:00
|
|
|
"execution_count": 3,
|
2024-05-08 08:48:17 +02:00
|
|
|
"id": "48fd2655-1dcc-41f6-9938-ef6ea937d52e",
|
|
|
|
|
"metadata": {
|
|
|
|
|
"tags": []
|
|
|
|
|
},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
2024-06-07 11:20:34 +02:00
|
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAjMAAAHFCAYAAAAHcXhbAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAt00lEQVR4nO3de1TVdb7/8dcudQsKpKZ7Q6GScrS8l46JY5IXyug2mmnapMdsLG2SrKWRldgqUOdkVk6Y5gVXmZWj5RzzQkelC3ZEG5KoMfuJSqMMZdzygqmf3x8t93EHXiDwuz/4fKz1Xcvv5/PZ3+97f4YVr/l8L7iMMUYAAACWusTpAgAAAH4LwgwAALAaYQYAAFiNMAMAAKxGmAEAAFYjzAAAAKsRZgAAgNUIMwAAwGqEGQAAYDXCDFBHvPzyy3K5XOrYsaPTpVRqz549crlcWrJkia8tKSlJLperSsc5fPiwkpKStHnz5ip9rrJztW7dWrfeemuVjnMuy5Yt05w5cyrtc7lcSkpKqtHzASDMAHXGokWLJEm5ubn63//9X4erOT9jx47Vli1bqvSZw4cPa/r06VUOM9U5V3WcLcxs2bJFY8eOrfUagIsNYQaoA7Zt26YvvvhC8fHxkqSFCxc6XNH5ufLKK3X99dfX6jkOHz58wc51Ltdff72uvPJKR2sA6iLCDFAHnAovM2bMUExMjJYvX+77JX667777TnfddZdCQkJ02WWXaeTIkcrKyqpw+Uf6JSDdfvvtatq0qRo2bKhu3brpnXfeOa969u/fr7vvvlshISEKCwvTsGHDVFBQUGFcZZd+Nm7cqNjYWDVr1kxBQUFq2bKlhgwZosOHD2vPnj1q3ry5JGn69OlyuVxyuVwaPXq03/E+//xz3XXXXWrSpInatGlzxnOdsmrVKnXu3FkNGzbUVVddpZdfftmvf8mSJXK5XNqzZ49f++bNm+VyuXyrRLGxsVqzZo327t3rq+30c1Z2menLL7/UHXfcoSZNmqhhw4bq2rWr0tLSKj3PW2+9palTpyoiIkKhoaEaMGCAdu7cWel3Ai4mhBnAckeOHNFbb72lHj16qGPHjhozZozKysr07rvv+o07dOiQbrzxRm3atEkzZ87UO++8I4/Ho2HDhlU45qZNm9S7d28VFxdr3rx5ev/999W1a1cNGzasQuiprJ4BAwZow4YNSklJ0bvvviuv11vpeX5tz549io+PV4MGDbRo0SKtW7dOM2bMUKNGjXTs2DGFh4dr3bp1kqT7779fW7Zs0ZYtW/T000/7HWfw4MFq27at3n33Xc2bN++s58zOzlZCQoIeffRRrVq1SjExMZo4caL+67/+65z1/tqrr76q3r17y+v1+mo726WtnTt3KiYmRrm5uXr55Ze1cuVKXXPNNRo9erRmzZpVYfyTTz6pvXv36vXXX9f8+fO1a9cu3XbbbTpx4kSVawXqFAPAakuXLjWSzLx584wxxpSVlZnGjRubPn36+I3761//aiSZtWvX+rWPGzfOSDKLFy/2tbVv395069bN/Pzzz35jb731VhMeHm5OnDhxxnpSU1ONJPP+++/7tT/wwAMVzjNt2jRz+n+GVqxYYSSZ7OzsMx7/+++/N5LMtGnTKvSdOt4zzzxzxr7TtWrVyrhcrgrnGzhwoAkNDTWHDh0yxhizePFiI8nk5eX5jdu0aZORZDZt2uRri4+PN61ataq09l/XPXz4cON2u82+ffv8xg0aNMgEBweb4uJiv/PccsstfuPeeecdI8ls2bKl0vMBFwtWZgDLLVy4UEFBQRo+fLgkqXHjxho6dKg+/vhj7dq1yzcuIyNDISEhuvnmm/0+f8899/jtf/vtt/rnP/+pkSNHSpKOHz/u22655RYdOHDgrJc2Nm3apJCQEN1+++1+7