 HeartDisease.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Veri seti linki Kaggle : https://www.kaggle.com/ronitf/heart-disease-uci"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"heart.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "1   37    1   2       130   250    0        1      187      0      3.5      0   \n",
       "2   41    0   1       130   204    0        0      172      0      1.4      2   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "1   0     2       1  \n",
       "2   0     2       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  "
      ]
     },
     "execution_count": 368,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.rename(columns = {\"age\" : \"Yas\",\n",
    "                           \"sex\" : \"Cinsiyet\", #1:Erkek 0:Kadın\n",
    "                           \"cp\" : \"GogusAgrisi\",\n",
    "                           \"trestbps\" : \"KanBasinci\",\n",
    "                           \"chol\" : \"Kolesterol\",\n",
    "                           \"fbs\" : \"KanSekeri\",   # kansekeri > 120 ise 1 degilse 0\n",
    "                           \"restecg\" : \"Elektrokardiyografik\",\n",
    "                           \"thalach\" : \"KalpAtisHizi\",\n",
    "                           \"exang\" : \"KalpAgrisi\",  # 1 : evet, 0 : hayir\n",
    "                           \"oldpeak\" : \"ST\", #  göğüs ağrısı sırasında olan ST depresyonu, ağrı geçtikten birkaç dakika sonra kaybolabilir.\n",
    "                           \"slope\" : \"STEgim\",\n",
    "                           \"ca\" : \"RenklendirilenDamarSayi\",\n",
    "                           \"target\": \"Sonuc\"})  # 0 : Hastalik yok, 1 : Hastalik var"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Yas</th>\n",
       "      <th>Cinsiyet</th>\n",
       "      <th>GogusAgrisi</th>\n",
       "      <th>KanBasinci</th>\n",
       "      <th>Kolesterol</th>\n",
       "      <th>KanSekeri</th>\n",
       "      <th>Elektrokardiyografik</th>\n",
       "      <th>KalpAtisHizi</th>\n",
       "      <th>KalpAgrisi</th>\n",
       "      <th>ST</th>\n",
       "      <th>STEgim</th>\n",
       "      <th>RenklendirilenDamarSayi</th>\n",
       "      <th>thal</th>\n",
       "      <th>Sonuc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Yas  Cinsiyet  GogusAgrisi  KanBasinci  Kolesterol  KanSekeri  \\\n",
       "0   63         1            3         145         233          1   \n",
       "1   37         1            2         130         250          0   \n",
       "2   41         0            1         130         204          0   \n",
       "3   56         1            1         120         236          0   \n",
       "4   57         0            0         120         354          0   \n",
       "\n",
       "   Elektrokardiyografik  KalpAtisHizi  KalpAgrisi   ST  STEgim  \\\n",
       "0                     0           150           0  2.3       0   \n",
       "1                     1           187           0  3.5       0   \n",
       "2                     0           172           0  1.4       2   \n",
       "3                     1           178           0  0.8       2   \n",
       "4                     1           163           1  0.6       2   \n",
       "\n",
       "   RenklendirilenDamarSayi  thal  Sonuc  \n",
       "0                        0     1      1  \n",
       "1                        0     2      1  \n",
       "2                        0     2      1  \n",
       "3                        0     2      1  \n",
       "4                        0     2      1  "
      ]
     },
     "execution_count": 370,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop([\"thal\", \"RenklendirilenDamarSayi\", \"STEgim\"], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Yas</th>\n",
       "      <th>Cinsiyet</th>\n",
       "      <th>GogusAgrisi</th>\n",
       "      <th>KanBasinci</th>\n",
       "      <th>Kolesterol</th>\n",
       "      <th>KanSekeri</th>\n",
       "      <th>Elektrokardiyografik</th>\n",
       "      <th>KalpAtisHizi</th>\n",
       "      <th>KalpAgrisi</th>\n",
       "      <th>ST</th>\n",
       "      <th>Sonuc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Yas  Cinsiyet  GogusAgrisi  KanBasinci  Kolesterol  KanSekeri  \\\n",
       "0   63         1            3         145         233          1   \n",
       "1   37         1            2         130         250          0   \n",
       "2   41         0            1         130         204          0   \n",
       "3   56         1            1         120         236          0   \n",
       "4   57         0            0         120         354          0   \n",
       "\n",
       "   Elektrokardiyografik  KalpAtisHizi  KalpAgrisi   ST  Sonuc  \n",
       "0                     0           150           0  2.3      1  \n",
       "1                     1           187           0  3.5      1  \n",
       "2                     0           172           0  1.4      1  \n",
       "3                     1           178           0  0.8      1  \n",
       "4                     1           163           1  0.6      1  "
      ]
     },
     "execution_count": 372,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yas                     0\n",
       "Cinsiyet                0\n",
       "GogusAgrisi             0\n",
       "KanBasinci              0\n",
       "Kolesterol              0\n",
       "KanSekeri               0\n",
       "Elektrokardiyografik    0\n",
       "KalpAtisHizi            0\n",
       "KalpAgrisi              0\n",
       "ST                      0\n",
       "Sonuc                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 373,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 303 entries, 0 to 302\n",
      "Data columns (total 11 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   Yas                   303 non-null    int64  \n",
      " 1   Cinsiyet              303 non-null    int64  \n",
      " 2   GogusAgrisi           303 non-null    int64  \n",
      " 3   KanBasinci            303 non-null    int64  \n",
      " 4   Kolesterol            303 non-null    int64  \n",
      " 5   KanSekeri             303 non-null    int64  \n",
      " 6   Elektrokardiyografik  303 non-null    int64  \n",
      " 7   KalpAtisHizi          303 non-null    int64  \n",
      " 8   KalpAgrisi            303 non-null    int64  \n",
      " 9   ST                    303 non-null    float64\n",
      " 10  Sonuc                 303 non-null    int64  \n",
      "dtypes: float64(1), int64(10)\n",
      "memory usage: 26.2 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 375,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "58    19\n",
       "57    17\n",
       "54    16\n",
       "59    14\n",
       "52    13\n",
       "51    12\n",
       "62    11\n",
       "44    11\n",
       "60    11\n",
       "56    11\n",
       "64    10\n",
       "41    10\n",
       "63     9\n",
       "67     9\n",
       "55     8\n",
       "45     8\n",
       "42     8\n",
       "53     8\n",
       "61     8\n",
       "65     8\n",
       "43     8\n",
       "66     7\n",
       "50     7\n",
       "48     7\n",
       "46     7\n",
       "49     5\n",
       "47     5\n",
       "39     4\n",
       "35     4\n",
       "68     4\n",
       "70     4\n",
       "40     3\n",
       "71     3\n",
       "69     3\n",
       "38     3\n",
       "34     2\n",
       "37     2\n",
       "77     1\n",
       "76     1\n",
       "74     1\n",
       "29     1\n",
       "Name: Yas, dtype: int64"
      ]
     },
     "execution_count": 375,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Yas.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(303, 11)"
      ]
     },
     "execution_count": 376,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 377,
   "metadata": {},
   "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>Yas</th>\n",
       "      <th>Cinsiyet</th>\n",
       "      <th>GogusAgrisi</th>\n",
       "      <th>KanBasinci</th>\n",
       "      <th>Kolesterol</th>\n",
       "      <th>KanSekeri</th>\n",
       "      <th>Elektrokardiyografik</th>\n",
       "      <th>KalpAtisHizi</th>\n",
       "      <th>KalpAgrisi</th>\n",
       "      <th>ST</th>\n",
       "      <th>Sonuc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>303.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>54.366337</td>\n",
       "      <td>0.683168</td>\n",
       "      <td>0.966997</td>\n",
       "      <td>131.623762</td>\n",
       "      <td>246.264026</td>\n",
       "      <td>0.148515</td>\n",
       "      <td>0.528053</td>\n",
       "      <td>149.646865</td>\n",
       "      <td>0.326733</td>\n",
       "      <td>1.039604</td>\n",
       "      <td>0.544554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.082101</td>\n",
       "      <td>0.466011</td>\n",
       "      <td>1.032052</td>\n",
       "      <td>17.538143</td>\n",
       "      <td>51.830751</td>\n",
       "      <td>0.356198</td>\n",
       "      <td>0.525860</td>\n",
       "      <td>22.905161</td>\n",
       "      <td>0.469794</td>\n",
       "      <td>1.161075</td>\n",
       "      <td>0.498835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>126.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>47.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>211.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>133.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>55.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>153.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>61.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>274.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>77.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>564.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>202.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.200000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Yas    Cinsiyet  GogusAgrisi  KanBasinci  Kolesterol  \\\n",
       "count  303.000000  303.000000   303.000000  303.000000  303.000000   \n",
       "mean    54.366337    0.683168     0.966997  131.623762  246.264026   \n",
       "std      9.082101    0.466011     1.032052   17.538143   51.830751   \n",
       "min     29.000000    0.000000     0.000000   94.000000  126.000000   \n",
       "25%     47.500000    0.000000     0.000000  120.000000  211.000000   \n",
       "50%     55.000000    1.000000     1.000000  130.000000  240.000000   \n",
       "75%     61.000000    1.000000     2.000000  140.000000  274.500000   \n",
       "max     77.000000    1.000000     3.000000  200.000000  564.000000   \n",
       "\n",
       "        KanSekeri  Elektrokardiyografik  KalpAtisHizi  KalpAgrisi          ST  \\\n",
       "count  303.000000            303.000000    303.000000  303.000000  303.000000   \n",
       "mean     0.148515              0.528053    149.646865    0.326733    1.039604   \n",
       "std      0.356198              0.525860     22.905161    0.469794    1.161075   \n",
       "min      0.000000              0.000000     71.000000    0.000000    0.000000   \n",
       "25%      0.000000              0.000000    133.500000    0.000000    0.000000   \n",
       "50%      0.000000              1.000000    153.000000    0.000000    0.800000   \n",
       "75%      0.000000              1.000000    166.000000    1.000000    1.600000   \n",
       "max      1.000000              2.000000    202.000000    1.000000    6.200000   \n",
       "\n",
       "            Sonuc  \n",
       "count  303.000000  \n",
       "mean     0.544554  \n",
       "std      0.498835  \n",
       "min      0.000000  \n",
       "25%      0.000000  \n",
       "50%      1.000000  \n",
       "75%      1.000000  \n",
       "max      1.000000  "
      ]
     },
     "execution_count": 377,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7.333333333333333\n"
     ]
    }
   ],
   "source": [
    "sirali = np.sort(df.KalpAtisHizi)\n",
    "max_deger = np.max(sirali)\n",
    "min_deger = np.min(sirali)\n",
    "DG = max_deger - min_deger\n",
    "k = math.ceil(np.sqrt(303))\n",
    "a = 1\n",
    "c = (DG+a)/k\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_alt = np.zeros((k, 1), dtype=np.float)\n",
    "s_ust = np.zeros((k, 1), dtype=np.float)\n",
