211 lines (210 with data), 39.7 kB

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "00b82428",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   id    age  gender  height  weight  ap_hi  ap_lo  cholesterol  gluc  smoke  \\\n",
      "0   0  18393       2     168    62.0    110     80            1     1      0   \n",
      "1   1  20228       1     156    85.0    140     90            3     1      0   \n",
      "2   2  18857       1     165    64.0    130     70            3     1      0   \n",
      "3   3  17623       2     169    82.0    150    100            1     1      0   \n",
      "4   4  17474       1     156    56.0    100     60            1     1      0   \n",
      "\n",
      "   alco  active  cardio  \n",
      "0     0       1       0  \n",
      "1     0       1       1  \n",
      "2     0       0       1  \n",
      "3     0       1       1  \n",
      "4     0       0       0  \n",
      "The average age of smokers  52.30366281251596\n",
      "The most repeated age of smokers  55.85205479452055\n",
      "The percent of smokers that get heart diseases is  47.47933214459394\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "cardio_data = pd.read_csv('cardio_train.csv', sep=';')\n",
    "print(cardio_data.head())\n",
    "smokers = cardio_data[cardio_data['smoke'] == 1]\n",
    "average_age = smokers['age'].mean()\n",
    "mode_age = smokers['age'].mode()[0]\n",
    "print('The average age of smokers ', average_age / 365)\n",
    "print('The most repeated age of smokers ', mode_age / 365)\n",
    "smokers_heart_disease = smokers[smokers['cardio']==1]\n",
    "smokers__heart_disease = smokers[smokers['cardio']==0]\n",
    "percent_of__smokers =  smokers_heart_disease.size/smokers.size*100\n",
    "print('The percent of smokers that get heart diseases is ',percent_of__smokers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b882d2a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The percent of non-smokers that get heart diseases is  50.21071266312607\n"
     ]
    }
   ],
   "source": [
    "nonsmokers = cardio_data[cardio_data['smoke'] == 0]\n",
    "nonsmokers_heart_disease = nonsmokers[nonsmokers['cardio']==1]\n",
    "nonsmokers__heart_disease = nonsmokers[nonsmokers['cardio']==0]\n",
    "percent_of_non_smokers =  nonsmokers_heart_disease.size/nonsmokers.size*100\n",
    "print('The percent of non-smokers that get heart diseases is ',percent_of_non_smokers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cc7922cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  HeartDisease    BMI Smoking AlcoholDrinking Stroke  PhysicalHealth  \\\n",
      "0           No  16.60     Yes              No     No             3.0   \n",
      "1           No  20.34      No              No    Yes             0.0   \n",
      "2           No  26.58     Yes              No     No            20.0   \n",
      "3           No  24.21      No              No     No             0.0   \n",
      "4           No  23.71      No              No     No            28.0   \n",
      "\n",
      "   MentalHealth DiffWalking     Sex  AgeCategory   Race Diabetic  \\\n",
      "0          30.0          No  Female        55-59  White      Yes   \n",
      "1           0.0          No  Female  80 or older  White       No   \n",
      "2          30.0          No    Male        65-69  White      Yes   \n",
      "3           0.0          No  Female        75-79  White       No   \n",
      "4           0.0         Yes  Female        40-44  White       No   \n",
      "\n",
      "  PhysicalActivity  GenHealth  SleepTime Asthma KidneyDisease SkinCancer  \n",
      "0              Yes  Very good        5.0    Yes            No        Yes  \n",
      "1              Yes  Very good        7.0     No            No         No  \n",
      "2              Yes       Fair        8.0    Yes            No         No  \n",
      "3               No       Good        6.0     No            No        Yes  \n",
      "4              Yes  Very good        8.0     No            No         No  \n"
     ]
    }
   ],
   "source": [
    "cardio_data_2 = pd.read_csv('heart_data.csv')\n",
    "print(cardio_data_2.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9bb3ff25",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The percent of smokers that get heart diseases is  12.157715983867543\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "smokers = cardio_data_2[cardio_data_2['Smoking']=='Yes']\n",
    "smokers['HeartDisease'].hist()\n",
    "smokers_heart_disease = smokers[smokers['HeartDisease']=='Yes']\n",
    "smokers__heart_disease = smokers[smokers['HeartDisease']=='No']\n",
    "percent_of__smokers =  smokers_heart_disease.size/smokers.size*100\n",
    "print('The percent of smokers that get heart diseases is ',percent_of__smokers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7e85f38d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The percent of non-smokers that get heart diseases is  6.03341370078824\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nonsmokers = cardio_data_2[cardio_data_2['Smoking']=='No']\n",
    "nonsmokers['HeartDisease'].hist()\n",
    "nonsmokers_heart_disease = nonsmokers[nonsmokers['HeartDisease']=='Yes']\n",
    "nonsmokers_non_heart_disease = nonsmokers[nonsmokers['HeartDisease']=='No']\n",
    "percent_of_non_smokers =  nonsmokers_heart_disease.size/nonsmokers.size*100\n",
    "print('The percent of non-smokers that get heart diseases is ',percent_of_non_smokers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "49605c69",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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",
   "version": "3.10.7"
  },
  "vscode": {
   "interpreter": {
    "hash": "3bd8617b38ef4fa5b1c1552c94826c5d43d8082c101bf117576360b493384e0f"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}