SNGjDjnd+natasaNGigP/3pT0pLS9Pu3bvP+ZnKDBky5LzHdujQQV26dPFrGzFihEpLS/X5559X6/zna+PGjerfv78iIyP92kePHq3Dhw9XWNX59Zx27txZkrR3795arRMIdIQZwGLffvutPvroI8XHx8sYo+LiYhUXF+uuu+6S9H9POEnSwYMH5fF4Khzj123//ve/JUmPP/646tev77eNHz9ekvTDDz+csaYzncfr9Z7z+7Rp00YffvihWrRooQkTJqhNmzZq06aNXnrppXN+9nTh4eHnPbayuk61HTx4sErnraqDBw9WWmtERESl52/WrJnfvtvtlvTLpT3gYlbP6QIAVN+iRYtkjNGKFSu0YsWKCv1paWl67rnndOmll6pZs2baunVrhTG/vjH38ssvlyQlJiZq8ODBlZ63Xbt2Z6zpfM9zJn369FGfPn104sQJbdu2Ta+88ooSEhLk8Xh8q0/nUpV311RW16m2U+GhYcOGkqTy8nK/cWcLdeejWbNmOnDgQIX2/fv3S/q//y0AnB0rM4ClTpw4obS0NLVp00abNm2qsD322GM6cOCA1q5dK0nq27evysrKfPunLF++3G+/Xbt2io6O1hdffKHu3btXuoWEhJyxrhtvvFFlZWVavXq1X/uyZcuq9P0uvfRS9ezZU3/9618lyXfJp6ZXI3Jzc/XFF1/4tS1btkwhISG69tprJf3ycj1J2rFjh9+4X3/HU/Wdb239+/fXxo0bfeHllKVLlyo4ONjxR8kBW7AyA1hq7dq12r9/v2bOnKnY2NgK/R07dtTcuXO1cOFC3XrrrRo1apRefPFF3XvvvXruuefUtm1brV27VuvXr5ckXXLJ//1/m9dee02DBg3STTfdpNGjR+uKK67Qjz/+qK+//lqff/55hSelTnfffffpxRdf1H333afnn39e0dHR+uCDD3znOZt58+Zp48aNio+PV8uWLXX06FHfpbIBAwZIkkJCQtSqVSu9//776t+/v5o2barLL7/cFziqKiIiQrfffruSkpIUHh6uN954Q+np6Zo5c6aCg4MlST169FC7du30+OOP6/jx42rSpIlWrVqlTz75pMLxOnXqpJUrVyo1NVXXXXedLrnkEnXv3r3Sc0+bNk3//d//rRtvvFHPPPOMmjZtqjfffFNr1qzRrFmzFBYWVq3vBFx0nL4DGUD13HnnnaZBgwamsLDwjGOGDx9u6tWrZwoKCowxxuzbt88MHjzYNG7c2ISEhJghQ4aYDz74oNKnj7744gtz9913mxYtWpj69esbr9dr+vXr53tq6my+++47M2TIEL/zZGZmnvNppi1btpg//OEPplWrVsbtdptmzZqZvn37mtWrV/sd/8MPPzTdunUzbrfbSDKjRo3yO973339foaYzPc0UHx9vVqxYYTp06GAaNGhgWrdubWbPnl3h8998842Ji4szoaGhpnnz5ubPf/6zWbNmTYWnmX788Udz1113mcsuu8y4XC6/c6qSp7BycnLMbbfdZsLCwkyDBg1Mly5d/ObImP97mundd9/1a8/Ly6swp8DFyGWMMQ7lKAABIDk5WU899ZT27dvH22kBWInLTMBFZO7cuZKk9u3b6+eff9bGjRv18ssv69577yXIALAWYQa4iAQHB+vFF1/Unj17VF5erpYtW2rKlCl66qmnnC4NAKqNy0wAAMBqPJoNAACsRpgBAABWI8wAAACr1fkbgE+ePKn9+/crJCSkSq84BwAAzjHGqKysTBEREX4v9axMnQ8z+/fvr/AXaQEAgB3y8/PP+eqIOh9mTv0Nmfz8fIWGhjpcDQAAOB+lpaWKjIw869+CO6XOh5lTl5ZCQ0MJMwAAWOZ8bhHhBmAAAGA1wgwAALAaYQYAAFiNMAMAAKxGmAEAAFYjzAAAAKsRZgAAgNUIMwAAwGqEGQAAYDXCDAAAsBphBgAAWI0wAwAArEaYAQAAViPMAAAAqxFmAACA1eo5XQAAXGxaP7HG6RKqbM+MeKdLAM6IlRkAAGA1wgwAALAaYQYAAFiNMAMAAKxGmAEAAFYjzAAAAKsRZgAAgNUIMwAAwGqEGQAAYDXCDAAAsBphBgAAWM3xMPOvf/1L9957r5o1a6bg4GB17dpV27dv9/UbY5SUlKSIiAgFBQUpNjZWubm5DlYMAAA