    "s_alt[0] = min_deger\n",
    "s_ust[0] = s_alt[1]-0.1\n",
    "for i in range(1, k):\n",
    "    s_alt[i] = (s_alt[i-1] + c)\n",
    "s_ust[:] = s_alt[:] + (c-0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Sınıf orta degeleri bulma\n",
    "s_ort = np.zeros((k, 1), dtype=np.float)\n",
    "for i in range(k):\n",
    "    s_ort[i] = (s_alt[i] + s_ust[i]) / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in df.KalpAtisHizi:\n",
    "    for j in range(k):\n",
    "        if((s_alt[j]<i) & (i<s_ust[j])):\n",
    "            z = s_ort[j]\n",
    "            df.loc[df.KalpAtisHizi == i, \"KalpAtisHizi\"] = int(z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "162    44\n",
       "155    37\n",
       "169    36\n",
       "140    35\n",
       "147    29\n",
       "177    21\n",
       "133    20\n",
       "125    17\n",
       "118    15\n",
       "111    13\n",
       "184    11\n",
       "103     6\n",
       "96      5\n",
       "159     4\n",
       "191     4\n",
       "181     2\n",
       "89      2\n",
       "199     1\n",
       "71      1\n",
       "Name: KalpAtisHizi, dtype: int64"
      ]
     },
     "execution_count": 382,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.KalpAtisHizi.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 383,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.7222222222222223\n"
     ]
    }
   ],
   "source": [
    "sirali = np.sort(df.Yas)\n",
    "max_deger = np.max(sirali)\n",
    "min_deger = np.min(sirali)\n",
    "DG = max_deger - min_deger\n",
    "k = math.ceil(np.sqrt(303))\n",
    "a = 1\n",
    "c = (DG+a)/k\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_alt = np.zeros((k, 1), dtype=np.float)\n",
    "s_ust = np.zeros((k, 1), dtype=np.float)\n",
    "s_alt[0] = min_deger\n",
    "s_ust[0] = s_alt[1]-0.01\n",
    "for i in range(1, k):\n",
    "    s_alt[i] = (s_alt[i-1] + c)\n",
    "s_ust[:] = s_alt[:] + (c-0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 385,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Sınıf orta degeleri bulma\n",
    "s_ort = np.zeros((k, 1), dtype=np.float)\n",
    "for i in range(k):\n",
    "    s_ort[i] = (s_alt[i] + s_ust[i]) / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 386,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in df.Yas:\n",
    "    for j in range(k):\n",
    "        if((s_alt[j]<i) & (i<s_ust[j])):\n",
    "            z = s_ort[j]\n",
    "            df.loc[df.Yas == i, \"Yas\"] = int(z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "57    36\n",
       "54    35\n",
       "52    33\n",
       "60    33\n",
       "63    30\n",
       "43    27\n",
       "65    24\n",
       "41    21\n",
       "46    19\n",
       "49    12\n",
       "71     7\n",
       "68     7\n",
       "38     7\n",
       "35     6\n",
       "33     2\n",
       "76     2\n",
       "73     1\n",
       "29     1\n",
       "Name: Yas, dtype: int64"
      ]
     },
     "execution_count": 387,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Yas.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5.944444444444445\n"
     ]
    }
   ],
   "source": [
    "sirali = np.sort(df.KanBasinci)\n",
    "max_deger = np.max(sirali)\n",
    "min_deger = np.min(sirali)\n",
    "DG = max_deger - min_deger\n",
    "k = math.ceil(np.sqrt(303))\n",
    "a = 1\n",
    "c = (DG+a)/k\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 389,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_alt = np.zeros((k, 1), dtype=np.float)\n",
    "s_ust = np.zeros((k, 1), dtype=np.float)\n",
    "s_alt[0] = min_deger\n",
    "s_ust[0] = s_alt[1]-0.01\n",
    "for i in range(1, k):\n",
    "    s_alt[i] = (s_alt[i-1] + c)\n",
    "s_ust[:] = s_alt[:] + (c-0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Sınıf orta degeleri bulma\n",
    "s_ort = np.zeros((k, 1), dtype=np.float)\n",
    "for i in range(k):\n",
    "    s_ort[i] = (s_alt[i] + s_ust[i]) / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in df.KanBasinci:\n",
    "    for j in range(k):\n",
    "        if((s_alt[j]<i) & (i<s_ust[j])):\n",
    "            z = s_ort[j]\n",
    "            df.loc[df.KanBasinci == i, \"KanBasinci\"] = int(z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "132    55\n",
       "120    49\n",
       "138    48\n",
       "126    33\n",
       "108    26\n",
       "150    24\n",
       "114    14\n",
       "162    13\n",
       "144    12\n",
       "102    11\n",
       "180     5\n",
       "168     4\n",
       "156     3\n",
       "94      2\n",
       "174     2\n",
       "192     1\n",
       "198     1\n",
       "Name: KanBasinci, dtype: int64"
      ]
     },
     "execution_count": 392,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.KanBasinci.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 393,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "24.38888888888889\n"
     ]
    }
   ],
   "source": [
    "sirali = np.sort(df.Kolesterol)\n",
    "max_deger = np.max(sirali)\n",
    "min_deger = np.min(sirali)\n",
    "DG = max_deger - min_deger\n",
    "k = math.ceil(np.sqrt(303))\n",
    "a = 1\n",
    "c = (DG+a)/k\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_alt = np.zeros((k, 1), dtype=np.float)\n",
    "s_ust = np.zeros((k, 1), dtype=np.float)\n",
    "s_alt[0] = min_deger\n",
    "s_ust[0] = s_alt[1]-0.01\n",
    "for i in range(1, k):\n",
    "    s_alt[i] = (s_alt[i-1] + c)\n",
    "s_ust[:] = s_alt[:] + (c-0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Sınıf orta degeleri bulma\n",
    "s_ort = np.zeros((k, 1), dtype=np.float)\n",
    "for i in range(k):\n",
    "    s_ort[i] = (s_alt[i] + s_ust[i]) / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 396,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in df.Kolesterol:\n",
    "    for j in range(k):\n",
    "        if((s_alt[j]<i) & (i<s_ust[j])):\n",
    "            z = s_ort[j]\n",
    "            df.loc[df.Kolesterol == i, \"Kolesterol\"] = int(z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 397,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "235    63\n",
       "211    56\n",
       "260    53\n",
       "186    36\n",
       "284    33\n",
       "308    28\n",
       "333    12\n",
       "162     9\n",
       "138     4\n",
       "406     3\n",
       "357     3\n",
       "382     1\n",
       "126     1\n",
       "552     1\n",
       "Name: Kolesterol, dtype: int64"
      ]
     },
     "execution_count": 397,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Kolesterol.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 398,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.35\n"
     ]
    }
   ],
   "source": [
    "sirali = np.sort(df.ST)\n",
    "max_deger = np.max(sirali)\n",
    "min_deger = np.min(sirali)\n",
    "DG = max_deger - min_deger\n",
    "k = math.ceil(np.sqrt(303))\n",
    "a = 0.1\n",
    "c = (DG+a)/k\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 399,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_alt = np.zeros((k, 1), dtype=np.float)\n",
    "s_ust = np.zeros((k, 1), dtype=np.float)\n",
    "s_alt[0] = min_deger\n",
    "s_ust[0] = s_alt[1]-0.01\n",
    "for i in range(1, k):\n",
    "    s_alt[i] = (s_alt[i-1] + c)\n",
    "s_ust[:] = s_alt[:] + (c-0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 400,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Sınıf orta degeleri bulma\n",
    "s_ort = np.zeros((k, 1), dtype=np.float)\n",
    "for i in range(k):\n",
    "    s_ort[i] = (s_alt[i] + s_ust[i]) / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 401,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in df.ST:\n",
    "    for j in range(k):\n",
    "        if((s_alt[j]<i) & (i<s_ust[j])):\n",
    "            z = s_ort[j]\n",
    "            df.loc[df.ST == i, \"ST\"] = round(float(z), 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 402,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    99\n",
       "0.9    30\n",
       "0.5    28\n",
       "1.9    24\n",
       "0.2    22\n",
       "1.2    20\n",
       "1.6    16\n",
       "1.4    13\n",
       "2.3     9\n",
       "2.6     8\n",
       "3.0     7\n",
       "2.8     6\n",
       "3.7     5\n",
       "3.3     5\n",
       "4.0     3\n",
       "4.2     2\n",
       "2.1     1\n",
       "0.7     1\n",
       "6.1     1\n",
       "4.4     1\n",
       "5.8     1\n",
       "3.5     1\n",
       "Name: ST, dtype: int64"
      ]
     },
     "execution_count": 402,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ST.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 403,
   "metadata": {},
   "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>Yas</th>\n",
       "      <th>Cinsiyet</th>\n",
       "      <th>GogusAgrisi</th>\n",
       "      <th>KanBasinci</th>\n",
       "      <th>Kolesterol</th>\n",
       "      <th>KanSekeri</th>\n",
       "      <th>Elektrokardiyografik</th>\n",
       "      <th>KalpAtisHizi</th>\n",
       "      <th>KalpAgrisi</th>\n",
       "      <th>ST</th>\n",
       "      <th>Sonuc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>144</td>\n",
       "      <td>235</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>132</td>\n",
       "      <td>260</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>132</td>\n",
       "      <td>211</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>169</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>235</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>177</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>357</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>162</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Yas  Cinsiyet  GogusAgrisi  KanBasinci  Kolesterol  KanSekeri  \\\n",
       "0   63         1            3         144         235          1   \n",
       "1   35         1            2         132         260          0   \n",
       "2   41         0            1         132         211          0   \n",
       "3   54         1            1         120         235          0   \n",
       "4   57         0            0         120         357          0   \n",
       "\n",
       "   Elektrokardiyografik  KalpAtisHizi  KalpAgrisi   ST  Sonuc  \n",
       "0                     0           147           0  2.3      1  \n",
       "1                     1           184           0  3.5      1  \n",
       "2                     0           169           0  1.4      1  \n",
       "3                     1           177           0  0.9      1  \n",
       "4                     1           162           1  0.5      1  "
      ]
     },
     "execution_count": 403,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### AYKIRI DEĞERLER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 404,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25     71\n",
       "60     71\n",
       "129    73\n",
       "144    76\n",
       "145    71\n",
       "151    71\n",
       "225    71\n",
       "234    71\n",
       "238    76\n",
       "240    71\n",
       "Name: Yas, dtype: int64"
      ]
     },
     "execution_count": 404,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Yas[df.Yas>70]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 405,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25     1\n",
      "60     1\n",
      "129    1\n",
      "144    1\n",
      "145    1\n",
      "151    1\n",
      "225    0\n",
      "234    0\n",
      "238    0\n",
      "240    0\n",
      "Name: Sonuc, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df.Sonuc[df.Yas > 70])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 406,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop([238, 225, 234, 240], axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 407,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=df.Kolesterol);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 408,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df.Kolesterol.quantile(0.25)\n",
    "Q3 = df.Kolesterol.quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "altsinir = Q1 - 1.5 * IQR\n",
    "ustsinir = Q3 + 1.5 * IQR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 409,
   "metadata": {},
   "outputs": [],
   "source": [