|
2024-05-08 08:48:17 +02:00
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"plt.hist(X['age'])\n",
|
|
|
|
|
"plt.xlabel('Age')\n",
|
|
|
|
|
"plt.ylabel('counts')\n",
|
|
|
|
|
"plt.title('Age distribution')\n",
|
|
|
|
|
"plt.show()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2024-06-07 11:20:34 +02:00
|
|
|
"execution_count": 4,
|
2024-05-08 08:48:17 +02:00
|
|
|
"id": "b9174a9d-6c8a-4915-9580-48f23cbdd038",
|
|
|
|
|
"metadata": {
|
|
|
|
|
"tags": []
|
|
|
|
|
},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
2024-06-07 11:20:34 +02:00
|
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAjMAAAHFCAYAAAAHcXhbAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAAB9VklEQVR4nO3dd3xT9f7H8ddJ0qR70EIHo5Q9CjJFhjIUlOFeIA4ExCtDhoKAgBWFMhRQURSuIl7lel38HKjgAFSGMpUlILOMUgrdadKM8/sjJFr2aHsyPs/HIw/NSZq8aZvk3XO+5/tVVFVVEUIIIYTwUTqtAwghhBBCXA0pM0IIIYTwaVJmhBBCCOHTpMwIIYQQwqdJmRFCCCGET5MyI4QQQgifJmVGCCGEED5NyowQQgghfJqUGSGEEEL4NCkzQviJV199FUVRSE1N1TrKOR04cABFUXj33Xc929LS0lAU5bIex2w2k5aWxsqVKy/r6871XDVr1qRXr16X9TgXs3jxYubMmXPO2xRFIS0trUyfTwghZUYIv/HOO+8AsH37dn799VeN01yagQMHsnbt2sv6GrPZzPPPP3/ZZeZKnutKXKjMrF27loEDB5Z7BiECjZQZIfzAhg0b+P333+nZsycAb7/9tsaJLk21atW47rrryvU5zGZzhT3XxVx33XVUq1ZN0wxC+CMpM0L4AXd5mTZtGu3atePDDz/0fIj/0+HDh7nnnnuIiIggOjqavn37sn79+rMO/4CrIN12221UqlSJ4OBgmjdvzkcffXRJeY4ePcp9991HREQEUVFR3H///WRmZp51v3Md+vnxxx/p1KkTsbGxhISEUKNGDe6++27MZjMHDhygcuXKADz//PMoioKiKPTr16/U423atIl77rmHmJgYateufd7ncluyZAlNmzYlODiYWrVq8eqrr5a6/d1330VRFA4cOFBq+8qVK1EUxbOXqFOnTixdupSDBw96sv3zOc91mGnbtm3cfvvtxMTEEBwcTLNmzVi0aNE5n+e///0vzz77LElJSURGRnLTTTexa9euc/6bhAgkUmaE8HHFxcX897//pXXr1qSmptK/f38KCgr4+OOPS92vqKiIzp07s2LFCqZPn85HH31EfHw8999//1mPuWLFCtq3b09ubi5vvvkmn3/+Oc2aNeP+++8/q/ScK89NN93E8uXLSU9P5+OPPyYhIeGcz3OmAwcO0LNnT4xGI++88w7ffvst06ZNIywsjJKSEhITE/n2228BGDBgAGvXrmXt2rVMnDix1OPcdddd1KlTh48//pg333zzgs+5ZcsWRowYwciRI1myZAnt2rVj+PDhvPTSSxfNe6Y33niD9u3bk5CQ4Ml2oUNbu3btol27dmzfvp1XX32Vzz77jEaNGtGvXz9mzJhx1v3Hjx/PwYMH+fe//838+fPZs2cPt956Kw6H47KzCuFXVCGET3vvvfdUQH3zzTdVVVXVgoICNTw8XL3++utL3e/1119XAfWbb74ptf3xxx9XAXXhwoWebQ0aNFCbN2+u2my2Uvft1auXmpiYqDocjvPmmTdvngqon3/+eantjz322FnP89xzz6n/fBv65JNPVEDdsmXLeR//xIkTKqA+99xzZ93mfrxJkyad97Z/Sk5OVhVFOev5unbtqkZGRqpFRUWqqqrqwoULVUDdv39/qfutWLFCBdQVK1Z4tvXs2VNNTk4+Z/Yzc/fu3Vs1mUzqoUOHSt2ve/fuamhoqJqbm1vqeXr06FHqfh999JEKqGvXrj3n8wkRKGTPjBA+7u233yYkJITevXsDEB4ezr333svPP//Mnj17PPdbtWoVERER3HLLLaW+vk+fPqWu//XXX/z555/07dsXALvd7rn06NGDY8eOXfDQxooVK4iIiOC2224rtf2BBx646L+lWbNmGI1GBg0axKJFi9i3b99Fv+Zc7r777ku+b+PGjbnmmmtKbXvggQfIz89n06ZNV/T8l+rHH3/kxhtvpHr16qW29+vXD7PZfNZenTO/p02bNgXg4MGD5ZpTCG8nZUYIH/bXX3/x008/0bNnT1RVJTc3l9zcXO655x7g7zOcAE6ePEl8fPxZj3HmtuPHjwPw9NNPExQUVOoyePBgALKzs8+b6XzPk5CQcNF/T+3atfn++++pUqUKQ4YMoXbt2tSuXZtXXnnlol/7T4mJiZd833Plcm87efLkZT3v5Tp58uQ5syYlJZ3z+WNjY0tdN5lMgOvQnhCBzKB1ACHElXvnnXdQVZVPPvmETz755KzbFy1axIsvvoheryc2NpbffvvtrPucOTA3Li4OgHHjxnHXXXed83nr169/3kyX+jznc/3113P99dfjcDjYsGEDr732GiNGjCA+Pt6z9+liLmfumnPlcm9zl4fg4GAArFZrqftdqNRditjYWI4dO3bW9qNHjwJ//yyEEBcme2aE8FEOh4NFixZRu3ZtVqxYcdblqaee4tixY3zzzTcAdOzYkYKCAs91tw8//LDU9fr161O3bl1+//13WrVqdc5LRETEeXN17tyZgoICvvjii1LbFy9efFn/Pr1eT5s2bXj99dcBPId8ynpvxPbt2/n9999LbVu8eDERERG0aNECcE2uB/DHH3+Uut+Z/0Z3vkvNduONN/Ljjz96yovbe++9R2hoqOankgvhK2TPjBA+6ptvvuHo0aNMnz6dTp06nXV7amoqc+fO5e2336ZXr1488sgjzJ49mwcffJAXX3yROnXq8M0337Bs2TIAdLq//7Z566236N69OzfffDP9+vWjatWqnDp1ip07d7Jp06azzpT6p4cffpjZs2fz8MMPM2XKFOrWrcvXX3/teZ4LefPNN/nxxx/p2bMnNWrUwGKxeA6V3XTTTQBERESQnJzM559/zo033kilSpWIi4vzFI7LlZSUxG233UZaWhqJiYm8//77fPfdd0yfPp3Q0FAAWrduTf369Xn66aex2+3ExMSwZMkSfvnll7Mer0mTJnz22WfMmzePli1botPpaNWq1Tmf+7nnnuOrr76ic+fOTJo0iUqVKvHBBx+wdOlSZsyYQVRU1BX9m4QIOFqPQBZCXJk77rhDNRqNalZW1nnv07t3b9VgMKiZmZmqqqrqoUOH1LvuuksNDw9XIyIi1Lvvvlv9+uuvz3n20e+//67ed999apUqVdSgoCA1ISFB7dKli+esqQs5fPiwevfdd5d6njVr1lz0bKa1a9eqd955p5qcnKyaTCY1NjZW7dixo/rFF1+Uevzvv/9ebd68uWoymVRAfeSRR0o93okTJ87KdL6zmXr27Kl+8sknauPGjVWj0ajWrFlTnTVr1llfv3v3brVbt25qZGSkWrlyZXXYsGHq0qVLzzqb6dSpU+o999yjRkdHq4qilHpOznEW1tatW9Vbb71VjYqKUo1Go3rNNdeU+h6p6t9nM3388celtu/fv/+s76kQgUhRVVXVqEcJIbzA1KlTmTBhAocOHZLZaYUQPkkOMwkRQObOnQtAgwYNsNls/Pjjj7z66qs8+OCDUmSEED5LyowQASQ0NJTZs2dz4MABrFYrNWrU4JlnnmHChAlaRxNCiCsmh5mEEEII4dPk1GwhhBBC+DQpM0IIIYTwaVJmhBBCCOHT/H4AsNPp5OjRo0RERFzWFOdCCCGE0I6qqhQUFJCUlFRqUs9z8fsyc/To0bNWpBVCCCGEb8jIyLjo1BF+X2bca8hkZGQQGRmpcRohhBBCXIr8/HyqV69+wbXg3Py+zLgPLUVGRkqZEUIIIXzMpQwRkQHAQgghhPBpUmaEEEII4dOkzAghhBDCp0mZEUIIIYRPkzIjhBBCCJ8mZUYIIYQQPk3KjBBCCCF8mpQZIYQQQvg0KTNCCCGE8GlSZoQQQgjh06TMCCGEEMKnSZkRQgghhE+TMiOEEEIIn+b3q2aLwLJixQp+/fVXmjdvzs0336x1HCGEEBVAUVVV1TpEecrPzycqKoq8vDwiIyO1jiPKkaqqdO3aFbvdDsCyZcswmUwapxJCCHElLufzWw4zCb9RXFzsKTIAhYWFGqYRQpQ1VVXJyMjA6XRqHUV4GSkzwm8
|
2024-05-08 08:48:17 +02:00
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"ax = sns.violinplot(X, x='sex', y='age')\n",
|
|
|
|
|
"ax.set_xticklabels(['male', 'female'])\n",
|
|
|
|
|
"plt.title('Age distribution')\n",
|
|
|
|
|
"plt.show()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2024-06-07 11:20:34 +02:00
|
|
|
"execution_count": 5,
|
2024-05-08 08:48:17 +02:00
|
|
|
"id": "522ff499-cd7f-4417-ae7d-d637402505b8",
|
|
|
|
|
"metadata": {
|
|
|
|
|
"tags": []
|
|
|
|
|
},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
2024-06-07 11:20:34 +02:00
|
|
|
"image/png": "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
|
2024-05-08 08:48:17 +02:00
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"ax = plt.hist(X['chol'])\n",
|
|
|
|
|
"plt.xlabel('Cholesterin')\n",
|
|
|
|
|
"plt.ylabel('counts')\n",
|
|
|
|
|
"plt.title('Cholesterin distribution')\n",
|
|
|
|
|
"plt.show()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2024-06-07 11:20:34 +02:00
|
|
|
"execution_count": 6,
|
2024-05-08 08:48:17 +02:00
|
|
|
"id": "f220fadf-33ec-4bf6-a225-a2c874f02088",
|
|
|
|
|
"metadata": {
|
|
|
|
|
"tags": []
|
|
|
|
|
},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
2024-06-07 11:20:34 +02:00
|
|
|
"image/png": "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
|
2024-05-08 08:48:17 +02:00
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"plt.hist(X['trestbps'])\n",
|
|
|
|
|
"plt.xlabel('Blood pressure (rest)')\n",
|
|
|
|
|
"plt.ylabel('counts')\n",
|
|
|
|
|
"plt.title('Blood pressure distribution')\n",
|
|
|
|
|
"plt.show()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2024-06-07 11:20:34 +02:00
|
|
|
"execution_count": 7,
|
2024-05-08 08:48:17 +02:00