    "aykiri = df.Kolesterol < altsinir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 410,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series([], Name: Kolesterol, dtype: int64)"
      ]
     },
     "execution_count": 410,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Kolesterol[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 411,
   "metadata": {},
   "outputs": [],
   "source": [
    "aykiri = df.Kolesterol > ustsinir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 412,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28     406\n",
       "85     552\n",
       "220    406\n",
       "246    406\n",
       "Name: Kolesterol, dtype: int64"
      ]
     },
     "execution_count": 412,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Kolesterol[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 413,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-413-51ee0f6b173f>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df.Kolesterol[aykiri] = int(df.Kolesterol.mean())\n"
     ]
    }
   ],
   "source": [
    "df.Kolesterol[aykiri] = int(df.Kolesterol.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 414,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28     245\n",
       "85     245\n",
       "220    245\n",
       "246    245\n",
       "Name: Kolesterol, dtype: int64"
      ]
     },
     "execution_count": 414,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Kolesterol[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 416,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=df.KalpAtisHizi);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 417,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df.KalpAtisHizi.quantile(0.25)\n",
    "Q3 = df.KalpAtisHizi.quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "altsinir = Q1 - 1.5 * IQR\n",
    "ustsinir = Q3 + 1.5 * IQR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 418,
   "metadata": {},
   "outputs": [],
   "source": [
    "aykiri = df.KalpAtisHizi > ustsinir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 419,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series([], Name: KalpAtisHizi, dtype: int64)"
      ]
     },
     "execution_count": 419,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.KalpAtisHizi[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 420,
   "metadata": {},
   "outputs": [],
   "source": [
    "aykiri = df.KalpAtisHizi < altsinir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 421,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "272    71\n",
       "Name: KalpAtisHizi, dtype: int64"
      ]
     },
     "execution_count": 421,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.KalpAtisHizi[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 422,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-422-3a44f737dded>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df.KalpAtisHizi[aykiri] = int(df.KalpAtisHizi.mean())\n"
     ]
    }
   ],
   "source": [
    "df.KalpAtisHizi[aykiri] = int(df.KalpAtisHizi.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 423,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "272    149\n",
       "Name: KalpAtisHizi, dtype: int64"
      ]
     },
     "execution_count": 423,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.KalpAtisHizi[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 425,
   "metadata": {},
   "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>Yas</th>\n",
       "      <th>Cinsiyet</th>\n",
       "      <th>GogusAgrisi</th>\n",
       "      <th>KanBasinci</th>\n",
       "      <th>Kolesterol</th>\n",
       "      <th>KanSekeri</th>\n",
       "      <th>Elektrokardiyografik</th>\n",
       "      <th>KalpAtisHizi</th>\n",
       "      <th>KalpAgrisi</th>\n",
       "      <th>ST</th>\n",
       "      <th>Sonuc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>144</td>\n",
       "      <td>235</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>132</td>\n",
       "      <td>260</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>132</td>\n",
       "      <td>211</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>169</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>235</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>177</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>357</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>162</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Yas  Cinsiyet  GogusAgrisi  KanBasinci  Kolesterol  KanSekeri  \\\n",
       "0   63         1            3         144         235          1   \n",
       "1   35         1            2         132         260          0   \n",
       "2   41         0            1         132         211          0   \n",
       "3   54         1            1         120         235          0   \n",
       "4   57         0            0         120         357          0   \n",
       "\n",
       "   Elektrokardiyografik  KalpAtisHizi  KalpAgrisi   ST  Sonuc  \n",
       "0                     0           147           0  2.3      1  \n",
       "1                     1           184           0  3.5      1  \n",
       "2                     0           169           0  1.4      1  \n",
       "3                     1           177           0  0.9      1  \n",
       "4                     1           162           1  0.5      1  "
      ]
     },
     "execution_count": 425,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=df.KanBasinci);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 427,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df.KanBasinci.quantile(0.25)\n",
    "Q3 = df.KanBasinci.quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "altsinir = Q1 - 1.5 * IQR\n",
    "ustsinir = Q3 + 1.5 * IQR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "metadata": {},
   "outputs": [],
   "source": [
    "aykiri = df.KanBasinci < altsinir # boş"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 429,
   "metadata": {},
   "outputs": [],
   "source": [
    "aykiri = df.KanBasinci > ustsinir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8      174\n",
       "101    180\n",
       "110    180\n",
       "152    168\n",
       "195    168\n",
       "203    180\n",
       "223    198\n",
       "228    168\n",
       "241    174\n",
       "248    192\n",
       "260    180\n",
       "266    180\n",
       "292    168\n",
       "Name: KanBasinci, dtype: int64"
      ]
     },
     "execution_count": 430,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.KanBasinci[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-431-a2c684581f98>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df.KanBasinci[aykiri] = int(df.KanBasinci.mean())\n"
     ]
    }
   ],
   "source": [
    "df.KanBasinci[aykiri] = int(df.KanBasinci.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8      131\n",
       "101    131\n",
       "110    131\n",
       "152    131\n",
       "195    131\n",
       "203    131\n",
       "223    131\n",
       "228    131\n",
       "241    131\n",
       "248    131\n",
       "260    131\n",
       "266    131\n",
       "292    131\n",
       "Name: KanBasinci, dtype: int64"
      ]
     },
     "execution_count": 432,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.KanBasinci[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=df.ST);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df.ST.quantile(0.25)\n",
    "Q3 = df.ST.quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "altsinir = Q1 - 1.5 * IQR\n",
    "ustsinir = Q3 + 1.5 * IQR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 435,
   "metadata": {},
   "outputs": [],
   "source": [
    "aykiri = df.ST < altsinir # boş"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series([], Name: ST, dtype: float64)"
      ]
     },
     "execution_count": 436,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ST[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 437,
   "metadata": {},
   "outputs": [],
   "source": [
    "aykiri = df.ST > ustsinir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "101    4.2\n",
       "204    6.1\n",
       "221    5.8\n",
       "250    4.2\n",
       "291    4.4\n",
       "Name: ST, dtype: float64"
      ]
     },
     "execution_count": 438,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ST[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-439-7882bb8a0c87>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df.ST[aykiri] = round(float(df.ST.mean()), 1)\n"
     ]
    }
   ],
   "source": [
    "df.ST[aykiri] = round(float(df.ST.mean()), 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 440,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "101    1.0\n",
       "204    1.0\n",
       "221    1.0\n",
       "250    1.0\n",
       "291    1.0\n",
       "Name: ST, dtype: float64"
      ]
     },
     "execution_count": 440,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ST[aykiri]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 441,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=df.ST);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 442,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 443,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#sns.boxplot(x=df.GogusAgrisi);\n",
    "sns.boxplot(x=df.Elektrokardiyografik);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 444,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x=\"Yas\", y=\"KalpAtisHizi\", color = \"red\" ,data = df)\n",
    "plt.title('Yas - KalpAtisHizi')\n",
    "plt.ylabel('KalpAtisHizi')\n",
    "plt.xlabel('Yas')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Yas', ylabel='GogusAgrisi'>"
      ]
     },
     "execution_count": 445,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(x=\"Yas\", y=\"GogusAgrisi\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 446,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(x=\"Yas\", y=\"GogusAgrisi\", hue=\"Cinsiyet\", data=df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 447,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"GogusAgrisi\", y=\"Kolesterol\", kind=\"violin\", data=df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 448,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"GogusAgrisi\", y=\"KanBasinci\", kind=\"violin\", data=df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 449,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x=\"KalpAtisHizi\", y=\"ST\", data=df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 450,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(x=\"ST\", y=\"GogusAgrisi\",  data=df, color=\"red\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 451,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 796.125x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(\n",
    "    data=df,\n",
    "    x=\"Yas\", y=\"KalpAtisHizi\", col=\"Cinsiyet\", hue=\"Cinsiyet\",\n",
    "    kind=\"line\",linewidth=4, zorder=5,\n",
    "  \n",
    "); # 0 : Kadın, 1 : Erkek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 452,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 796.125x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(\n",
    "    data=df,\n",
    "    x=\"Yas\", y=\"Sonuc\", col=\"Cinsiyet\", hue=\"Cinsiyet\",\n",
    "    kind=\"line\",linewidth=4, zorder=5,\n",
    "  \n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 453,
   "metadata": {},
   "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>Yas</th>\n",
       "      <th>Cinsiyet</th>\n",
       "      <th>GogusAgrisi</th>\n",
       "      <th>KanBasinci</th>\n",
       "      <th>Kolesterol</th>\n",
       "      <th>KanSekeri</th>\n",
       "      <th>Elektrokardiyografik</th>\n",
       "      <th>KalpAtisHizi</th>\n",
       "      <th>KalpAgrisi</th>\n",
       "      <th>ST</th>\n",
       "      <th>Sonuc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>144</td>\n",
       "      <td>235</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>132</td>\n",
       "      <td>260</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>132</td>\n",
       "      <td>211</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>169</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>235</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>177</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>357</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>162</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Yas  Cinsiyet  GogusAgrisi  KanBasinci  Kolesterol  KanSekeri  \\\n",
       "0   63         1            3         144         235          1   \n",
       "1   35         1            2         132         260          0   \n",
       "2   41         0            1         132         211          0   \n",
       "3   54         1            1         120         235          0   \n",
       "4   57         0            0         120         357          0   \n",
       "\n",
       "   Elektrokardiyografik  KalpAtisHizi  KalpAgrisi   ST  Sonuc  \n",
       "0                     0           147           0  2.3      1  \n",
       "1                     1           184           0  3.5      1  \n",
       "2                     0           169           0  1.4      1  \n",
       "3                     1           177           0  0.9      1  \n",
       "4                     1           162           1  0.5      1  "
      ]
     },
     "execution_count": 453,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.pointplot(x=\"KalpAtisHizi\", y=\"GogusAgrisi\", data=df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 455,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 8))\n",
    "sns.pointplot(x=\"Yas\", y=\"Sonuc\", data=df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 456,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Qx3QN9kGbuWaX5qzb5bcgADGLQAYg7k1ZsV2b9uRJks7o20rpqbXTKqk6rhzeKXL7yUn0twRQPgIZgLgXi5crS53Uq6XaNs6QJL05Z4O25+R7rghALCKQAYhruQVFemdeMGG+beMMDenU1HNFB0pOMo0Nt8AoKCrR81+t9VwRgFhEIAMQ196fv1m5BcWSpDED29R6q6TquHhwe9VLCU63T09ZraJitsAAcCACGYC49urMry9X+twMtjJN6qdp9IBgX7SNu/P0wYLNnisCEGuiFsjMrL2ZTTCzBWY238xuLnPfjWa2KDx+V5njvzCzZWa22MxOi1ZtAOqGLXvy9PnSrZKk/u0aqWuLBp4rqtgVZSf3R2ELDADxLZq9LIsk3eqcm2FmDSVNN7MPJLWUNFpSf+dcvpm1kCQz6y3pEklHSmoj6UMz6+6cK45ijQDi2BuzNijslKTzBvppJF5dfdo20uCOTTRt9U5NWbFDizbtUc9WWb7LAhAjojZC5pzb6JybEd7eK2mhpLaSrpf0V+dcfnjflvApoyU975zLd86tlLRM0pBo1Qcg/r0StkpKSTKd47lVUnVcOaJT5PZTk9kCA8DXamUOmZl1kjRQ0lRJ3SUda2ZTzewTMzs6fFhbSWWXH60LjwHAtyzcuEeLNu2VJJ3Qo7maNfDbKqk6Tu/TSi3Clk6vzViv3bmFnisCag+tvioX9UBmZg0kvSLpFufcHgWXSZtKGibpZ5JeNLNqL4sys2vMbJqZTdu6dWtUagYQ+16Lg8n835SanKTLhgZbYOwvLNZL09kCA4mDVl+Vi2ogM7NUBWHsGefcq+HhdZJedYEvJZVIypa0XlL7Mk9vFx47gHPuEefcYOfc4ObNm0ezfAA1pKZ/Mz6gVVJ6ik7q1aJGXrc2XDq0vVKTg99Bn5q8WiWlk+AAJLRorrI0SY9JWuicu7vMXa9LGhU+prukNEnbJI2XdImZ1TOzzpK6SfoyWvUBqD01/ZvxF8u2acveYMf7s/u1jqlWSVVp0TBdZ/ZtLUlasyNXE5dsqeIZABJBNEfIjpE0VtKJZjYr/DhT0uOSjjCzeZKel3RlOFo2X9KLkhZIelfSDaywBFCespcrY61VUnWUndxPf0sAUhS3vXDOfS6porlhl1fwnD9J+lO0agIQ//blF+ndeZskSe2bZmhwxyaeKzp4A9s3Vt+2jTR3/W59smSrVmzN0RHNY3cPNQDRx079AOLKu/M2aX9hMHh+3oC2Oog1QTHDzNgCA8ABCGQA4sqrM9dFbp8Xh5crS53dr7Wa1k+TJL0yfZ1y8os8VwTAJwIZgLixcfd+TVq+XZI0sENjdc6u77miQ5eemqxLjg4Wlu/NL9JrM9ZV8QwAdRmBDEDceGPWBrlwl4jzY7xVUnVcPqyjksIrrk9OXi3n2AIDSFQEMgBxwTmnV8NRpNRk09n9Yr9VUlXaNM7Qqb1bSZKWbcmJjP4BSDwEMgBxYf6GPVqyOUeSNKpHCzUJ51/Fu7KT+5+YtMpbHQD8IpABiAsH7j0W/5crSw07oql6tGwoSfpo4Wat3ZHruSIAPhDIAMS8ouISvTFrgySpUUaqRvWMn1ZJVTEzXTEi6G9Z4qSnp9bNLTBoLA1UjkAGIOZ9tmybtuV83SqpXkr8tEqqjvMGtlXD9GCf7he+Wqu8wrrXpITG0kDlCGQAYt5rM+rm5cpSmWkpumhwsAXGrtxCjQ9HAwEkDgIZgJi2N69Q780PWiV1bJapQR3ir1VSdYwd1lGlTQeemLSKLTCABEMgAxDT3pm3SflFJZKCS3vx2CqpOjpl19cJ3ZtLkhZs3KPpq3d6rghIPBMWb9GVj3+pNduDxTU79xVoV25Brbw3gQxATHu1zA725w+M31ZJ1cEWGIA/D05Ypqv++5U+WbJVxeEI9a79hRrz4Bfasjcv6u9PIAMQs9bv2q8pK3ZIkgZ3bKIOzTI9VxRdx3VrHmkH9e68Tdq8J/r/CQCQlm3Zq7+9t7jc+1Ztz9Vf31kU9RoIZABi1utl9h47rw5O5v+mpCTT2GHBFhhFJU7PTF3juSIgMbw0vfJesm/N2ajcgqKo1kAgAxCTyrZKSktO0tl9479VUnVcOLidMtOCbT2enbpGBeH8OQDRs2l35aPRBUUl2rEvunPJCGQAYtLc9bu1fOs+SdJJvVqoUWaq54pqR1Z6amRrj205+Xpn3kbPFQF1X9vGGZXen56apGb160W1BgIZgJj0apm9x84bWPcvV5Z15fBOkdtM7gei7zvhPoAVGTOgrTLSorshNYEMQMwpLC7Rm7ODzVGbZKbqhB51p1VSdXRr2VAjujSTJM1cs0tz1u3yWxBQx81aW/E2M91bNtBtp/eMeg0EMgAx59MlW7U9nK9xTv82SktJvFNV2S0wnpxUN/tbArFgwYY9+sWrcyNfH9WxsVKSgv0Om2Sm6pXrR6hp/bSo15F4ZzkAMS+RL1eWOrlXy8i8ljfnbND2sJcngJqzK7dA1z49TXmFweKZm07qpleuP0btmwZb7DTOTFPD9NqZv0ogAxBTdu8v1AcLN0uSjsiurwHtG/styJPkJNPl4RYYBUUlev6rtZ4rAuqWkhKnW16YpbU7gob3J/RorltO6uatHgIZgJjyztyNka0e6nKrpOq45Oj2qhdern1mymoVFbMFBlBT/vnRUk1cvFWS1L5phv558QAlJfk73xDIAMSUspcrxyTo5cpSTeqn6dz+wf5rG3bn6cNw5BDA4flo4Wbd99FSScGWFg9fPliNM6M/T6wyBDIAMWPtjlx9uSpolTSkc9PIPI5ERn9LoGat2rZPt7wwK/L1X87vq95tsvwVFCKQAYgZZVslnZ/go2Ol+rRtpMEdm0iSpqzYocWb9nquCIhfuQVFunbcdO3NC9ogXTm8o84b2M5zVQECGYCY4JzTq2EgS0tJ0pn9WnuuKHZcUXYLjMmrvNUBxDPnnH7+ylwt3hz8UjO4YxP98qzenqv6GoEMQEyYtXaXVm4LWiWd0rulsmppqXk8OP3IVmrRMGjb8tqM9dqdW+i5IiD+/PeLVRofbjjdvGE9/euyQTG1x2HsVAIgob3G5coKpaUk6btDO0iS9hcW66XpbIEBHIypK7brT28vlCSlJJn+ddkgtchK91zVgQhkALwrKCqJ/ObarH6ajuve3HNFsee7QzsoNTlYkj9uymqVlDjPFQHxYfOePN3w7EwVh/9mfnlWLx3dqannqr6NQAbAu4mLt2hXeBnunP5tlJrMqembWjRM1xl9gnl1q7fn6pMlWz1XhFgw9rGpGvX3iRr72FTfpcSkgqISXf/0dG0LO12MGdBG3yszJzOWcNYD4F3ZvcfOH8TlyoqwBQa+ad3O/Vq5bZ/W7dzvu5SY9Ie3FmjGml2SpJ6tGuov5/eL2c2mCWQAvNqdW6iPF22RJHVt0UB92zbyXFHsGtShceT788mSrSpk536gQq9MX6dxU1ZLkrLSU/Tw2KOUkZbsuaqKEcgAePXW3A0qKKZVUnWYma4Y3jHydelqS+eYTwaUNW/9bt3x2lxJkpl07yUD1bFZfc9VVY5ABsArWiUdnHP6t1GDeimSpL35weaW63bu1zNTVxPMAEm7cgt03dPTlR/2xL35pG4a1bOF56qqRiAD4M3q7fs0ffVOSdLwI5qpbeMMzxXFvskrtmtfGMRKFZU4/fK1ebr7gyWeqgJiQ3GJ003Pz4rMqTuxZwvddGI3z1VVD4EMgDdl9x47j8n8VSopcfr9mwtU0TjYgxOWacMuJncjcf3zwyX6NFyB3KFppu65aICSkuJjGgSBDIAXzrlIIEtPTdIZfVp5rij2zd+wJ9LNoDwlTnp77sZarAiIHR8s2Kz7P14mKTinPDz2KDXKjJ+OHwQyAF7MWLNTq7fnSpJO7d1KDWmVVKW9eVW3TCptmgwkkhVbc/STF2ZFvr7zgn7q1TrLX0GHgEAGwItXZnC58mB1bdlAyVVcfmndqF4tVQPEhn35Rbru6emRRS7fG9FJowfE3zmFQAag1uUXFet/c4JLa9kN6unYrtmeK/pauyYZ6pxdX+2axN4CgxYN03V2v9aVPubv7y/R1BXba6kiwC/nnG5/ZY6WbM6RJA3p1FS/PKuX56oOTYrvAgAkngmLtmj3/uDy2+gBbZQSQ62Sxl091HcJlfr96D5auyM3svt4qeQkU3GJ07acAn33P1N1x5m99P1jOrGvG+q0xz5fqbfCX+5aNKynBy4bGLet1+KzagBx7YDLlew9dlAaZaTqxWuH69+XHxXZj6xZ/TRN+vkojR7QRlKw9P8Pby3QTc/PUm4Bc8pQN01evl1/eWeRJCklyfTQ5YPUomG656oOHYEMQK3aua9AExcHrZJ6tGyoI9vE18TbWJCSnKTT+7RS84bBfLGsjFS1zMrQPy8eoP93Tm+lhPPM3py9Qec9OKnSlZlAPNq4e79ufG6GikuCTWB+fXZvHdWxqeeqDg+BDECtemvOBhUWByfR8wbRKqkmmZmuOqaznrtmWCSsLd68V+fe/7k+WLDZc3VAzcgvKtb/PTND23IKJEnnD2x7QEuxeEUgA1CrSi9XmilyiQ016+hOTfW/G0fq6E5NJAUtln741DT9/b3FkREFIF79/s0FmhnOoezVOkt/Oq9vnfjFjkAGoNYUFpdo1tpdkqRjumSrdaPYW8lYV7TIStezPxym743oFDn2wIRl+t5/v9TOfQX+CgMOw0vT1uqZqWskBfMpH778KGWkJXuuqmYQyADUmpwym5YymT/6UpOT9Ntzj9Q/Lx6g9NTgdP/Z0m06+/7PNW/9bs/VAQdn3vrd+uXr8yQFI+z/vGSAOjTL9FxVzSGQAag1OeHGjRmpyTqdVkm1ZszAtnrt/45Rx/A/r/W79uv8hybpxWlrPVcGVM/OfQW6dtx0FRSVSJJ+fHJ3jerRwnNVNYtABqDWFIXzl07v00r167ENYm3q1TpL4380Uif1DP4TKygq0W0vz9Edr81VflGx5+qAihWXON30/Eyt37VfknRyrxb60aiunquqeQQy1Iqxj03VqL9P1NjHpvouBbVs9tpd2r4v/4BjXK70o1FGqh69YrB+ckp3lc6BfnbqGl308BRtCP+zA2LN3R8s1mdLt0mSOjXL1D8uGqCkKlqIxSMCGWrFup37tXLbPq3byUk/URSXOP3spdka/eAX2rP/67ljJim5DqyIildJSaabTuqmx793tBplBA3dZ6/dpXPu/1yTlm/zXB1woPfmb9KDE5ZLCqY6/HvsUZG/t3UNgQxAVDzy6Qq9NH3dt447Sdc+PV07WOnn1ageLfTmj0aqd+tgY97t+wp0+X+m6uFPlss5tsaAf8u35ujWF2dHvr7zwn7q2arubiRNIANQ44pLnJ6YtLLC+3Pyi/TydCaU+9ahWaZeuX6Ezh8UXEIucdJf3lmkG56dEVmAAfiwL79I142bHvl7+P1jOuvc/nV730ICGRCnYnle3racfG3ek1/pY+asY9uFWJCRlqx/fKe//jCmj1KTg0vJb8/dpDEPfqFlW3I8V4dE5JzTbS/P0dLw79+Qzk31izN7eq4q+ghkQJyK5Xl51dmosQGrLGOGmWnssI56/prhapkVtFxatiVHYx78Qu/O2+i5OiSaRz9bof/NDf7etcyqpwe/O0ipyXU/rtT9PyGAWpeVnqqRXZtV+pgz+7aupWpQXUd1bKK3bjxWQzsHTZpz8ot03dMz9Jd3FqqouMRzdUgEk5Zv01/fWSRJSk02/euyoyJ9Wes6AhmAqBjUoUmF953Ys4VGds2uxWpQXc0b1tPTPxiqH4zsHDn28CcrdMXjX2p7TuWXoYHDsWHXft347EyVtlv9zdm9dVTHis8jdQ2BDECNW7YlR49+9u1J/WbSNccdoX9dNqhO7iNUV6QmJ+lXZ/fW/ZcOVGZ4+XnS8u065/7PI71IgZqUX1Ss65+Zoe3h6usLBrXT5cM6eq6qdhHIANSovMJi3fjcTO0vDHZ/v/mkbmrfNGgi3qFppu44s5fSU+tGM+C67pz+bfT6Dceoc3Z9SdKG3Xm66N+T9dyXazxXhrrmt+MXaHYY9o9sk6U/nddHlmD7FVYayMysaWUftVUkgPjx13cWaeHGPZKkIZ2a6sYTuyolKTjVJCXYCbYu6N6yod740TE6tXdLSVJBcYl+8epc3f7yHOUV0nIJh+/Fr9ZGQn6jjFT9+/KjEvKXtqqWOU1XsI9jeWdRJ+mIGq8IQNz6cMFmPTFplaTgxHrPJQOUkgCro+q6rPTgP8mHPlmuf7y/WCVOemHaWi3YuEcPXT5I7Zpk+i4RcWrOul361RvzJAVTGu67dKDaN03Mv0+Vnimdc52dc0eEn7/5QRgDELFpd55+9nKZXbUv6Ku2jTM8VoSalJRkumFUVz35/SFqkhm0rpm7frfOuf9zfbZ0q+fqEI927CvQ9U/PUEFRsIL31lO66/juzT1X5U+1f3U1s3PN7O/hx9nRLApAfCkucfrxC7O0M7dQknTZ0A46vQ/bWtRFx3ZrrjdvHKm+bRtJknbmFurKx7/UgxOW0XIJ1VZc4nTTczO1Pmxqf3Kvlvq/E7p6rsqvagUyM/urpJslLQg/bjazP0ezMADx46GJyzR5xXZJUveWDfTrs3t7rgjR1K5Jpl66brguHtxeUtBy6W/vLda146ZrT16h5+oQD/7+/mJ9vixoZt85u77uvrh/wq+8ru4I2ZmSTnHOPe6ce1zS6ZIYJQOg6at36J4Pl0qS6qUk6YHvDkrICbmJJj01WXde2E9/Ob+v0sJ5gu8v2KwxD3yhJZv3eq4OsWbj7v3aF/alzMkv0kMTl0uSMtOS9e/Lj1JWeqrP8mLCwcy2bVzmdqMargNAHNq9v1A3PTdLxeFOjr85p7e6t2zouSrUpkuHdNCL1w1Xm0bpkqQV2/ZpzINf6K05GzxXhliwN69QNz03U8f89WNt2RtsLLx179cbDN91YT/1aMU5Q6p+IPuzpJlm9oSZPalg9eWfolcWgFjnnNMdr86NzAE5o08rfXdIB89VwYcB7RvrzRtHakSXoF1WbkGxfvTsTP3xrQUqKi7Rmu252rM/uJRZOoEbdZ9zTtc9PV3jZ2+I7L5f1vHdm+vsfm1qv7AYVWUgM7MkSSWShkl6VdIrkoY7516Icm0AYtgLX62NNABu0yhdfz2/X8Jt5IivNWtQT099f4iuPf7rBfj/+Xylhv/lIx33twmRHdjX79qva8dNi1y+Qt01ZcUOfbFse4X3L9+6NzK6jmoEMudciaTbnHMbnXPjw49NtVAbgBi1dPNe/fbN+ZKkJJPuvXSgGmUyByTRpSQn6Rdn9NJDlw1S/bDl0tacgm897r35m3Xri7O/dRx1y8TFWyq9f93OPC3fmlNL1cS+6l6y/NDMfmpm7dmpH0hspa2R8gqDS083n9RdR3fidICvndG3tf571dGVPubd+Zu0bAuT/+uywuKqL08XFTNCVqqqnfpLXRx+vqHMMXbqBxLQn99eqEWbgv9Ih3Ruqh+dmNh7B6F8O/Z9e2Tsmy56eIp6t85SuyYZ4Udm5HOLhvUSfhuEeLZ2R66mrNhR6WOyG6Spa4sGtVRR7KtWIHPOdY52IQBi3/vzN+mpyaslSY0zU3XvJQOUzH+aKEd15hPu2FcQ2Yvqm9KSk9SmcbraNclU+6Zlw1pwu3mD6AW2Eja4PWQlJU7jpqzWne8uUm5B5b1Of3DsEUpLobVaqWoFMjPLlPQTSR2cc9eYWTdJPZxzb0W1OgAxY+Pu/brtlTmRr++6oJ9aN6I1Eso3rHMzpacmRS5tl6d1o3Rt2Ztf7sTuguISrdqeq1Xbc8t9blpyktpGAlrNBLYPF2zWAxOWaXX4nht27dfnS7dpZLfsg3qdRLVia45uf2WOvlq1M3KsS/P6SjbTki0HzhW77vguuvY4LrKVVd1Llv9VsNXFiPDr9ZJekkQgAxJAcYnTzc/P0q6wNdIVwzvq1CNbea4KsaxRZqquHtlZD05YXu79Fw9urzsv7Kei4hJt3puvdTtytW7n/vAjvL0rVxt25VUY2FZu26eV2/aV+/oVB7ZMtW+SoexvBLYXvlqj21+Ze8Br5BeV6IrHp+r+SwfprH60AqtIUXGJ/vP5St39wZLItiYpYe/TG0Z1VWqyadrqnbp23HTt2Feg9k0z9PMzenquOvZUN5B1cc5dbGaXSpJzLtdY3w4kjAc+XqYvVwbzQXq2aqg7zuzluSLEg1tP6SGT6T+frzhgpOyK4R31q7OC9lopyUlq2zhDbRtnaGg5r/HNwLa2NKyFnzfuPsTAlpKkdo0z1LZJhlplpeuNWeVvZFvipP83fr5O6d2Sy2vlWLhxj257eY7mrt8dOda3bSPddWE/9WqdFTl2dKemapSRqh37CpSSxPexPNUNZAVmlqFgIr/MrIuk/MqfAqAu+GrVDt370RJJUnpqku6/dCCtkVAtSUmmn57WQz889gidcs8n2rI3Xx2aZur3o/tU+zWqE9g27cn79uhaVYGtqEQrtu3TigoCW1nbcvI1ecV2Hd+9ebXrrusKikr04IRlenDCMhWF39+0lCT95JTu+sHIzkpJJnQdrOoGst9KeldSezN7RtIxkq6KVlEAYsPu3ELd/NzMyC7b/++cI9WN1kg4SI0yU1W/Xoq0N7/GF4GkJCeFlyMzy72/osC2dkdpYNtf7i7y37Rp9/4arTuezV67S7e9PEeLy/QsPbpTE915QT8d0ZxVk4equqss3zez6Qp26zdJNzvnyl8aA6BOcM7p9lfmaMPuPEnSWX1b65Kj23uuCjg4VQW2wuISvTNvo256blalr/OHtxZqw648XXVMJzXOTItCpbEvr7BYd3+wRP/5bEUkxGamJev203tq7LCObFNymKo1pmhmHznntjvn/uece8s5t83MPop2cQD8efbLNXp3ftCUo23jDP35/L60RkKdk5qcpHP6tVGPKkZ+c/KLdO9HSzXyzgm6891F2paTWLN2pq7YrtP/+ake+fTrMHZst2y9d8txunJEJ8JYDag0kJlZergjf7aZNSmzS38nSW1rpUIAtW7xpr36/ZsLJEnJSab7Lh2gRhm0RkLdZGZ68LJBapWV/q372jXJ0HeHdoi0gsrJL9JDE5dr5J0f6/dvLtCmcAS5rsrJL9KvX5+nix+ZEtmCJCs9RXdd2E9PfX+I2jctf+QRB6+qEbJrFWx30TP8XPrxhqQHKnti2GZpgpktMLP5ZnbzN+6/1cycmWWHX5uZ3Wdmy8xsjpkNOtQ/FIBDF7RGmqH8cPn6j0/upqM60hoJdVvXFg30/k+O02/P6a3MMHw1q5+m9398nP58Xl99fvuJuumkbspKD2b65BWW6PEvVuq4uybol6/N1dod5e+XFs8+XbJVp93zqcZNWR05dkrvlvrgJ8frosHtGTGvYZXOIXPO3SvpXjO70Tl3/0G+dpGkW51zM8ysoaTpZvaBc26BmbWXdKqkNWUef4akbuHHUEkPhZ8B1KI/vLVASzYHmzgOP6KZrj+B1khIDFnpqfreMZ315OTVWrltn7IyUpWZFvw32aR+WrCC8NjOGjd5tR77fKV27CtQQXGJnpm6Rs9/tVbnDWyr/zuhS9xPbN+dW6g//G+BXp6+LnKsaf00/e7cI3V2v9YEsSip7rrUTWGokpn9ysxerWoEyzm30Tk3I7y9V9JCfX2Z8x5JtyncRiM0WtJTLjBFUmMzYyc+1Jo563ZF5oXs2Feg5VtzqnhG3fPuvI16Zmrwe1KTzFTdczGtkYCystJTdcOorvr89lH61Vm91KJhPUnB5skvT1+nk+7+RDc+N1OLNu3xXOmheW/+Jp18zycHhLFz+7fRBz8+Tuf0b0MYi6LqBrJfO+f2mtlISSdLekzBCFa1hHPOBkqaamajJa13zs3+xsPaSlpb5ut1Yp4aaoFzTn9+e6HOfeAL7c0rkiTt3l+oU+7+RE9NXuW3uFq0ftd+3fby162R/v6d/mrV6NtzagBImWkp+sGxR+jT20bpD2P6qG3joI2Yc9Kbszfo9H9+pmuemqY563b5LbSatuXk64ZnZ+jacdO1dW/wi2nLrHr6zxWDdd+lA9WsQT3PFdZ91d2HrLRD6FmSHnHO/c/M/lidJ5pZA0mvSLpFwWXMOxRcrjwkZnaNpGskqUOHDof6MkDE+Nkb9MinK751vMRJv3ljvvq2baSBHZp4qKz2FBWX6JbnZ2pPGEi/N6KTTurV0nNVQOxLT03W2GEddcnR7fXazPX614Rlkcnv7y/YrPcXbNbx3ZvrxhO7anCn2JuL6ZzT+Nkb9Nvx87UzbI0mSZcc3V6/OLMXi3lqUXUD2Xoze1jSKZLuNLN6qsbompmlKghjzzjnXjWzvpI6S5odDnu2kzTDzIYo6I9ZdpOjduGxAzjnHpH0iCQNHjy4Gtv5AZV7ctKqSu8fN3l1nQ9k93+8LNIQuFfrLPrMAQcpNTlJFw1urwsGtdNbczbowQnLInMxP1myVZ8s2aphRzTVjSd204guzWLi0t+m3Xn65Wtz9dGiLZFj7Zpk6K/n96OhugfVDWQXSTpd0t+dc7vCuV0/q+wJYa/LxyQtdM7dLUnOubmSWpR5zCpJg8N9zcZL+pGZPa9gMv9u59zGg/0DAQdr0aa9ld6/sIr7492UFdt1/8dLJUkZqcm0RgIOQ3KSafSAtjqnXxu9v2CzHpiwVPPWB/PJpqzYoSkrpmpgh8a68cSuGtWjhZdg5pzTC1+t1Z/+t1B784NRcTPpyuGd9LPTegRdFVDrqrtTf66ZbZE0UtJSBZcel1bxtGMkjZU018xmhcfucM69XcHj35Z0pqRlknJFaybUkkYZqcotKK7w/v0FRSoucXVycvvOfQX68QuzIhs9/u7cI9W1RXyvEANiQVKS6fQ+rXTakS01cclW3f/RUs1Ys0uSNHPNLn3/iWnq3TpLN57YVacd2arWNlZduyNXP391jr5Ytj1y7Ijm9XXXBf1i8pJqIqlWIDOz/ydpsKQekv4rKVXS0wpCV7mcc58raLNUIedcpzK3naQbqlMPUFOcc2rXJEMbK9nccdX2XJ33ry/0xzF91K9d49orLsqcc7rtlTmRP/s5/dvoO4Pbea4KqFvMTKN6tNAJ3Ztr8orteuDjZZq0PAhDCzbu0fXPzFC3Fg10w6iuOrtf66g15S4ucXpy0ir97b3F2l8Y/AKanGS65rgjdPNJ3RgVjwHVHZc8T8EqydJtLDaUboMBxCvnnP7yzqLI3KnKzFm3W6Mf/ELfHdJBt53WU40y43+i69NTVuuDBZslSe2bZuhP5/WJiXktQF1kZhrRJVsjumRr+uodeuDjZZqweKskaemWHN3ywizd8+ES/d8JXXTewHZKS6m5YLZsS45uf2WOpq/++lzXs1VD/e3C/urbrlGNvQ8OT3V/4gXhCJaTJDOrH72SgOgrLnH6+StzI6srk810dKcmkSFdM+n7x3TW6zccoyGdg2F856Rnpq7RqH9M1IvT1qqkJH7XlCzcuEd/+N9CSVJKkum+SwYqKz3+QyYQD47q2FT/vWqI3rpxpE4/slXk+Ortubr9lbk64W8T9NTkVcorrHgqRXUUFZfoXxOX6cz7PouEsdRk009O6a7xPxpJGIsx1Q1kL4arLBub2Q8lfSjp0eiVhco45zR77S7lhJMxg6yM6sovKtaPnp2hF6YF296lpSTp32OP0kvXjVCHZkFfto5NM/Wbc3prQPvGeuGaYbrn4v7KDvfh2bGvQLe9PEcXPTxZCzfG3+aP+wuKdeNzM1UQtkb6yand6/wqUiAW9WnbSP8ee5Te//FxGj2gjUqnkW3YnaffvDFfx941QY9+ukL7wnP9wViwYY/G/OsL3fXu4si/9f7tG+utG4/VTSd1q9ERONSM6k7q/7uZnSJpj4J5ZL9xzn0Q1cpQrqWb9+rHL86KrNqRpHU79+uLZdt0TFeWKVclt6BI146brs+WbpMk1U9L1qNXDtaILsH3Lim8ZFf20p2Z6byB7XRiz5a654MlemryKpU4adrqnTr7/s915fBO+vEp3dQwTkaYfv/WfC3bEizHP6ZrM113XBfPFeFQtWuSccBnxKfuLRvq3ksG6paTu+uhicv06oz1Kipx2ro3X396e6H+NXGZrh7ZWVeM6HTASPbu/YXaHy5IKv3FPL+oWA98vEwPTVyuonAUv15Kkn56ag99f2TnOrk4qa6o9trWMIARwjzalpOvSx+dom05BQccLypxuuqJr/Tq9SPUpy1D0BXZnVuoq574MrLSqUlmqp78/pBqT9RvlJGq3557pC48qp1+/cY8zVyzS8UlTo9/sVJvzdmgX57VS+fGeGuR/83ZqOe+DEYGm9ZP0z0XDai11V2oeeOupt1vXdI5u77uurC/bjqpmx7+ZIVemLZWBUUl2plbqL+/v0QPf7pC3xvRSZcN7ahHP1uhZ6auVl5hMPq1Zkeu/vz2Qk1YtEVLt3zd9m1o56a684J+6pTNTKNYV+mYpZntNbM95XzsNbP4u1YT556ZsuZbYaxUQVGJHvpkeS1XFD+27MnTxY9MjoSxVlnpeum64Ye0arJP20Z65boRuvOCvmoSTu7fsjdfNz8/S999dKqWbYnNfcvW7QyWu5f6x3f6q0UWrZGAWNOuSab+MKaPPrttlH4wsrMywhWQe/OKdP/Hy3TMnR/rsc9XRsKYFHQWeeTTFZEwVj8tWX8c00fP/XAYYSxOVBrInHMNnXNZ5Xw0dM5l1VaRCHyyZEul938artjBgdbuyNV3Hp4c2QC2U7NMvXTdcHVtcegLhZOSTBcf3UEf33qCLh3SXqWDYpNXbNcZ936mv76zSLkFBz/vI1qKikt08/OzIr06rx7ZWaN6tqjiWQB8apmVrl+d3Vuf3z5KN4zqogbhhq3FVSwoOrZbtt7/yfG6fFhHRsDjSLVn9ZlZfzP7UfjRL5pFoXxVLeorLimp/AEJaMnmvbrgoUlaHfaW69mqoV68brjaN82skddvUj9Nfzm/X3i5OPgdpbDY6d+fLNfJ//hE787bGBOLLu79aGlkldWRbbJ02+k9PFcEoLqaNainn53WU1/cfqKOrUZLox+N6hppdo74Ua1AZmY3S3pGQdujFpKeMbMbo1kYvm1El2aV3p+cnBSZrA1p1tpduujhydqyN1+SdFTHJnrh2uFq0bDmL9MN7NBEb9wwUr8ffaQapge/xW7Ynafrnp6hq574Squ27avx96yuScu36YEJyyRJmWlBa6R6KWwCCcSbRpmpGtq56t30i+J4S55EVt0RsqslDXXO/cY59xtJwyT9MHploTxjh3dUVnrF6zD25hXp7Ps/07NT18TEqIxPk5Zt02WPTtGu3EJJ0vHdm2vc1UPUKCN6KyGTk0xXDO+kj289QecPahs5PnHxVp36z0919wdLDntfoYO1I2yNVPrX4fej++iI5rRGAuJVVe2N6qUkqU8bFnfFo+oGMpNU9n+SYlXRFgk1r3WjDN136cBvHTcLepFJUl5hie54ba6ue3q6du4rfwFAXffe/E363n+/0r5wOfhZfVvr0SsGKzOtdhrmNm9YT3dfNEAvXjtcPVoG89QKikp030dLdeo9n2rCosrnAtYU55xue3m2Nu8JRghHD2ijC8oERQDxZ2jnphrQvnGF9186pEOd6CSSiKobyP4raaqZ/dbMfitpiqTHolYVKlT20ldmWnDZqUPTTL1/y3G65eRukY0F35u/Waff+6m+WLbNR5nevDx9na5/eroKioP5dJcOaa/7Lh3oZRPEIZ2b6q2bRupXZ/VS/fBntWZHrq564itd89Q0rduZG9X3f3LSKn24MAh/HZpm6o9jaI0ExDsz0yNXHFVuKBszoI3uOLNX7ReFGlHVthftJck5d7ekqyTtCD+ukrQs6tXhW16ftUGSlGRSswZp4W1TSnKSbjm5u166bnhkk8jNe/J1+WNT9Ze3F0Z2aq7LHv98pX760uzI4odrjz9Cfz6vr9eNEFOTk/SDY4/QR7eeoLP7tY4cf3/BZp189yd6cMKyqPxs5m/YrT+/vUhS2Brp0oFxs3EtgMq1aJiu1/5vhJ774TA1DkfD2jbO0D8v8fPLJ2pGVT+5D8yskyQ552Y45+5zzt2noNH4vdEuDgdavX2fZq3dJUka0SVbKUnf/vEd1bGp3r75WI0Z0EZS0H/x4U9X6PyHvtDyrXVzwr9zTvd8sES/f2tB5Njtp/fUL87oFTMjQq0apeuB7w7S01cPPeDy8t/eW1zjI5m5BUVBa6RwlPBnp/Wo9BIHgPhjZhrepZmaZAa/mBPE4l9VP8GfSHrfzLqVHjCzn0v6saTjo1kYvu2NcHRMCuYDVSQrPVX/vGSg/nnxADUM962Zt36Pzr7vcz33Zd2a8F9S4vS7Nxfo3o+WSgrm0/35vL66/oTYbAc0slu23rn5WP3stB5KTw3++a3Yuk+X/WeqfvTsDG3anXfY7/G78Qu0YmtwafvYbtn64bFHHPZrAgCiq6qNYd+WdL2kd8ysj5n9U9K5ko5zzq2rhfoQcs7p9VnrJQW/CZ3Wp1WVzxkzsK3evvlYHdUxaBy9v7BYv3i17kz4Lywu0U9fmq0nJq2SFF6au2Sgvju0g9/CqlAvJVk3jOqqD39yvE7t3TJy/K05G3XSPybqP5+tUGHxoV3GfHP2hkjT9OwGafrHRf3ZGBIA4kCVY5zOuY8UzBmbKOkISSc653ZGuS58w/wNeyKjHif3anFAg9nKtG+aqReuGVbnJvznFRbr+qdn6NWZQUhNT03So1cO1jn9Kx45jDXtmmTqkSsG6/HvDVaHcKPafQXF+uP/Fuqc+z/Xlyt3HNTrrd2RqztenRv5+h8XDYjKnmsAgJpXrV6Wkt6WlCXpJElb6nIvy7GPTdWov0/U2Mem+i7lAK+HwUOSRg84uK0L6tqE/5z8Il3136/04cLNkqSG6Skad/VQjeoRn62ATuzZUu//+DjdfFK3yDyQRZv26qKHJ+vWF2drW05+la9RWFyiG5+bqb35QWuka447Qsd3bx7VugEANae6vSwbOufSnHP163ovy3U792vltn1at3O/71Iiikuc3pwTzB/LSk/RCT0O7T/aujDhf8e+An330SmavGK7pOCy3PPXDNPRVWyWGOvSU5P141O66/1bjjsgSL0yY51O/PtEjZu8qtL+dfd8sCSy4KNv20b66am0RgKAeMKyjDgwdcX2yOaeZ/ZtfVhtb+J5wv/G3ft10cOTNWfdbknBMu8Xrx2uI+vQrtSdsuvriauO1r8vH6Q2jYLLjXvyivTrN+ZrzINfaNbaXXLO6cuVO7QtbAm1ZU+eHpq4XJJUP2yNxIorALGmXZMMdc6uH7lSgwPVztblOCxlV1eeW8nqyoMxZmBbHdWxiW55YZamr94ZmfA/cfEW/fX8fmpSP61G3qemrNoWrERcvysYuezSvL6e/sFQtW5U9/5hm5lO79Nax3Vvrvs+Wqb/fLZCRSVOc9fv1nn/+kKdm9XXijIbBJd2JJCkP57XR52y6/soGwAqNe7qob5LiGn8Gh3j8gqL9fa8jZKkVlnpGtq58gbjByNeJvwv2LBHF/57ciSM9W3bSC9eO7xOhrGyMtNS9PMzeurdW47V8COCn7tzOiCMlWWS+rVrXHsFHgR+MwaAyhHIYtzExVu1Ny+YqH1O/9Y1vut8rE/4n756hy55ZHJkYvvQzk317A+HqlmDel7rqk1dWzTUsz8cqnsvGVDpz99Jenbqmtor7CCMu3qoJvz0BH5DBoAKEMhi3BuzDn115cGIxQn/nyzZqsv+M1V7wkB6cq8WevL7QxKyBVBwGbNVpRP7JWnRpjq5+BkA6jwCWQzbk1eojxYFzaG7NK+vI9tEd2FrLE34f2vOBv3gya+UVxiM0I0Z0EYPXX6U0lMPfUFDvEtNSlJGFX/+6u5PBwCILQSyGPbuvE2RS4ZjBrSttb6Mvnf4f+7LNbrxuZkqLA4C4BXDO+ruiwYoNTmx/7omJdkBDcrLE08b4wIAvpbY/8PFuLKXK2tqdWV1+Zrw//Any/WLV+eqdDDuphO76nfnHkn7n9DNJ3dTdoPyV8Ae2y1bpx1ZdUstAEDsIZDFqC178jRpebD56cAOjdWxWe1vZVCbE/6dc7rz3UX6yzuLIsd+dVYv/eTUHrU2MhgP2jXJ1Gv/d8wBI2VJJt0wqosevWJwjS/6AADUDgJZjBo/e0NklGi058tQ0Z7wX1zi9MvX50U2N00y6a4L++kHxx5x2K9dF7VvmqkHvjtIHZsF/S87NM3Uz07rmdDz6wAg3hHIYtT42cFmsMlJprNjYF5QtCb8FxSV6ObnZ0a2a0hLTtK/Lhukiwa3r7Ha66qkcOSQEUQAiH8Eshi0YmtOpD3QyK7Zyo6hPbdqcsL//oJiXTNumt6aE2x8m5mWrMe/d7RO71P5xHUAAOoaAlkMKtsqaXQtT+avjpqY8L97f6GueHyqJi7eKklqlJGqZ34wVCO7ZUerbAAAYhaBLMY45yKrK9NTk3RqjK6aO5wJ/1v35uvSR6boq1U7JUktGtbTi9cO18AOTWqldgAAYg2BLMbMWbdbq7bnSpJO7tVSDerFdv/3qib8L9iwR78dP1+b9+RJknILinTRw5O1YGOwo3z7phl6+boR6tGqobc/AwAAvsX2//YJ6PUye4+NiWKrpJpUOuH/hB4t9OvX52lvfpHmrd+j0+75VEXfaPWzeU++pKAvZY+WDfXU1UPUMivdQ9UAAMQORshiSHGJ05uzgwnujTNTdVz35p4rOjjfnPD/zTBW1hHZ9fXCtcMIYwAAiEAWUyYt36ZtOcHo0Zl9WystJf5+PKUT/jtnV76RbZsmGWqcWf6O8wAAJJr4+x+/DjtgdWUM7D12qFKSk6rcxX/5lsPfUBYAgLqCQBYj8gqL9e68TZKkNo3SdXSnpp4rOjyNMlIP634AABIJgSxGfLRwi3LyiyRJ5wxoE/fNtKtqhn5OHI8AAgBQ0whkMeKNOFxdWZnLh3VUzwq2sujRsqGuGN6xlisCACB2EchiwO7cwsiO9d1bNqgwyMSTBvVS9MI1w3Xl8I4H7KXWMD1FL1w7TA3TuWQJAEApAlkMeGfeRhUUB5PgRw9oW2eaRTfKTNXvRvfRzN+cog5NMyVJ2Q3qsboSAIBvIJDFgLKbwZ5bB+dWpSYnKTnO58QBABBNBDLPNu7er6krd0iSBndsovbhSBIAAEgcBDLP3py9QS7c0H70wPifzA8AAA4egcyz0s1gU5JMZ/Vt7bkaAADgA83FPVq2Za/mb9gjSTque3M1rc9kdwB1U7smGQd8BnAgAplHB7RKqmIjVQCIZ+OuHuq7BCCmccnSE+dcJJBlpCbrlN4tPVcEAAB8IZB5MmPNLq3ZkStJOvXIlspMY7ASAIBERSDzZHwda5UEAAAOHYHMg8LiEr01Z6MkqWn9NI3slu25IgAA4BOBzIMvlm3T9n0FkqSz+rZWajI/BgAAEhlJwANWVwIAgLIIZLVsf0Gx3pu/SVKwH89RHZt4rggAAPhGIKtlHyzcrNyCYklBI3Ezmm4DAJDoCGS17IDVlfSuBAAAIpDVqp37CjRx8VZJUq/WWeresqHnigAAQCwgkNWit+dtVFGJk8RkfgAA8DUCWS16Y+bXqyvP7U8gAwAAAQJZLVm3M1dfrtohSRrSuanaNM7wXBEAAIgVBLJa8ubsjZHbtEoCAABlEchqyRvh6srUZNOZfVt5rgYAAMQSAlktWLRpjxZt2itJOr57CzXOTPNcEQAAiCUEslpAqyQAAFAZAlmUlZQ4jQ8DWf20ZJ3cq6XnigAAQKwhkEXZ9DU7tX7XfknSaUe2UkZasueKAABArCGQRdkbZVoljaZVEgAAKAeBLIoKi0v0vznBdhfZDdJ0TJdmnisCAACxiEAWRZ8t3aqduYWSpLP7tVFKMt9uAADwbSSEKHp9JqsrAQBA1QhkUbIvv0gfLNgsSerYLFMD2jf2WxAAAIhZKb4LqKs+WLBZ+wuLJUmj+7eRmXmuCAAAVEe7JhkHfK4NBLIoeb3M6spz6V0JAEDcGHf10Fp/Ty5ZRsH2nHx9tnSbJKlP2yx1bdHAc0UAACCWEcii4H9zN6q4xEmSRvdndAwAAFSOQBYFpb0rzaRz+rO6EgAAVI5AVsPW7sjV9NU7JUnDOjdTq0bpnisCAACxjkBWw8bP/nrvsTEDGR0DAABVY5VlDXLO6fWZwerKtOQknd6nteeKAAB1mY/tGRAdBLIatHDjXi3dkiNJGtWzuRplpHquCHUZJ2IAPrZnQHRELZCZWXtJT0lqKclJesQ5d6+Z/U3SOZIKJC2XdJVzblf4nF9IulpSsaSbnHPvRau+aHijzN5jo9l7DFHGiRgA6o5oziErknSrc663pGGSbjCz3pI+kNTHOddP0hJJv5Ck8L5LJB0p6XRJ/zKz5CjWV6NKSlxk/ljDeik6sWcLzxUBAIB4EbVA5pzb6JybEd7eK2mhpLbOufedc0Xhw6ZIahfeHi3peedcvnNupaRlkoZEq76a9uWqHdq4O0+SdFqfVkpPjZssCQAAPKuVVZZm1knSQElTv3HX9yW9E95uK2ltmfvWhce++VrXmNk0M5u2devWKFR7aMperhzD5UoAAHAQoh7IzKyBpFck3eKc21Pm+C8VXNZ85mBezzn3iHNusHNucPPmzWu22EOUX1Sst+dukiQ1b1hPw7s081wRAACIJ1FdZWlmqQrC2DPOuVfLHP+epLMlneScc+Hh9ZLal3l6u/BYzPtk8Vbt3l8oSTqnXxslJ5nnigAAQDyJ2giZmZmkxyQtdM7dXeb46ZJuk3Sucy63zFPGS7rEzOqZWWdJ3SR9Ga36atIbbAYLAAAOQzRHyI6RNFbSXDObFR67Q9J9kupJ+iDIbJrinLvOOTffzF6UtEDBpcwbnHPFUayvRuzNK9SHCzZLkjpn11ffto08VwQAAOJN1AKZc+5zSeVdu3u7kuf8SdKfolVTNLw/f7Pyi0okSaMHtFEYMgEAAKqNXpaH6XU2gwUAAIeJQHYYtu7N1xfLtkmS+rdrpM7Z9T1XBAAA4hGB7DC8NWeDSsI1oucyOgYAAA4RgewwvDErWF2ZZNI5/Vp7rgYAAMQrAtkhWrVtn2at3SVJGtElWy2y0v0WBAAA4haB7BCVjo5JwepKAACAQ0UgOwTOOb0xO1hdmZaSpNP6tPJcEQAAiGcEskMwb/0erdi6T5J0cq8WykpP9VwRAACIZwSyQ/AGe48BAIAaRCA7SMUlTuPD3pVZ6Sk6oUdzzxUBAIB4RyA7SFNXbNeWvfmSpDP7tla9lGTPFQEAgHhHIDtIZVslncvqSgAAUAMIZAchr7BY78zbJElqlZWuoZ2bea4IAADUBQSygzBx8RbtzSuSJJ3Tv7WSk8xzRQAAoC4gkB2EAzeDZXUlAACoGQSyatqTV6iPFm2RJHVpXl9HtsnyXBEAAKgrCGTV9O7cTSooKpEkjRnQVmZcrgQAADUjxXcB8aK0VZLE6koAqMvaNck44DNQGwhk1bB5T54mLd8uSRrYobE6NqvvuaIAJw0AqHnjrh7quwQkIAJZNbw5e4OcC26P7h87o2OcNAAAqBsIZNVQuroyOcl0dgwFsnjCaB4AABUjkFVh+dYczV2/W5I0smu2shvU81xRfGI0DwCAirHKsgoH7j3G6BgAAKh5BLJKOOc0PuxdmZ6apFOPbOW5IgAAUBcRyCoxe91urdqeK0k6uVdLNajHFV4AAFDzCGSVeGPW13uPjaFVEgAAiBICWQWcc3pz9kZJUuPMVB3XvbnnigAAQF1FIKvA/sJibcvJlySd2be10lL4VgEAgOggZVRgX35x5HYsbQYLAADqHmapV2BfQZEkqU2jdB3dqannalBb2MAWAOADgawCpa2SzhnQRklJ5rcY1Bo2sAUA+MAlyyqwuhIAAEQbgewbiktc5Hb3lg3Us1VDj9UAAIBEwCVLSSUlTs9/tVZPTV6lNTtyI8dP7d1KZlyuBAAA0ZXwI2TOOd3+yhzd8dpcLdq094D7Xpu5LrL1BQAAQLQkfCD7Ytl2vTR9Xbn3rd+Vp3s/XFrLFQEAgEST8IHs1Rnlh7FSr81cr5Iy88oAAABqWsIHsq1VXJLMyS9SXlFxpY8BAAA4HAkfyDpn16/0/hYN6ykjNbmWqgEAAIko4QPZpUM6VHr/d4d2YKUlAACIqoQPZL1aZ+nXZ/cu975ju2XruuO71HJFAAAg0SR8IJOkq0d21us3HKMLj2qntJTgW9K8QT3993tHK53LlQAAIMrYGDY0oH1jDWjfWNNX79TKbfvUID1FKcnkVQAAEH0kDgAAAM8IZAAAAJ4RyAAAADwjkAEAAHhGIAMAAPCMQAYAAOAZgQwAAMAzAhkAAIBnBDIAAADPCGQAAACeEcgAAAA8I5ABAAB4RiADAADwjEAGAADgGYEMAADAMwIZAACAZwQyAAAAzwhkAAAAnhHIAAAAPCOQAQAAeEYgAwAA8IxABgAA4BmBDAAAwDMCGQAAgGcEMgAAAM8IZAAAAJ4RyAAAADwjkAEAAHhGIAMAAPCMQAYAAOAZgQwAAMAzAhkAAIBnBDIAAADPCGQAAACeEcgAAAA8I5ABAAB4RiADAADwjEAGAADgWdQCmZm1N7MJZrbAzOab2c3h8aZm9oGZLQ0/NwmPm5ndZ2bLzGyOmQ2KVm0AAACxJJojZEWSbnXO9ZY0TNINZtZb0s8lfeSc6ybpo/BrSTpDUrfw4xpJD0WxNgAAgJgRtUDmnNvonJsR3t4raaGktpJGS3oyfNiTksaEt0dLesoFpkhqbGato1UfAABArKiVOWRm1knSQElTJbV0zm0M79okqWV4u62ktWWeti48BgAAUKdFPZCZWQNJr0i6xTm3p+x9zjknyR3k611jZtPMbNrWrVtrsFIAAAA/ohrIzCxVQRh7xjn3anh4c+mlyPDzlvD4ekntyzy9XXjsAM65R5xzg51zg5s3bx694gEAAGpJNFdZmqTHJC10zt1d5q7xkq4Mb18p6Y0yx68IV1sOk7S7zKVNAACAOisliq99jKSxkuaa2azw2B2S/irpRTO7WtJqSReF970t6UxJyyTlSroqirUBAADEjKgFMufc55KsgrtPKufxTtIN0aoHAAAgVrFTPwAAgGcEMgAAAM8IZAAAAJ4RyAAAADwjkAEAAHhGIAMAAPCMQAYAAOAZgQwAAMAzAhkAAIBnBDIAAADPCGQAAACeEcgAAAA8I5ABAAB4RiADAADwjEAGAADgGYEMAADAMwIZAACAZwQyAAAAzwhkAAAAnhHIAAAAPCOQAQAAeEYgAwAA8IxABgAA4BmBDAAAwDMCGQAAgGcEMgAAAM8IZAAAAJ4RyAAAADwjkAEAAHhGIAMAAPCMQAYAAOAZgQwAAMAzAhkAAIBnBDIAAADPCGQAAACeEcgAAAA8I5ABAAB4RiADAADwjEAGAADgGYEMAADAMwIZAACAZwQyAAAAzwhkAAAAnhHIAAAAPCOQAQAAeEYgAwAA8IxABgAA4BmBDAAAwDMCGQAAgGcEMgAAAM8IZAAAAJ4RyAAAADwjkAEAAHhGIAMAAPCMQAYAAOAZgQwAAMAzAhkAAIBnBDIAAADPCGQAAACepfguINa0a5JxwGcAAIBoI5B9w7irh/ouAQAAJBguWQIAAHhGIAMAAPCMQAYAAOAZgQwAAMAzAhkAAIBnBDIAAADPCGQAAACeEcgAAAA8I5ABAAB4RiADAADwjEAGAADgGYEMAADAMwIZAACAZwQyAAAAzwhkAAAAnhHIAAAAPCOQAQAAeEYgAwAA8IxABgAA4BmBDAAAwDMCGQAAgGcEMgAAAM/MOee7hkNmZlslrY7CS2dL2haF140Gaq158VKnRK3RQq3RQa3RQa3REY1aOzrnmpd3R1wHsmgxs2nOucG+66gOaq158VKnRK3RQq3RQa3RQa3RUdu1cskSAADAMwIZAACAZwSy8j3iu4CDQK01L17qlKg1Wqg1Oqg1Oqg1Omq1VuaQAQAAeMYIGQAAgGcJH8jM7GYzm2dm883slm/cd6uZOTPL9lTb42a2xczmlTnW1Mw+MLOl4ecm4fHLzGyOmc01s0lm1j+Ga21kZm+a2ezw+35VDNT6nbCWEjP71qoaM+tgZjlm9tMYqPVvZrYo/Hm/ZmaNy9z3CzNbZmaLzey0GK+1n5lNDr/vc80s3XOtfwjrnGVm75tZm/B4z7DO/Nr++R9CrbF4Hqio1pg7D5S5r9xzv5kdbWZFZnZh7VVa4ff1t2a2Pvy+zjKzM8vc5+U8cAh1xtQ5IDx+Y3jOmm9md4XHTjGz6WGN083sxKgU5ZxL2A9JfSTNk5QpKUXSh5K6hve1l/Segn3Osj3Vd5ykQZLmlTl2l6Sfh7d/LunO8PYISU3C22dImhrDtd5R5nZzSTskpXmutZekHpImShpcznNelvSSpJ/GwPf1VEkp4e07y3wve0uaLamepM6SlktKjtFaUyTNkdQ//LpZDNSaVeb2TZL+Hd5uIeloSX+q7Z//IdQai+eBimqNufNAeLzcc7+kZEkfS3pb0oUx8H39bXl/H32eBw6yzlg8B4xSkAPqhV+3CD8PlNQmvN1H0vpo1JToI2S9FJywcp1zRZI+kXR+eN89km6T5G2SnXPuUwUnqbJGS3oyvP2kpDHhYyc553aGx6dIalcbNZY6mFoVfE8bmplJahA+r6gWygzevJxanXMLnXOLy3u8mY2RtFLS/OhXd6AKan0//PsqHfizHi3peedcvnNupaRlkobEaK2nSprjnJsdPm67c67Yc617ynxZX+G/fefcFufcV5IKa6u+b9R1MLXG3HmgoloVg+eBUEXn/hslvSJpS5RL+5ZKai2Pt/PAQdYZc+cASddL+qtzLj98zJbw80zn3IbwMfMlZZhZvZquKdED2TxJx5pZMzPLlHSmpPZmNlpBAp7tt7xytXTObQxvb5LUspzHXC3pndorqUIV1fqAgjC8QdJcSTc750o81FclM2sg6XZJv/NdSwW+r69/1m0lrS1z37rwWKwoW2t3Sc7M3jOzGWZ2m8e6IszsT2a2VtJlkn7ju57KVKPWWDkPVFRrzJ0HKjr3m1lbSedJeshLYRX7UXg5+HELp4QoNs8D5dUZi+eA7goywVQz+8TMji7nMRdImlEa2mpSQgcy59xCBZdR3pf0rqRZCoZ571CMn4wlyQXjpwf8FmdmoxSciG/3UlQFvlHraQq+120kDZD0gJll+amsSr+VdI9zLsd3Id9kZr9UMKLwjO9aqlJOrSmSRir4D3qkpPPM7CRP5UU4537pnGuvoM4f+a6nMpXVGmvngQpqjanzQPhLeUXn/n9Kut13YPyGhyR1UfC92yjpH16rqVhFdcbiOSBFUlNJwyT9TNKL4QiuJMnMjlSQGa6NxpsndCCTJOfcY865o5xzx0naqWA4srOk2Wa2SsGQ/wwza+WxzLI2m1lrSQo/R4bPzayfpP9IGu2c2+6pvrIqqvUqSa+6wDIFlwN7eqqxKkMl3RX+XbhF0h1m5v0/ajP7nqSzJV0Whl1JWq9g/kupduExryqodZ2kT51z25xzuQrm5QzyVGJ5nlHwm3A8OKDWGDwPlFW21lg7D3RRxef+wZKeD49fKOlf4VQGb5xzm51zxWFIfFRfX5aMqfNAJXXG4jlgnb7+O/mlpBIF/SxlZu0kvSbpCufc8mi8ecIHMjNrEX7uoGD+2JPOuRbOuU7OuU4KfkCDnHObPJZZ1nhJV4a3r5T0hhSp/1VJY51zSzzV9k3l1ippjaSTJMnMWiqYTL+i1qurBufcsWX+LvxT0p+dcw/4rMnMTlcwx+Xc8ERWarykS8ysnpl1ltRN0pc+aixVSa3vSeprZplmliLpeEkLfNRYysy6lflytKRFvmqpSkW1xuJ5oJLva0ydB5xzcys69zvnOpc5/rKk/3POve6rVinyS26p8xRMwZFi7DxQSZ0xdw6Q9LqCif0ys+6S0iRts2B1+P8ULFL7Imrv7qKwUiCePiR9puAvwWxJJ5Vz/yr5W2X5nIIh3kIFJ4erFaxE+UjSUgWrQZqGj/2PghG+WeHHtBiutY2Cy8RzFfzjvDwGaj0vvJ0vabOk98p53m9V+6ssy6t1mYI5IqU/63+XefwvFayqWizpjBiv9XIFI9LzJN0VA7W+EtYyR9KbktqGj20VPmaPpF3h7awYrTUWzwMV1Rpz54Fv3L9K5Zz7JT2h2l9lWd73dVz4vZujIIS1LvN4L+eBQ6gz1s4BaZKeDuuZIenE8LG/krSvzL+rWQpXYNbkBzv1AwAAeJbwlywBAAB8I5ABAAB4RiADAADwjEAGAADgGYEMAADAMwIZgLhhZjllbp9pZkvMrOMhvE4nM9tvZrPMbLaZTTKzHodY09vhPkUH+7w2ZvbyobwngLqHbS8AxA0zy3HONQhbrDws6TR3CLtmm1knSW855/qEX18raYRz7spKnwgAUcIIGYC4YmbHKWjBcnZpGDOzH5rZV+Fo1ythX0KZ2RNmdl84ArbCzC6s4GWzFGyoWjp69lnY8HiGmY0Ij7c2s0/DUbV5ZnZseHyVmWWHz1toZo+a2Xwze9/MMsLHdDWzD8P6ZphZl/Dx8yqoB0CCYYQMQNwws0JJeyWd4JybU+Z4Mxf2bTSzP0ra7Jy738yekFRf0sUK+iSOd851DUfIFirYybyhpExJQ51za8IwV+Kcywvb/jznnBtsZrdKSnfO/cnMkiVlOuf2hv0NB0tqoKAzwWDn3CwzezF8v6fNbKqkvzrnXjOzdAW/DLdQmVE6AIktxXcBAHAQCiVNUtDm5OYyx/uEQayxgmD0Xpn7XndBY+MFYc/EUsudcwMkycwulvSIpNMlpUp6wMwGSCqW1D18/FeSHjez1PA1Z5VT38oyx6dL6mRmDRW0C3pNkpxzeeF7HuyfHUAdxiVLAPGkRNJFkoaY2R1ljj8h6UfOub6Sficpvcx9+WVuV5SCxks6Lrz9YwX9TPsrGPlKkyTn3KfhY9ZLesLMrijndcq+V7H4pRdANRHIAMQV51yupLMkXWZmV4eHG0raGI5eXXYILztSQTNmSWokaWM4qjZWUrIkhas5NzvnHlXQxHtQNevdK2mdmY0JX6de6Rw3ACjFb28A4o5zboeZnS7pUzPbKunXkqZK2hp+bliNl+liZrMUjJoVSPpBePxfkl4JR8DelbQvPH6CpJ+F89hyJJU3QlaRsZIeNrPfK7js+h0Fo30AIIlJ/QAAAN5xyRIAAMAzAhkAAIBnBDIAAADPCGQAAACeEcgAAAA8I5ABAAB4RiADAADwjEAGAADg2f8HHPVCeVAeS5wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.pointplot(x=\"KanBasinci\", y=\"Kolesterol\", data=df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 457,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,6))\n",
    "sns.pointplot(x=\"Yas\", y=\"Kolesterol\", data=df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 458,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "sns.pointplot(x=\"GogusAgrisi\", y=\"KanSekeri\", data=df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 459,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0xWZ0w/h0kiPWbN9ovm/Dc6rqKkkOT/Ifm/DYAABwhdmMsPy+JLesqptW1SFJHpHktHXnnJbkMfPbD03ypl60/wcAAFzBFu6G0d0XVdUTk7w2yZWT/El3n1NVz0xyRnefluRFSV5aVR9L8sXMAjUAAGxrm9Jnubtfk+Q16/Y9Y83tryX5ic14LAAA2CpW8AMAgAFhGQAABoRlAAAYEJYBAGBAWAYAgAFhGQAABoRlAAAYEJYBAGBAWAYAgAFhGQAABjZluWsADh7nnnTswvexe/funHvcrsWLAZiYK8sAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADBwlakLAKZz7knHLnwfu3fvzrnH7Vq8GADYhlxZBgCAAWEZAAAGhGUAABgQlgEAYEBYBgCAAWEZAAAGhGUAABgQlgEAYEBYBgCAAWEZAAAGLHcNEEt/A7AxV5YBAGBAWAYAgAFhGQAABoRlAAAYEJYBAGBAWAYAgAFhGQAABoRlAAAYEJYBAGBAWAYAgAFhGQAABoRlAAAYEJYBAGBAWAYAgAFhGQAABoRlAAAYEJYBAGBAWAYAgAFhGQAABoRlAAAYEJYBAGBAWAYAgAFhGQAABoRlAAAYEJYBAGBAWAYAgAFhGQAABoRlAAAYEJYBAGBAWAYAgAFhGQAABoRlAAAYEJYBAGBAWAYAgIGFwnJVXaeqXl9VH53/vPYG59y+qt5VVedU1Qer6uGLPCYAAGyVRa8sn5jkjd19yyRvnG+v95UkP9Xd35fkmCS/W1XXWvBxAQDgCrdoWH5QklPmt09J8uD1J3T3P3f3R+e3P5Pk80mut+DjAgDAFW7RsLyjuz87v/25JDv2dnJV3TnJIUn+ZcHHBQCAK1x1995PqHpDkutvcOhpSU7p7mutOfc/u/tS/Zbnx26QZHeSx3T3uwfnnJDkhCTZsWPHnU499dR9+C+Mnf3p8xf6/STZcfXkvK8udh9H3fDwhetYlLbYXHv27Mmhhx46dRnbgrZYpS1WaYtV2mLVwdIW2+Ezdbt8nh4sbXH00Uef2d07Nzp2mWF5b6rqI0l2dfdnV8Jwd996g/MOyywoP7u7X7kv971z584+44wz9ru2JDnyxNMX+v0kecpRF+W5Z19lofs496RjF65jUdpic+3evTu7du2auoxtQVus0hartMUqbbHqYGmL7fCZul0+Tw+WtqiqYVheLPkkpyV5TJKT5j//doMHPyTJXyf5030NyptlMxpv9+7dOfe4XYsXAwDAAWfRPssnJblPVX00yQ/Pt1NVO6vqhfNzHpbkHkmOr6qz5v9uv+DjAgDAFW6hK8vd/R9J7r3B/jOSPH5++8+S/NkijwMAAFOwgh8AAAwIywAAMCAsAwDAgLAMAAADwjIAAAwIywAAMCAsAwDAgLAMAAADwjIAAAwIywAAMCAsAwDAgLAMAAADwjIAAAwIywAAMCAsAwDAgLAMAAADwjIAAAwIywAAMCAsAwDAgLAMAAADwjIAAAwIywAAMCAsAwDAgLAMAAADwjIAAAwIywAAMCAsAwDAgLAMAAADV5m6ALbGuScdu/B97N69O+cet2vxYgAADhCuLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAA8IyAAAMCMsAADAgLAMAwICwDAAAAwuF5aq6TlW9vqo+Ov957b2ce1hVfaqqXrDIYwIAwFZZ9MryiUne2N23TPLG+fbIbyR564KPBwAAW2bRsPygJKfMb5+S5MEbnVRVd0qyI8nrFnw8AADYMtXd+//LVV/q7mvNb1eS/1zZXnPOlZK8Kcmjkvxwkp3d/cTB/Z2Q5IQk2bFjx51OPfXU/a5ts+zZsyeHHnro1GVsC9pilbZYpS1WaYtV2mKVtlh1sLTF2Z8+f+H72HH15Lyv7v/vH3XDwxeuYTMcLG1x9NFHn9ndOzc6dpXL+uWqekOS629w6GlrN7q7q2qj5P1zSV7T3Z+a5emx7j45yclJsnPnzt61a9dllXeF2717d7ZDHduBtlilLVZpi1XaYpW2WKUtVh0sbXH8iacvfB9POeqiPPfsy4xhQ+cet2vhGjbDMrTFZVbW3T88OlZV51XVDbr7s1V1gySf3+C0/5rkh6rq55IcmuSQqtrT3Xvr3wwAAJPb/xg/c1qSxyQ5af7zb9ef0N3HrdyuquMz64YhKAMAsO0tOsDvpCT3qaqPZtYf+aQkqaqdVfXCRYsDAIApLXRlubv/I8m9N9h/RpLHb7D/JUlesshjAgDAVrGCHwAADAjLAAAwICwDAMCAsAwAAAPCMgAADAjLAAAwsOiiJAAALKlzTzp24fvYvXv3tlm+eyOuLAMAwICwDAAAA7phAABcDsvQ9YBVriwDAMCAsAwAAAPCMgAADAjLAAAwICwDAMCAsAwAAAPCMgAADAjLAAAwICwDAMCAsAwAAAPCMgAADAjLAAAwICwDAMCAsAwAAAPCMgAADAjLAAAwICwDAMCAsAwAAAPV3VPXsKGq+vckn5y6jiTXTfKFqYvYJrTFKm2xSlus0hartMUqbbFKW6zSFqu2Q1vcpLuvt9GBbRuWt4uqOqO7d05dx3agLVZpi1XaYpW2WKUtVmmLVdpilbZYtd3bQjcMAAAYEJYBAGBAWL5sJ09dwDaiLVZpi1XaYpW2WKUtVmmLVdpilbZYta3bQp9lAAAYcGUZAAAGhGUAABgQlgEAYEBYXqeqbl5V3zG/vauqfqGqrjVxWQAAB7SquuvUNewPA/zWqaqzkuxMcmSS1yT52yTf1933m7CsSVTVG7v73pe172BWVd/T3R+uqjtudLy737/VNbE9VNV19na8u7+4VbWw/VTVddY/B6rqpt39ialqYjpVdVh3f3n0vrEs7xdV9f7u3vDzdDu7ytQFbEPf7u6LqurHkjy/u59fVR+YuqitVFVXS/KdSa5bVddOUvNDhyW54WSFTePJSU5I8twNjnWSe21tOdOqqpd398Oq6uzM/v8XH0rS3X27iUqbwpmZtUFtcKyT3Gxry5mO58WG/q6q7tvdX06SqrpNkpcnue20ZW0dz4tL+Isk98/G7xtL9X5xIHJleZ2qek+S303ytCQP6O5PVNWHunuZ3uB+MckvJfnuJJ9Zc+jLSf64u18wRV1Mr6pu0N2fraqbbHS8uz+51TUxPc+LS6uqY5P8cpJjk9w6yZ8mOa67z5qyrq3kecF6VfWlJG8dHe/uB25dNftOWF5n/tf/E5K8q7tfVlU3TfKw7n7OxKVtuap6Unc/f+o6toOq+okkf9/dF1TV05PcMclvdPdSfeuwYv66+Gx3f22+ffUkO7r73EkLm0hVPTDJPeabu7v71VPWM4WqunKSN3T30VPXsl1U1YMzC8zXTPKQ7v7naSuaRlX9SpIXd/en1uw7obu39UIUV4SquluSs7r7wqp6VGafJb/b3f86cWlboqo+muTxo+Pd/ZYtLGefCcsMVdU1kvz3JDfu7hOq6pZJbr2kQeCD3X27qrp7kmcl+e0kz+juu0xc2iSq6owkP9jd35hvH5LkHd39A9NWtvWq6qQkP5Dkz+e7Hpnkfd39v6erahpV9cYkP97d509dy1Sq6vm5ZJeDeyf5lyTnJkl3/8IEZU2qqj6f5N+TPLG73zzfd0D2XV1UVX0wyfcnuV2SlyR5YWYX5O45ZV1bpao+0N13mLqOy0uf5XXmgfA3k9wmydVW9nf3MvYn+pPM+lf94Hz700lekWTpwnKSb81/Hpvk5O4+vaqeNWVBE7vKSlBOku7+xjwwL6P7Jbl9d387SarqlCQfSLJ0YTnJniRnV9Xrk1y4snPJAuIZ67bPnKSK7eXTSR6U5BVV9cru/u1s3Nd/GVzU3V1VD0rygu5+UVU9buqittB/VtX1u/tzSVJVP5XkIUk+meTXtutAR2H50l6c5FeT/E6So5M8Nss7xd7Nu/vhVfXIJOnur1TVsr7Bfbqq/ijJfZI8Zz694LI+L5Lk36vqgd19WpLM3/i/MHFNU7pWkpU3+cMnrGNqfzX/t7S6+5Spa9iOuvtfq+qeSf6wql6R5OpT1zSRC6rqqUkeleQeVXWlJFeduKatdK0kK99I3iPJSUmelOT2SU5O8tCpCtsbYfnSrt7db6yqmg8++LWqOjPJM6YubALfmPdF7WQ2B3WSr09b0mQeluSYJP+nu79UVTdI8j8nrmlKT0jy51X1gsyuEP1bkp+atqTJPDvJB6rqzZm1xT2SnDhtSdPo7lPm7xk37u6PTF3PFPYyA0SSZMlmgFhxRpLMxzg8tqp+Psmdpi1pMg9P8pNJHtfdn6uqG2fWrW9ZXGnN1eOHZ/ZN7auSvGo+de+2pM/yXFW9JsnPZ9bv8O5JXpnkTZl9fXRSd996wvImUVU/ktmsILdJ8rokd0tyfHfvnrKurWRuzL2rqkOTpLv3TF3LFOZXhR6a5G2Z9VtOkveufMW4bKrqAUn+T5JDuvumVXX7JM/criPcrwhV9d3d/RkzQMClVdWHMuu2dlFVfTjJCd391pVj23XmMWF5bj7bwf+T5KWZTR13eJLfyGxu4d/q7vdMV910quq/JLlrZlfM3t3dS/VVe1W9urvvX1WfyAZzYy5pX/bMu6E8JLPFey7+hqq7nzlVTVOpqjO6e+fUdWwH82/h7pXZjCB3mO/bth+AV4SVgWtV9dLufvTU9UzJVfZVVfX27r57VV2QjeecPmyi0rZUVT0ts3EeX0hy4yR3nPfhvkWSU7r7bpMWOCAsrzG/SvYrmX3d/tKsPqG7u583WWETqapXJXlRZlOmfXvqeqYy76d9xLJM7bMvqurvk5yf2eCllcGP6e6NFm85qM1nw/hCkr/MJQe1Ld23DlX17u6+69oR7yszyUxd21aZXzl7dmYXWy7VVau7l6ZPt3mW2UjNlry+QZLXdfeF8323SnJob9NVcfVZvqRvZPZh9x2ZzYu5tAFx7g8zG+D4/PmAjBcvYz/E+V+9pyc5aupatpEbdfcxUxexTTx8/vPn1+xb1hW5zqmqn0xy5fnMQr+Q5J0T17TVnpDkuMwGMj1g3bHOEg2A7O7Pzn8Kxbl4LvJzuvt7pq5lSt397g32bes5yIXluao6JsnzkpyW2dcCX5m4pMl19xuSvKGqDs9s7tg3VNW/JfnjJH/W3d+ctMCt9f6q+oHuft/UhWwT76yqo7r77KkLmVp333TqGraRJ2U2zuHrmS3v+7okS9U1p7vfnuTt8+45L5q6nilt0OXg4kNZoq4HK7r7W1X1kaq6sW8qDyy6YcxV1duSPKG7z5m6lu1k3mf5UUkendnS1ysDII/q7l0Tlral5gMRbpHZXJAXZvXNfmm+Xl6rqv4xs/b4RGbBaGnbo6q+M8mTY/GeVNXj1gfEqjqpu5dydpCqum0uPWf/n05X0XQO1MUoNltVvTXJHZK8N5fstrU0g2APRK4sz3X3D01dw3ZTVX+d5NaZ9d9+wMpXakn+cr6C2zL50akL2GbuO3UB28iLY/GeFQ+pqq91958nyXxqwaWcT7eqfjXJrszC8msye828PclShuVsfIV5Gf3K1AVw+QnL7M3/XVmadL0lHP1/wT7uO6itTKWXJfy/74XFe1Y9JMlpVfXtzAZKf6m7l2l1srUemtmyxh/o7sdW1Y4kfzZxTUysu98ydQ1cfsIyl1JV9+ruNyW5dlX9+PrjyzSae433JzkiyX9m1uXgWkk+V1XnJfmZ7l6WJW3/Isn9M7uSeqmp9LKcg9qWfvGedfOQPz7J3yR5R5Jfr6rrLOPMIEm+2t3frqqLquqwJJ/P7D1kaaz7/LjW+s+TZfwsGfTjPj+zhVue0t0f3/qquCzCMhu5Z2YLsqwfyZ0s2WjuNV6f5JXd/drk4gVbHpLZV/B/kOQuE9a2Zbr7/vOfBrWt+rUkf5/kiKr688wW73nspBVtvbV/PK38PHb+b1n/iDqjqq6V2YDoM5PsSfKuSSvaems/Q96ybntZP0t+N8mnMrvwUEkekeTmmV2Q+ZPMuu6wzRjgB/ugqs7u7qPW7ftgd9+uqs7q7ttPVNokqupuSc7q7gur6lFJ7pjkd5d1hPeyL97DJc274dyou/9tvn1kksO6+4OTFsbkquofuvv71+07q7tvv9ExtocrTV0A21dV/WJVHVYzL6yq98+vqC6jz1bV/6qqm8z//XKSz8/nzVzG+bj/MMlXqur7kzwlyb9kNhB06VTVG7v7P7r79O5+dXd/oareOHVdU6iq76yqp1fVyfPtW1bV/aeua6v17CrUa9Zsn7vMQdlnySV8paoeVlVXmv97WJKvzY+5erlNCcvszU/PB3P9SJL/ktn0cSdNW9JkfjLJjTLri/k3mS3T+YgkV07ysMmqms5F80DwoCQv6O7fz2whn6VRVVeb99W9blVdu6quM/93ZJIbTlzeVF6c2eJOa2cGedZ05Uzq/VX1A1MXsU34LFl1XGb//88nOW9++1HzcQ9PnLIwxvRZZm9WBm/dL8mfdvc5yzrKf/61+pNWtqvqaplNp/eKJB+brLDpXFBVT81sDu57VNWVklx14pq22n9L8ktJvjuzPqkrr40vJ3nBRDVNzcwgq+6S5LiqMje7z5KLzQfwXWI80HzBq49lNrUg25CwzN6cWVWvS3LTJE+tqqVeAnze5eJHM1vN8D6ZvbG9YtKipvPwzK62P667P1dVN07y2xPXtKW6+/eS/F5VPam7nz91PdvE0s8Msoa52Vf5LFmnqm6T2WfJI5N8KcmyTcd6QDHAj6H51cLbJ/l4d39pPojphsvW966q7plZMLxfZqsu3S3JzSyJTpJU1U8k+fvuvqCqnp7ZYMdndff7Jy5ty1XVfZI8PbOFOF6X2Wvl+O7ePWVdU1g3nd6KC7r7m1tezMR8lszMu2itBORvJrlJkp3dfe6EZbEPhGX2qqpumNkL+uJvIbr7rdNVtLWq6lNJ/jWzAW1/Mw9En1j2qdOq6q5Jnp/ke5Mcklnf7T3dffikhU1gzawod8+sf+5vJ3lGdy/FdILrmRlkpqrOzQZzs2fWT3Up5mavqu/p7g9X1R03Or5Mf1BW1buSHJbk1CSndvdHfZYcOHTDYKiqnpPZ1+3/mORb892dZGnCcpJXJnlwZu3wrar62xixnMz65D4is24oO5P8VJJbTVrRdFZeG8cmObm7T6+qpRrUVlU3yWy1vvO7+z+q6iuZvW5uVVUv6O5vTFvhJMzNnjw5yQlJnrvBsU5yr60tZ1LnZTbwd0eS6yX5aHyWHDBcWWaoqj6S5Hbdvax9DpNcPGfqrsy+OrtfksOTPC7Ja7p7z4SlTaaqzujunStXVef7PtDdd5i6tq1WVa/ObNaH+2TWBeOrSd67TPOlVtV7kvxYd3+mqm6f5A1JfjPJ7ZJ8s7sfP2V9UzA3+6qqulp3f+2y9h3squrwJD+e2WfJLTP7tuFHu/u9U9bFZXNlmb35eGYzHCx1WJ5PkfbmJG+uqqtmdZDfHyS57pS1TegrVXVIkrOq6reSfDbLOxXlw5Ick+T/zPtj3iDJ/5y4pq129e7+zPz2o5L8SXc/d95X9azpyprUZ6vqf2X2tXsy+3bqvCWdm/2dmf0heVn7DmrdfX5m3yy8uKq+K7PnxO9U1Y27e6mWQj/QCMvszVcyC0NvzJrA3N2/MF1J0+rub1bVOzLrx/wzU9czoUdnFo6fmOS/Z9Y38yGTVjSR+fRon09y98y+Wr1o/nOZrJ0G7F5Jnpok3f3tJZ0hLJkNCv7VzOZlT5J3zPctzdzsVXX9zLoeXL2q7pDV58lhSb5zssK2h68leUl3P3/ejYltTDcMhqrqMRvt7+5TtrqWqVXV7iQPzOwPzDMzm1D+Hd395CnrYnpV9auZ9du+dXffqqq+O8kruvtuE5e2Zarq95LcILNvGB6Y5FbzPyxvkOTvuntpp8WaT5PWy9hla/4Zcnxmr4/3ZTUsX5BZUPyriUqbzHyhmj/JbBGnymzauJ9ehgGfBzJhGfbBSn/cqnp8kiO6+1fX9tddFlV1yyRPS/LFJM9L8sdJfiiz5a4f393vm7C8SVTVWUnukOT9K322l+25Me/X//DMAvPLu/vT8/13SPJdK4PclklVHZXkT5OsTCH3hSSP6e4PTVfVNKrqId39qnX7fmBJ3y8+mOTnu/tt8+27J/mDZXq/OBDphsGlVNXLu/thVXV2Nhitu6Qv6qvMr5I9LLOwuKxenFkAOCzJezJbwe7HMgvML8hyjPBf7xvd3VW1shDHNaYuaKvN+/WfusH+D0xQznbxR0me3N1vTpKq2pXk5KwuBb40VoKyhTiSJN9aCcpJ0t1vr6qLpiyIyyYss5HnV9Xdktx/3f4jMpsndBk9M8lrk7y9u99XVTfL8vVLTZJDu/vkJKmqJ8yX+06S11fVUq3gt8bLq+qPklyrqn4myU9ndsV96VTVjyd5TpLvyuwr5pUlng+btLBpXGMlKCdJd+9exj+kLMRxKW+Zv1+8LLOLUQ9PsntlLuplmnv6QKIbBpcynwrrqd199rr9RyV5dnc/YOPf5GBXVe/v7juuv73R9jKZr1z3I5mFw9d29+snLmkSVfWxJA/o7n+aupapVdVfJ3l/kpfOdz0qyZ26+8emq2prWYjj0qrqzXs53N29THNPHzBcWWYjO9YH5STp7rPnVwmWTlW9OBt3SfnpCcqZ0vfM+9xVkpvPb2e+fbPpyprWPBwvZUBe5zxB+WI/neTXk/xVZu8db5vvWyYW4linu4+eugYuP2GZjVxrL8euvlVFbDOvXnP7apn10/3M4NyD2fdOXcB2UVUXZOMP/mXuenBGVf1lZtOlrZ1uculmPUhyo2WeZjNJuvvBaxbi+LX5AOFrVdWdl20hjqra68xJ3f28raqFy083DC6lql6W5E3d/cfr9j8+yX26++HTVLZ9zBdbeHt3L91gHRiZfwOzXi/hNzCpqrcl+Y7MBsX+xXxBiqW2ZiGORyRZqoU45lNMDnX3r29VLVx+wjKXUlU7kvx1km9kNqdwMhu1fEhmS9ou6yC/i1XVrZOc3t23mLqWKRjIdUlV9f2ZzQiSJG/t7g/u7XyWQ1XdKsljk/xEkvcmefGy9mdPkqo6LLP3iQuq6ibd/cmpa4J9ISwzVFVHJ7ntfPOc7n7TlPVMac1X7jX/+bnMBkG+aq+/eJAykGtVVf1iZqs5rnQ1+LEkJ3f386erahpVdbUkj0vyfZl1V0qylH37LzZf3vrBSf5vki9n9h7yv5epa4qFOFZ5jRyYhGXgcquqdyzTCnV7Mx/k+F+7+8L59jWSvGsZ5yOvqlck+XBmyzo/M8lxSf6pu39x0sImUFW3y+yq8rGZDf58UXe/f77C47u6e2mWOLYQxyqvkQOTsAz7YGUOzHXOT/LJ7l66CeXnyxtfPwZyZb54zw9099fm21dL8r7uPmrayrbempUuP9jdt6uqqyZ5W3ffderatlpVvSXJizJb+vyr6449urtfuvFvHnxWnhfr9i3lVJNeIwcms2HAvvmDJHdMsjJt2lFJPpTk8Kr62e5+3ZTFTeCwJF/JbG7hFZ3VrgjL5MVJ3jOfVzeZfeX+ounKmdQ35z+/VFW3zay70ndNWM9kuvueezm2NEF5zkIcq7xGDkCuLMM+qKq/SvIr3X3OfPs2mX2F9stJ/qq7bz9heUygqo7o7n+b375jkrvPD70tyQ27+9XDXz5IzWfMeVVmf0y+JMmhmb1u/mjKurZSVb28ux82/8Zh7QfsyiDYZex6YCGOOa+RA5OwDPugqj7U3bfdaF9VnbVsYdkglaSqPpzkmPXL9lbVTyd5WnfffJLCJrD2D4cNjt1/mf5wqKobdPdnq2rDPslmgFhOXiMHNt0wYN+cU1V/mNmyrcnsa8R/rKrvyOrXasvkpZkNUvnRrBmkMmlFW+/JSV5XVcd290eTpKpOzKwthl/BH6ReX1Ub/eHw2CRPzyUX9Tmodfdn5z+XPhRbiOMSvEYOYMIy7Jvjk/xckl+ab78jyf/ILCgv4/Klt+jun6iqB3X3KVX1F5l1P1ga3f2aqvp6kv+vqh6c5PFJ7pzkHt39n5MWt/U2+sPhqZmN+F+qPxz2srJjkmTJ5iK/5tQFbCNeIwcwYRn2QXd/taqen+R1mX0QfqS7V64o75musskYpJKku984vzK0O8k7k9xrZVaMZeIPh1Xdfc0kqarfSPLZzL6Fqcy+cbjBhKVtOavSrfIaObDpswz7oKp2JTklybmZffAdkeQx3f3W6aqajkEql1qoZqU7zreyxKsZVtUPZbb65zuTPGwZ/3BYUVX/0N3ff1n7loExDqu8Rg5MrizDvnlukh/p7o8kFy9j+7Ikd5q0qi22Mkilu1843/XWJDebH7v/dJVtvZUriGz4h8O9k3y+qpb2D4ckF1bVcZmNc+gkj0xy4bQlTWbpxzh4jRzYXFmGfbAygfxl7TvY7WUGiMcmefoyzQABe1NVRyb5vSR3yywkvSPJL61/7SwDC3FwoHNlGfbNGVX1wiR/Nt9+VJIzJqxnKgapwGWoqisneWJ3P2jqWrYJYxw4oAnLsG9+NsnPJ3nSfPttma3qt1QMUoHL1t3fqqq7X/aZS+Pkqrp2ZlOknZb5GIdpS4J9pxsG7EVVPSjJjbr79+fb701yvcy+Vv3l7n7llPVNxSAV2Lv5vOw3TPKKrOmr3N1LsyS8hTg4WAjLsBdV9Y4kj1izrPFZSe6V2ZWRF3f3vScsb8uZAQL2TVW9eIPdvUwzQBjjwMFCNwzYu0PWXRl5e3d/MckXq+oaUxU1FTNAwL7p7sdOXcM2YIwDBwVhGfbu2ms3uvuJazavt8W1AAcIcwsb48DB40pTFwDb3Huq6mfW76yq/5bkvRPUAxwYXprk+pnNLfyWJDdKcsGkFU2gu9+YZGWVy5tltsqloMwBRZ9l2Iuq+q4kf5Pk60neP999p8z66z64u8+bqDRgGzO3sDEOHDx0w4C96O7PJ/nBqrpXZl+nJsnp3f2mCcsCtr+ln1vYGAcOFq4sA8Amq6rHJ3lVkqOSvCTzuYW7+4+mrAu4/IRlANhkVXWd+cw5a/fdtLs/MVVNwP4xwA8ANt/fVdXFfXKr6nuT/N2E9QD7SVgGgM337MwC86FVdackr0zyqIlrAvaDAX4AsMm6+/T5DBivS3LNJD/W3f88cVnAftBnGQA2SVU9P7Pp0lbcO8m/JDk3Sbr7FyYoC1iAK8sAsHnOWLd95iRVAJvGlWUAuAJU1SFJbjXf/Eh3f3Nv5wPbk7AMAJusqnYlOSWz7heV5Igkj+nut05XFbA/hGUA2GRVdWaSn+zuj8y3b5XkZd19p2krAy4vU8cBwOa76kpQTpL5TBhXnbAeYD8Z4AcAm+/Mqnphkj+bbx+XSw/+Aw4AumEAwCarqu9I8vNJ7j7f9bYkf9DdX5+uKmB/CMsAsImq6spJzunu75m6FmBx+iwDwCbq7m8l+UhV3XjqWoDF6bMMAJvv2knOqar3JrlwZWd3P3C6koD9ISwDwOb7lakLADaHsAwAm+9+3f2/1u6oquckectE9QD7SZ9lANh899lg3323vApgYa4sA8AmqaqfTfJzSW5eVR9cc+iaSd45TVXAIkwdBwCbpKoOz2xw328mOXHNoQu6+4vTVAUsQjcMANgk3X1+d5+b5A3d/ck1/75YVSdNXR9w+emGAQCb7yFV9bXu/vMkqarfT3K1iWsC9oOwDACb7yFJTquqbyc5JsmXuvtxE9cE7Ad9lgFgk1TVddZsXjPJ3yR5R5JnJIl+y3DgEZYBYJNU1SeSdJJa83NFd/fNJikM2G/CMgAADJgNAwA2WVV9Z1U9vapOnm/fsqruP3VdwOUnLAPA5ntxkm8k+cH59qeTPGu6coD9JSwDwOa7eXf/VpJvJkl3fyWX7L8MHCCEZQDYfN+oqqtnNsgvVXXzJF+ftiRgf5hnGQA2368m+fskR1TVnye5W5LjJ60I2C9mwwCAK0BV/Zckd82s+8W7u/sLE5cE7AdhGQA2SVXdcW/Hu/v9W1ULsDmEZQDYJFX15r0c7u6+15YVA2wKYRkAAAbMhgEAm6SqfnnN7Z9Yd+zZW18RsChhGQA2zyPW3H7qumPHbGUhwOYQlgFg89Tg9kbbwAFAWAaAzdOD2xttAwcAA/wAYJNU1beSXJjZVeSrJ/nKyqEkV+vuq05VG7B/hGUAABjQDQMAAAaEZQAAGBCWAQBgQFgGAICB/x8+vdM9u97OuQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# splitting data - Hangi sutunlarin verileri 1 ve 0 tarafinda etkiledigini goruyoruz.\n",
    "X = df.drop(\"Sonuc\", axis =1)\n",
    "Y = df[\"Sonuc\"]\n",
    "X.corrwith(df.Sonuc).plot(kind='bar',\n",
    "                           grid=True, \n",
    "                           figsize=(12, 8),\n",
    "                           title=\"Sonuc Iliskisi\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 460,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,9))\n",
    "sns.heatmap(df.corr(),cmap='Blues',annot=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 461,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([df[df.Sonuc==0].KanBasinci, df[df.Sonuc==1].KanBasinci], bins = 20, alpha = 0.5, label = [\"Kalp Hastaligi Yok\",\"Kalp Hastaligi Var\"])\n",
    "plt.xlabel(\"KanBasinci\")\n",
    "plt.ylabel(\"YuzdeOrani(%)\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([df[df.Sonuc==0].KalpAtisHizi, df[df.Sonuc==1].KalpAtisHizi], bins = 20, alpha = 0.5, label = [\"Kalp Hastaligi Yok\",\"Kalp Hastaligi Var\"])\n",
    "plt.xlabel(\"KalpAtisHizi\")\n",
    "plt.ylabel(\"YuzdeOrani(%)\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 463,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([df[df.Sonuc==0].GogusAgrisi, df[df.Sonuc==1].GogusAgrisi], bins = 20, alpha = 0.5, label = [\"Kalp Hastaligi Yok\",\"Kalp Hastaligi Var\"])\n",
    "plt.xlabel(\"GogusAgrisi\")\n",
    "plt.ylabel(\"YuzdeOrani(%)\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 464,
   "metadata": {},
   "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>Yas</th>\n",
       "      <th>Cinsiyet</th>\n",
       "      <th>GogusAgrisi</th>\n",
       "      <th>KanBasinci</th>\n",
       "      <th>Kolesterol</th>\n",
       "      <th>KanSekeri</th>\n",
       "      <th>Elektrokardiyografik</th>\n",
       "      <th>KalpAtisHizi</th>\n",
       "      <th>KalpAgrisi</th>\n",
       "      <th>ST</th>\n",
       "      <th>Sonuc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>144</td>\n",
       "      <td>235</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>132</td>\n",
       "      <td>260</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>132</td>\n",
       "      <td>211</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>169</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>235</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>177</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>357</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>162</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Yas  Cinsiyet  GogusAgrisi  KanBasinci  Kolesterol  KanSekeri  \\\n",
       "0   63         1            3         144         235          1   \n",
       "1   35         1            2         132         260          0   \n",
       "2   41         0            1         132         211          0   \n",
       "3   54         1            1         120         235          0   \n",
       "4   57         0            0         120         357          0   \n",
       "\n",
       "   Elektrokardiyografik  KalpAtisHizi  KalpAgrisi   ST  Sonuc  \n",
       "0                     0           147           0  2.3      1  \n",
       "1                     1           184           0  3.5      1  \n",
       "2                     0           169           0  1.4      1  \n",
       "3                     1           177           0  0.9      1  \n",
       "4                     1           162           1  0.5      1  "
      ]
     },
     "execution_count": 464,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 465,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([df[df.Sonuc==0].Cinsiyet, df[df.Sonuc==1].Cinsiyet], bins = 20, alpha = 0.5, label = [\"Kalp Hastaligi Yok\",\"Kalp Hastaligi Var\"])\n",
    "plt.xlabel(\"Cinsiyet\")\n",
    "plt.ylabel(\"YuzdeOrani(%)\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([df[df.Sonuc==0].Yas, df[df.Sonuc==1].Yas], bins = 20, alpha = 0.5, label = [\"Kalp Hastaligi Yok\",\"Kalp Hastaligi Var\"])\n",
    "plt.xlabel(\"Yas\")\n",
    "plt.ylabel(\"YuzdeOrani(%)\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEGCAYAAABiq/5QAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAAsTAAALEwEAmpwYAAAeTklEQVR4nO3de5QU1bn38e8PgiJCQGVUjigQY7wcQPQMl2hA8BKMxwtGohAVjAb0APHuGzWuJRoTLzFhxZiIerygkighQQx4NLw6BDxvVG6jgCaiUY94iCCRESQYLs/7R9dMxmEuPTDVzUz9Pmv16u5dtbuePTXr6epdu3YpIjAzs+xoVewAzMyssJz4zcwyxonfzCxjnPjNzDLGid/MLGM+V+wA8tG5c+fo3r17scMwM2tWFi1a9GFElNQsbxaJv3v37ixcuLDYYZiZNSuS3q2t3F09ZmYZ48RvZpYxTvxmZhnTLPr4zazxNm/ezMqVK9m0aVOxQ7GUtW3blq5du9KmTZu81nfiN2uhVq5cSYcOHejevTuSih2OpSQiWLt2LStXrqRHjx551XFXj1kLtWnTJvbZZx8n/RZOEvvss0+jftk58Zu1YE762dDY/ezEb2aWMe7jN8uISXPeaNLPu+KkLzW4Tvv27dmwYQMATz/9NJdffjlz5syhW7duta4/ceJE2rdvz9VXX51XDHPnzuXOO+9k1qxZVWUXXHABp556KsOHD8/rM6p/1m677cYxxxxT73oPP/wwCxcu5O6772by5Mm0a9eOUaNG1bn+woULeeSRR7jrrruqylavXk2/fv148cUX2X///QEYP348Xbt25brrrtvuMwYPHsydd95JaWlpo9pUFyd+K5yyW2svH7L9P7q1LM899xyXXnopzz77bJ1Jv9jmzp1L+/btG0z81V1yySUNrlNaWrpdwt5333259tprufrqq3nsscdYvHgx8+fPZ9GiRY2Oe0e4q8fMUjVv3jzGjBnDrFmzOPjggwG4//776du3L0ceeSRnnXUWGzdu3K7e4MGDueyyy+jTpw89e/bk5ZdfbvS2b775Zvr27UvPnj0ZO3YslXccvOuuuzjiiCPo3bs3I0aM4J133mHy5MlMmjSJPn36MH/+fH73u9/Rv39/jjrqKE488UQ++OCD7T5/4sSJ3HnnnQAsWLCA3r1706dPH6655hp69uwJ5L5QTj311O3qjh07lrfeeouysjLGjx/P3XffzfLlyxkwYAC9e/fmzDPP5KOPPvpMnW3btnHBBRdwww03NPpvUZ0Tv5ml5tNPP2XYsGE8+eSTHHbYYVXlX//611mwYAGvvPIKhx9+OA888ECt9Tdu3Eh5eTm/+MUvuPDCC2tdZ/78+fTp06fq8dRTT1UtmzBhAgsWLGDZsmX8/e9/r+oSuu2221iyZAmvvvoqkydPpnv37lxyySVcccUVlJeXM3DgQL7yla/w4osvsmTJEkaMGMEdd9xRb1u/9a1vce+991JeXk7r1q0b/Nu0atWKe+65h7POOotDDz2UQYMGMWrUKG6//XZeffVVevXqxU033VS1/pYtWzj33HM55JBDuOWWWxr8/Hq3vVO1zczq0aZNG4455pjtEvuyZcsYOHAgvXr1YurUqSxfvrzW+iNHjgRg0KBBfPzxx6xbt267dQYOHEh5eXnV4/TTT69aVlZWRv/+/enVqxfPP/981XZ69+7Nueeey2OPPcbnPld7j/fKlSsZOnQovXr14kc/+lGdMQKsW7eO9evX8+UvfxmAb37zm3X/Uaqp/DUzbtw4KioqWLduHccddxwAo0ePZt68eVXrXnzxxfTs2ZPvfe97eX12fZz4zSw1rVq1Ytq0abz88sv88Ic/rCq/4IILuPvuu1m6dCk33nhjnWPQaw5TbMywxU2bNjFu3DimT5/O0qVLGTNmTNV2Zs+ezfjx41m8eDF9+/Zly5Yt29X/zne+w4QJE1i6dCn33ntvaldAt2rVilatGk7FxxxzDGVlZU0ShxO/tXxlt9b+sIJo164ds2fPZurUqVVH/uvXr6dLly5s3ryZqVOn1ln3iSeeAOCFF16gY8eOdOzYMe/tVibIzp07s2HDBqZPnw7k+snfe+89hgwZwu23305FRQUbNmygQ4cOrF+/vqp+RUUFBxxwAABTpkypd1udOnWiQ4cOvPTSSwA8/vjjecdZqWPHjuy1117Mnz8fgEcffbTq6B/goosu4pRTTuHss8+u9YuqMTyqxywj8hl+mZa9996bZ555hkGDBlFSUsL3v/99+vfvT0lJCf379/9Mwq2ubdu2HHXUUWzevJkHH3ywUdvs1KkTY8aMoWfPnuy///707dsXgK1bt3LeeedRUVFBRHDppZfSqVMnTjvtNIYPH87MmTP52c9+xsSJE/nGN77BXnvtxfHHH8/bb79d7/YeeOABxowZQ6tWrTjuuOMa9SVVacqUKVxyySVs3LiRL3zhCzz00EOfWX7llVdSUVHB+eefz9SpU/P6pVAbVZ7l3pWVlpaGb8TSAhRrOGdGh5G+/vrrHH744cUOY4c19dj1tG3YsIH27dsDuZPHq1at4qc//WnBtl/b/pa0KCK2+wOmdsQvqS0wD9g92c70iLhR0sPAcUBFsuoFEVGeVhxmZoUwe/Zsbr31VrZs2UK3bt14+OGHix1SndLs6vkUOD4iNkhqA7wg6b+SZddExPQUt21mzdzcuXOLHUKjnHPOOZxzzjnFDiMvqSX+yPUhbUjetkkeu36/kplZC5fqqB5JrSWVA6uBORHxUrLoB5JelTRJ0u511B0raaGkhWvWrEkzTDOzTEk18UfE1ojoA3QF+knqCVwHHAb0BfYGvltH3fsiojQiSktKStIM08wsUwoyjj8i1gFlwMkRsSpyPgUeAvoVIgYzM8tJc1RPCbA5ItZJ2gM4CbhdUpeIWKXcJXjDgGVpxWBm1TT1RWt5DIf1tMy1T8u8ceNGDjzwQN5++20+//nPV5UPGzaMkSNHpn6SOM1RPV2AKZJak/tlMS0iZkl6PvlSEFAONDyvqZk1a56W+bND6du1a8fQoUOZMWMGo0ePBnJXCr/wwgv88pe/bPAzI4KI2OELuFLr6omIVyPiqIjoHRE9I+LmpPz4iOiVlJ0XERsa+iwza748LXPt0zKPHDnyM1M7zJgxg6FDh7Jt2zZOOOEEjj76aHr16sXMmTMBeOeddzj00EMZNWoUPXv25L333mv036OS5+oxs9R4Wua6DR06lMWLF7N27VogN7/PyJEjadu2LTNmzGDx4sWUlZVx1VVXVX1hrVixgnHjxrF8+fKd+uXkxG9mqfG0zHXbbbfdOP3005k+fToffvghS5YsYejQoUQE119/Pb179+bEE0/k/fffr/q10a1bNwYMGNDgZzfEid/MUuNpmetX2d0zffp0zjjjDNq0acPUqVNZs2YNixYtory8nP32269q23vuuWeTbNeJ38xS5WmZ6zZ48GBWrFjBz3/+86pfNxUVFey77760adOGsrIy3n333bzbnC9Py2yWFUWcjdTTMteuVatWDB8+nGnTplXNvX/uuedy2mmn0atXL0pLSz9zbqSpeFpmKxxPy1xQnpa5sDwts5lZxnhaZjOzneRpmdPjk7tmLVhz6Mq1ndfY/ezEb9ZCtW3blrVr1zr5t3ARwdq1a2nbtm3eddzVY9ZCde3alZUrV+L7WbR8bdu2pWvXrnmv78Rv1kK1adOGHj16FDsM2wW5q8fMLGOc+M3MMsaJ38wsY5z4zcwyxonfzCxjnPjNzDLGid/MLGNSS/yS2kp6WdIrkpZLuikp7yHpJUlvSnpC0m5pxWBmZttL84j/U+D4iDgS6AOcLGkAcDswKSK+CHwEXJRiDGZmVkNqiT9yNiRv2ySPAI4HpiflU4BhacVgZmbbS7WPX1JrSeXAamAO8BawLiIqb3C5EjigjrpjJS2UtNBzjZiZNZ1UE39EbI2IPkBXoB+Q9z3EIuK+iCiNiNKSkpK0QjQzy5yCjOqJiHVAGfBloJOkysnhugLvFyIGMzPLSXNUT4mkTsnrPYCTgNfJfQEMT1YbDcxMKwYzM9temtMydwGmSGpN7gtmWkTMkvQa8LikW4AlwAMpxmBmZjWklvgj4lXgqFrK/0Kuv9/MzIrAV+6amWWME7+ZWcY48ZuZZYwTv5lZxjjxm5llTJrDOc2s7Nbay4dcV9g4zKrxEb+ZWcY48ZuZZYwTv5lZxjjxm5lljBO/mVnGeFSPtRiT5rxRa/kV/i83+wwf8ZuZZYwTv5lZxjjxm5lljBO/mVnGOPGbmWWME7+ZWcY48ZuZZUxeiV/SvpLOlDRe0oWS+kmqt66kAyWVSXpN0nJJlyXlEyW9L6k8eZzSFA0xM7P81Htpi6QhwLXA3sASYDXQFhgGHCxpOvDjiPi4lupbgKsiYrGkDsAiSXOSZZMi4s4maoOZmTVCQ9c0ngKMiYj/qblA0ueAU4GTgN/UXB4Rq4BVyev1kl4HDtjpiM3MbKfU210TEdfUlvSTZVsi4smI2C7p1ySpO3AU8FJSNEHSq5IelLRXHXXGSlooaeGaNWsa2oSZmeWpUSd3JQ2Q9IykuZLOzLNOe3K/CC5PuoTuAQ4G+pD7RfDj2upFxH0RURoRpSUlJY0J08zM6tFQH//+EfHXakVXAmcCInf0PqOB+m3IJf2pEfFbgIj4oNry+4FZOxa6mZntiIb6+CdLWgzcERGbgHXAcGAbUNsJ3SqSBDwAvB4RP6lW3iXp/4fcl8iyHYzdzMx2QL2JPyKGSToNmCXpEeBy4JtAO3Ije+pzLHA+sFRSeVJ2PTBSUh8ggHeAi3csdDMz2xENzlQeEb+T9DQwjlzXzg8iYl4e9V4g1yVU09ONjtKaTtmttZcPua6wcbQwvheANScNXYR1uqQy4BlyXTLnAGdIelzSwYUI0MzMmlZDxyO3AP2APYBnI6IfcJWkQ4AfACNSjs/MzJpYQ4m/Avg6uT791ZWFEbECJ30zs2apoXH8ZwL7kPuC+Gb64ZiZWdoaOuLfFBE/q28FSe0jYkMTxmRmZilqKPHPTIZizgQWRcQnAJK+AAwBzgbuB6anGaSZ1a3OEUUnfanAkVhz0dA4/hOSaZMvBo6VtDewGfgzMBsYXePKXjMz28XlM47/aTz23sysxWhorp7DIuJPko6ubXlELE4nLDMzS0tDR/xXAmOpfQbNAI5v8ojMzCxVDfXxj02ehxQmHDMzS1veM4lIOgboXr1ORDySQkxmZpaivBK/pEfJ3TylHNiaFAfgxG9m1szke8RfChwREZFmMGZmlr58b724DNg/zUDMzKww8j3i7wy8Jull4NPKwog4PZWozMwsNfkm/olpBmFmZoWTV+KPiD+kHYiZmRVGXn38kgZIWiBpg6R/SNoqqd6brZuZ2a4p35O7dwMjgRXk7sb1beDn9VWQdKCkMkmvSVou6bKkfG9JcyStSJ732pkGmJlZ4+Sb+ImIN4HWEbE1Ih4CTm6gyhbgqog4AhgAjJd0BHAt8FxEHAI8l7w3M7MCyffk7kZJuwHlku4AVtHAl0ZErErWIyLWS3odOAA4AxicrDYFmAt8t9GRm5nZDsn3iP/8ZN0JwCfAgcBZ+W5EUnfgKOAlYL/kSwHgr8B+ddQZK2mhpIVr1qzJd1NmZtaABhO/pNbADyNiU0R8HBE3RcSVSddPgyS1B34DXB4RnzkhnFwJXOvVwBFxX0SURkRpSUlJPpsyM7M8NJj4I