|
|
|
"id": "f568c911-d961-4d7f-87b1-f25dd5403cff",
|
|
|
|
|
"metadata": {
|
|
|
|
|
"tags": []
|
|
|
|
|
},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
2024-06-07 11:20:34 +02:00
|
|
|
"image/png": "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
|
2024-05-08 08:48:17 +02:00
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"plt.boxplot(X['trestbps'])\n",
|
|
|
|
|
"plt.ylabel('Blood pressure (rest)')\n",
|
|
|
|
|
"plt.title('Blood pressure')\n",
|
|
|
|
|
"plt.show()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2024-06-07 11:20:34 +02:00
|
|
|
"execution_count": 8,
|
2024-05-08 08:48:17 +02:00
|
|
|
"id": "5c174a9d-59b7-4efe-a0eb-a132388c1d2a",
|
|
|
|
|
"metadata": {
|
|
|
|
|
"tags": []
|
|
|
|
|
},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
2024-06-07 11:20:34 +02:00
|
|
|
"image/png": "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
|
2024-05-08 08:48:17 +02:00
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"from sklearn.linear_model import LinearRegression\n",
|
|
|
|
|
"\n",
|
|
|
|
|
"model = LinearRegression()\n",
|
|
|
|
|
"x = np.array(X['age'])\n",
|
|
|
|
|
"x = x[:, np.newaxis]\n",
|
|
|
|
|
"reg = model.fit(x, X['chol'])\n",
|
|
|
|
|
"pred = reg.predict(x)\n",
|
|
|
|
|
"\n",
|
2024-06-07 11:20:34 +02:00
|
|
|
"sick = y != 0\n",
|
2024-05-08 08:48:17 +02:00
|
|
|
"\n",
|
|
|
|
|
"sns.scatterplot(X, x='age', y='chol', hue='sex')\n",
|
|
|
|
|
"plt.plot(x, pred, color='black')\n",
|
|
|
|
|
"plt.xlabel('Age')\n",
|
|
|
|
|
"plt.ylabel('Chol')\n",
|
2024-06-07 11:20:34 +02:00
|
|
|
"plt.title('Chol / Age split by sex')\n",
|
|
|
|
|
"plt.legend(['male', 'female'])\n",
|
|
|
|
|
"plt.show()"
|
2024-05-08 08:48:17 +02:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2024-06-07 11:20:34 +02:00
|
|
|
"execution_count": 9,
|
2024-05-08 08:48:17 +02:00
|
|
|
"id": "b3d627cf-3ec9-4cd9-bee6-5baeb9d1a22d",
|
|
|
|
|
"metadata": {
|
|
|
|
|
"tags": []
|
|
|
|
|
},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
2024-06-07 11:20:34 +02:00
|
|
|
"image/png": "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
|
2024-05-08 08:48:17 +02:00
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"model = LinearRegression()\n",
|
|
|
|
|
"x = np.array(X['chol'])\n",
|
|
|
|
|
"x = x[:, np.newaxis]\n",
|
|
|
|
|
"reg = model.fit(x, X['trestbps'])\n",
|
|
|
|
|
"pred = reg.predict(x)\n",
|
|
|
|
|
"\n",
|
2024-06-07 11:20:34 +02:00
|
|
|
"sick = y != 0\n",
|
2024-05-08 08:48:17 +02:00
|
|
|
"\n",
|
|
|
|
|
"sns.scatterplot(X, x='chol', y='trestbps', hue='sex')\n",
|
|
|
|
|
"plt.plot(x, pred, color='black')\n",
|
|
|
|
|
"plt.xlabel('Chol')\n",
|
|
|
|
|
"plt.ylabel('Blood pressure (rest)')\n",
|
2024-06-07 11:20:34 +02:00
|
|
|
"plt.title('Blood pressure / Age split by sex')\n",
|
|
|
|
|
"plt.legend(['male', 'female'])\n",
|
|
|
|
|
"plt.show()"
|
2024-05-08 08:48:17 +02:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2024-06-07 11:20:34 +02:00
|
|
|
"execution_count": 10,
|
2024-05-08 08:48:17 +02:00
|
|
|
"id": "3a6dc91a-f3e9-4d7e-9e4b-58c59d24463c",
|
|
|
|
|
"metadata": {
|
|
|
|
|
"tags": []
|
|
|
|
|
},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
2024-06-07 11:20:34 +02:00
|
|
|
"image/png": "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
|
2024-05-08 08:48:17 +02:00
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"corr = df.corr()\n",
|
|
|
|
|
"\n",
|
2024-06-07 11:20:34 +02:00
|
|
|
"sns.heatmap(corr)\n",
|
|
|
|
|
"plt.show()"
|
2024-05-08 08:48:17 +02:00
|
|
|
]
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"metadata": {
|
|
|
|
|
"kernelspec": {
|
|
|
|
|
"display_name": "Python 3 (ipykernel)",
|
|
|
|
|
"language": "python",
|
|
|
|
|
"name": "python3"
|
|
|
|
|
},
|
|
|
|
|
"language_info": {
|
|
|
|
|
"codemirror_mode": {
|
|
|
|
|
"name": "ipython",
|
|
|
|
|
"version": 3
|
|
|
|
|
},
|
|
|
|
|
"file_extension": ".py",
|
|
|
|
|
"mimetype": "text/x-python",
|
|
|
|
|
"name": "python",
|
|
|
|
|
"nbconvert_exporter": "python",
|
|
|
|
|
"pygments_lexer": "ipython3",
|
2024-06-05 11:20:55 +02:00
|
|
|
"version": "3.11.7"
|
2024-05-08 08:48:17 +02:00
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
"nbformat": 4,
|
|
|
|
|
"nbformat_minor": 5
|
|
|
|
|
}
|