2Ir0C3p6mkUSW3IJf2pEfHbpPgDSV2S5V2A1Y39XDMz23H59vH/BfhvSU+R6+oBICJ+UlcFSQIeAF6vsd5TwGjgtuR5ZmODNjOzHZdv4n8rebQCOuRZ51hy5waWJjdsB7ieXMKfJuki4F1yN2w3M7MCyffK3ZuSvnoiYkOedV4AVMfiE/ILz5qbSXPeqHPZFXnf/cHM0pTPyd1xkv6H3NH5u5LelTQu/dDMzCwN9SZ+STcApwKDI2KfiNgHGAJ8LVlmZmbNTENH/OcDX4+Iv1QWJK/PBkalGZiZmaWjocQfEbGplsK/A9vSCcnMzNLUUOJ/X9J2J2IlHU8yHYOZmTUvDY2zuBSYKekFYFFSVkpuqOYZaQZmZmbpaGiiteVAT2Ae0D15zAN6JsvMzKyZaXBkddLH/6CkbsAhEfF/Je0hqUNErE8/RDMza0r53oFrDDAduDcp6go8mVJMZmaWonynZR5Prl//Y4CIWAHsm1ZQZmaWnnwT/6cR8Y/KN5I+Rx3TKZuZ2a4t38T/B0nXA3tIOgn4NfC79MIyM7O05Jv4rwXWAEuBi4GnAU/ZYGbWDOU7O+c24P7kYWZmzVi9iV/SUurpy4+I3k0ekZmZpaqhI/5Tk+fxyfOjyfN5+OSumVmzVG/ij4h3ASSdFBFHVVv0XUmLyfX9m5lZM5LvyV1JOrbam2MaUdfMzHYh+d4M7yJy0zZ0TN6vAy5MJSIzM0tVXkftEbEoIo4EjgSOjIg+EbG4vjqSHpS0WtKyamUTJb0vqTx5nLJz4ZuZWWPlO1fPVkm3AR9HREVSVm/iBx4GTq6lfFLyxdEnIp5uVLRmZrbT8u2nX56s+3tJeydlqq9CRMwD/rYTsZmZWQry7ePfEhH/R9I5wHxJo9jx4ZwTkvoLgasi4qPaVpI0FhgLcNBBB+3gpsysKMpurb18yHWFjcNqlfeoHoCIeAI4B3gI+MIObO8e4GCgD7lbN/64rhUj4r6IKI2I0pKSkh3YlJmZ1SbfI/5vV76IiGWSBrIDt16MiA8qX0u6H5jV2M8wM7Odk2/i/1dJ/7qzG5PUJSIqb9J+JrCsvvXNzKzp5Zv4+1Z73RY4AVgMPFJXBUm/AgYDnSWtBG4EBkvqQ+78wDvkZvo0M7MCynd2zu9Ufy+pE/B4A3VG1lL8QN6RmZlZKnZ02oVPgB5NGYiZmRVGQ9MyP01uZs67+OfwzdbA4eTuwmVmZs1MQ109DwHPAlOAl4F/AFuAdyNiZcqxmZlZCurt6omIXwNHA58H7iR3krc/cLakK9MPz8zMmlo+J3f/Qa5Pf3egA7At1YjMzCxVDfXxnwz8BHgKODoiNhYkKjMzS01DR/zfA74REcsLEYyZmaWvoVsvDixUIGZmVhi+faKZWcY48ZuZZYwTv5lZxuQ7SZs1M5PmvFFr+RXe49ZE6vofA/+f7ep8xG9mljFO/GZmGePEb2aWMU78ZmYZ48RvZpYxTvxmZhnjxG9mljGpJX5JD0paLWlZtbK9Jc2RtCJ53iut7ZuZWe3SPOJ/GDi5Rtm1wHMRcQjwXPLezMwKKLXEHxHzgL/VKD6D3G0cSZ6HpbV9MzOrXaEvrN4vIlYlr/8K7FfXipLGAmMBDjrooAKEZtbClN1ae/mQ6wobh+1yinZyNyICiHqW3xcRpRFRWlJSUsDIzMxatkIn/g8kdQFInlcXePtmZplX6MT/FDA6eT0amFng7ZuZZV6awzl/BfwROFTSSkkXAbcBJ0laAZyYvDczswJK7eRuRIysY9EJaW3TzMwa5it3zcwyxonfzCxjnPjNzDLGid/MLGOc+M3MMsaJ38wsY5z4zcwyxonfzCxjnPjNzDLGid/MLGOc+M3MMqbQN2IxM9tpk+a8UWv5FSd9qcCRNE8+4jczyxgnfjOzjHHiNzPLGCd+M7OMceI3M8sYJ34zs4xx4jczy5iijOOX9A6wHtgKbImI0mLEYWaWRcW8gGtIRHxYxO2bmWWSu3rMzDKmWEf8AfxeUgD3RsR9NVeQNBYYC3DQQQcVOLym4cvKzWxXVKwj/q9ExNHA14DxkgbVXCEi7ouI0ogoLSkpKXyEZmYtVFESf0S8nzyvBmYA/YoRh5lZFhU88UvaU1KHytfAV4FlhY7DzCyritHHvx8wQ1Ll9n8ZEc8UIQ4zs0wqeOKPiL8ARxZ6u2aWAWW31l4+5LrCxrGL83BOM7OMceI3M8sYJ34zs4xx4jczyxgnfjOzjCnmJG3FVcyz/x55YGZF5CN+M7OMceI3M8sYJ34zs4xx4jczyxgnfjOzjGnxo3rqvBlKi2+5NVbd/yu/qb2CR2FZdc1otJ6P+M3MMsaJ38wsY5z4zcwyxonfzCxjfIrTzKwRUhkwUteJYUjl5LCP+M3MMsaJ38wsY4qS+CWdLOnPkt6UdG0xYjAzy6qCJ35JrYGfA18DjgBGSjqi0HGYmWVVMY74+wFvRsRfIuIfwOPAGUWIw8wskxQRhd2gNBw4OSK+nbw/H+gfERNqrDcWGJu8PRT4c0ED3TGdgQ+LHUQBZa29kL02u73NW7eIKKlZuMsO54yI+4D7ih1HY0haGBGlxY6jULLWXshem93elqkYXT3vAwdWe981KTMzswIoRuJfABwiqYek3YARwFNFiMPMLJMK3tUTEVskTQCeBVoDD0bE8kLHkZJm1TXVBLLWXshem93eFqjgJ3fNzKy4fOWumVnGOPGbmWWME38jSHpQ0mpJy6qVTZT0vqTy5HFKtWXXJdNS/FnS0OJEveMkHSipTNJrkpZLuiwp31vSHEkrkue9knJJuitp86uSji5uCxqnnva2yH0sqa2klyW9krT3pqS8h6SXknY9kQzCQNLuyfs3k+Xdi9qARqqnvQ9Lerva/u2TlDfr/+d6RYQfeT6AQcDRwLJqZROBq2tZ9wjgFWB3oAfwFtC62G1oZHu7AEcnrzsAbyTtugO4Nim/Frg9eX0K8F+AgAHAS8VuQxO1t0Xu42Q/tU9etwFeSvbbNGBEUj4Z+I/k9ThgcvJ6BPBEsdvQRO19GBhey/rN+v+5voeP+BshIuYBf8tz9TOAxyPi04h4G3iT3HQVzUZErIqIxcnr9cDrwAHk2jYlWW0KMCx5fQbwSOS8CHSS1KWwUe+4etpbl2a9j5P9tCF52yZ5BHA8MD0pr7l/K/f7dOAESSpMtDuvnvbWpVn/P9fHib9pTEh+Cj5Y2e1BLmG8V22dldSfRHZpyc/6o8gdJe0XEauSRX8F9ktet5g212gvtNB9LKm1pHJgNTCH3K+WdRGxJVmlepuq2pssrwD2KWjAO6lmeyOicv/+INm/kyTtnpQ1+/1bFyf+nXcPcDDQB1gF/Lio0aRAUnvgN8DlEfFx9WWR+03cosYE19LeFruPI2JrRPQhdwV9P+Cw4kaUrprtldQTuI5cu/sCewPfLV6EheHEv5Mi4oPkn2kbcD///KnfIqamkNSGXBKcGhG/TYo/qPzJmzyvTsqbfZtra29L38cAEbEOKAO+TK5Lo/LizuptqmpvsrwjsLawkTaNau09Oenii4j4FHiIFrh/a3Li30k1+vzOBCpH/DwFjEhGQvQADgFeLnR8OyPpv30AeD0iflJt0VPA6OT1aGBmtfJRyWiIAUBFtS6hXV5d7W2p+1hSiaROyes9gJPIndcoA4Ynq9Xcv5X7fTjwfPKLr1moo71/qnYQI3LnM6rv32b7/1yfXXZ2zl2RpF8Bg4HOklYCNwKDk+FfAbwDXAwQEcslTQNeA7YA4yNiaxHC3hnHAucDS5N+UYDrgduAaZIuAt4Fzk6WPU1uJMSbwEbgWwWNdufV1d6RLXQfdwGmKHdzpFbAtIiYJek14HFJtwBLyH0Zkjw/KulNcoMcRhQj6J1QV3ufl1RCbvROOXBJsn5z/3+uk6dsMDPLGHf1mJlljBO/mVnGOPGbmWWME7+ZWcY48ZuZZYwTv7V4kjZUe32KpDckdctn/UZu53JJ7Xakbh2f946kzk31eWaVnPgtMySdANwFfC0i3k1hE5cDjUr8yZhys4Jy4rdMkDSI3HQLp0bEW0nZlZKWJY/L66h3jaQFyQRelfO37ylpdjKv+zJJ50i6FPgXoExSWbLeVyX9UdJiSb9O5gCqPJK/XdJi4BuSRkpamnzW7en/NSzrfOWuZcHuwJPA4Ij4E4CkfyN3JWZ/cldsviTpDxGxpLKSpK+Sm4ahX7LOU8kXSAnwvxHx78l6HSOiQtKVwJCI+DDporkBODEiPpH0XeBK4Obk49dGxNGS/gV4Efg34CPg95KGRcSTaf5BLNt8xG9ZsBn4f8BF1cq+AsyIiE+SOdp/CwysUe+ryWMJsJjcDI6HAEuBk5Kj9oERUVHLNgeQu1HLfyfTP4wGqp9XeCJ57gvMjYg1yVTHU8nd8McsNT7ityzYRm4+oeckXR8RP8yznoBbI+Le7RbkbsN3CnCLpOci4uZa6s6JiJF1fPYnecZg1uR8xG+ZEBEbgX8Hzk0ml5sPDJPUTtKe5GbdnF+j2rPAhdX65g+QtG/SPbMxIh4DfkTudpwA68ndshFy3TfHSvpiUndPSV+qJbSXgeMkdU5O9I4E/tBEzTarlY/4LTMi4m+STgbmAZeRu9dq5TTK/1m9fz9Z//eSDgf+mJuxlw3AecAXgR9J2kauG+k/kir3Ac9I+t+IGCLpAuBX+ucdnW4gdx/f6ttYJelaclMhC5gdETMxS5Fn5zQzyxh39ZiZZYwTv5lZxjjxm5lljBO/mVnGOPGbmWWME7+ZWcY48ZuZZcz/BxP/6LJsDFceAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([df[df.Sonuc==0].Kolesterol, df[df.Sonuc==1].Kolesterol], bins = 20, alpha = 0.5, label = [\"Kalp Hastaligi Yok\",\"Kalp Hastaligi Var\"])\n",
    "plt.xlabel(\"Kolesterol\")\n",
    "plt.ylabel(\"YuzdeOrani(%)\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([df[df.Sonuc==0].KanSekeri, df[df.Sonuc==1].KanSekeri], bins = 20, alpha = 0.5, label = [\"Kalp Hastaligi Yok\",\"Kalp Hastaligi Var\"])\n",
    "plt.xlabel(\"KanSekeri\")\n",
    "plt.ylabel(\"YuzdeOrani(%)\")\n",
    "plt.legend()\n",
    "plt.show() # 0 : <120 , 1 : > 120"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Machine Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 489,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lightgbm import LGBMClassifier\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV,cross_val_score\n",
    "from sklearn.metrics import mean_squared_error, confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 471,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop([\"Sonuc\"], axis = 1)\n",
    "y = df.Sonuc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 472,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 474,
   "metadata": {},
   "outputs": [],
   "source": [
    "lgbm_model = LGBMClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 475,
   "metadata": {},
   "outputs": [],
   "source": [
    "lgbm_params = {\"learning_rate\" : [0.001, 0.1, 0.01],\n",
    "              \"n_estimators\" : [200, 500, 100, 800],\n",
    "              \"max_depth\" : [1, 2, 3, 5, 8],\n",
    "              \"random_state\" : np.arange(1,50,5),\n",
    "              \"boosting_type\" : [\"gbdt\", \"dart\", \"goss\", \"rf\"],\n",
    "              \"max_leaves\" : np.arange(1,40)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 93600 candidates, totalling 280800 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 8 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done  25 tasks      | elapsed:    2.7s\n",
      "[Parallel(n_jobs=-1)]: Done 288 tasks      | elapsed:    6.1s\n",
      "[Parallel(n_jobs=-1)]: Done 1100 tasks      | elapsed:   14.5s\n",
      "[Parallel(n_jobs=-1)]: Done 2232 tasks      | elapsed:   27.2s\n",
      "[Parallel(n_jobs=-1)]: Done 3692 tasks      | elapsed:   46.3s\n",
      "[Parallel(n_jobs=-1)]: Done 5472 tasks      | elapsed:  1.1min\n",
      "[Parallel(n_jobs=-1)]: Done 7580 tasks      | elapsed:  1.7min\n",
      "[Parallel(n_jobs=-1)]: Done 10008 tasks      | elapsed:  2.3min\n",
      "[Parallel(n_jobs=-1)]: Done 12764 tasks      | elapsed:  3.0min\n",
      "[Parallel(n_jobs=-1)]: Done 15840 tasks      | elapsed:  3.9min\n",
      "[Parallel(n_jobs=-1)]: Done 19244 tasks      | elapsed:  4.9min\n",
      "[Parallel(n_jobs=-1)]: Done 22968 tasks      | elapsed:  5.9min\n",
      "[Parallel(n_jobs=-1)]: Done 27020 tasks      | elapsed:  6.7min\n",
      "[Parallel(n_jobs=-1)]: Done 31392 tasks      | elapsed:  7.6min\n",
      "[Parallel(n_jobs=-1)]: Done 36092 tasks      | elapsed:  8.8min\n",
      "[Parallel(n_jobs=-1)]: Done 41112 tasks      | elapsed: 10.2min\n",
      "[Parallel(n_jobs=-1)]: Done 46460 tasks      | elapsed: 11.8min\n",
      "[Parallel(n_jobs=-1)]: Done 52128 tasks      | elapsed: 12.9min\n",
      "[Parallel(n_jobs=-1)]: Done 58124 tasks      | elapsed: 14.3min\n",
      "[Parallel(n_jobs=-1)]: Done 64440 tasks      | elapsed: 16.0min\n",
      "[Parallel(n_jobs=-1)]: Done 71084 tasks      | elapsed: 18.0min\n",
      "[Parallel(n_jobs=-1)]: Done 76500 tasks      | elapsed: 19.8min\n",
      "[Parallel(n_jobs=-1)]: Done 80225 tasks      | elapsed: 21.3min\n",
      "[Parallel(n_jobs=-1)]: Done 83834 tasks      | elapsed: 23.1min\n",
      "[Parallel(n_jobs=-1)]: Done 87618 tasks      | elapsed: 25.1min\n",
      "[Parallel(n_jobs=-1)]: Done 91378 tasks      | elapsed: 27.0min\n",
      "[Parallel(n_jobs=-1)]: Done 96820 tasks      | elapsed: 29.1min\n",
      "[Parallel(n_jobs=-1)]: Done 102136 tasks      | elapsed: 31.3min\n",
      "[Parallel(n_jobs=-1)]: Done 106018 tasks      | elapsed: 33.4min\n",
      "[Parallel(n_jobs=-1)]: Done 109850 tasks      | elapsed: 35.7min\n",
      "[Parallel(n_jobs=-1)]: Done 113450 tasks      | elapsed: 37.9min\n",
      "[Parallel(n_jobs=-1)]: Done 117472 tasks      | elapsed: 40.2min\n",
      "[Parallel(n_jobs=-1)]: Done 124995 tasks      | elapsed: 43.0min\n",
      "[Parallel(n_jobs=-1)]: Done 129508 tasks      | elapsed: 45.5min\n",
      "[Parallel(n_jobs=-1)]: Done 134149 tasks      | elapsed: 48.1min\n",
      "[Parallel(n_jobs=-1)]: Done 139384 tasks      | elapsed: 51.0min\n",
      "[Parallel(n_jobs=-1)]: Done 151180 tasks      | elapsed: 54.0min\n",
      "[Parallel(n_jobs=-1)]: Done 162408 tasks      | elapsed: 57.3min\n",
      "[Parallel(n_jobs=-1)]: Done 174884 tasks      | elapsed: 59.8min\n",
      "[Parallel(n_jobs=-1)]: Done 187680 tasks      | elapsed: 62.3min\n",
      "[Parallel(n_jobs=-1)]: Done 200804 tasks      | elapsed: 65.3min\n",
      "[Parallel(n_jobs=-1)]: Done 223328 tasks      | elapsed: 68.2min\n",
      "[Parallel(n_jobs=-1)]: Done 278416 tasks      | elapsed: 70.4min\n",
      "[Parallel(n_jobs=-1)]: Done 280800 out of 280800 | elapsed: 70.4min finished\n"
     ]
    }
   ],
   "source": [
    "lgbm_cv = GridSearchCV(lgbm_model, lgbm_params, cv = 3, verbose = 2, n_jobs = -1).fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'boosting_type': 'goss',\n",
       " 'learning_rate': 0.1,\n",
       " 'max_depth': 1,\n",
       " 'max_leaves': 1,\n",
       " 'n_estimators': 200,\n",
       " 'random_state': 31}"
      ]
     },
     "execution_count": 480,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lgbm_cv.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "metadata": {},
   "outputs": [],
   "source": [
    "tuned = LGBMClassifier(learning_rate = 0.1, max_depth = 1, n_estimators = 200, random_state = 31, boosting_type = \"goss\", max_leaves = 1).fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 482,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = tuned.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 483,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.46188021535170065"
      ]
     },
     "execution_count": 483,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(mean_squared_error(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 485,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0], dtype=int64)"
      ]
     },
     "execution_count": 485,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tuned.predict(X_test)[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 486,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "221    0\n",
      "139    1\n",
      "237    0\n",
      "175    0\n",
      "231    0\n",
      "Name: Sonuc, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(y_test[0:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 487,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train score :  0.8392857142857143\n",
      "\n",
      "Test score :  0.7866666666666666\n"
     ]
    }
   ],
   "source": [
    "print(\"Train score : \", tuned.score(X_train, y_train))\n",
    "print(\"\\nTest score : \", tuned.score(X_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 490,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[28, 11],\n",
       "       [ 5, 31]], dtype=int64)"
      ]
     },
     "execution_count": 490,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confusion_matrix(y_test, y_pred)"
   ]
  }
 ],
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