week4_homework_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".. _boston_dataset:\n",
      "\n",
      "Boston house prices dataset\n",
      "---------------------------\n",
      "\n",
      "**Data Set Characteristics:**  \n",
      "\n",
      "    :Number of Instances: 506 \n",
      "\n",
      "    :Number of Attributes: 13 numeric/categorical predictive. Median Value (attribute 14) is usually the target.\n",
      "\n",
      "    :Attribute Information (in order):\n",
      "        - CRIM     per capita crime rate by town\n",
      "        - ZN       proportion of residential land zoned for lots over 25,000 sq.ft.\n",
      "        - INDUS    proportion of non-retail business acres per town\n",
      "        - CHAS     Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n",
      "        - NOX      nitric oxides concentration (parts per 10 million)\n",
      "        - RM       average number of rooms per dwelling\n",
      "        - AGE      proportion of owner-occupied units built prior to 1940\n",
      "        - DIS      weighted distances to five Boston employment centres\n",
      "        - RAD      index of accessibility to radial highways\n",
      "        - TAX      full-value property-tax rate per $10,000\n",
      "        - PTRATIO  pupil-teacher ratio by town\n",
      "        - B        1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town\n",
      "        - LSTAT    % lower status of the population\n",
      "        - MEDV     Median value of owner-occupied homes in $1000's\n",
      "\n",
      "    :Missing Attribute Values: None\n",
      "\n",
      "    :Creator: Harrison, D. and Rubinfeld, D.L.\n",
      "\n",
      "This is a copy of UCI ML housing dataset.\n",
      "https://archive.ics.uci.edu/ml/machine-learning-databases/housing/\n",
      "\n",
      "\n",
      "This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.\n",
      "\n",
      "The Boston house-price data of Harrison, D. and Rubinfeld, D.L. 'Hedonic\n",
      "prices and the demand for clean air', J. Environ. Economics & Management,\n",
      "vol.5, 81-102, 1978.   Used in Belsley, Kuh & Welsch, 'Regression diagnostics\n",
      "...', Wiley, 1980.   N.B. Various transformations are used in the table on\n",
      "pages 244-261 of the latter.\n",
      "\n",
      "The Boston house-price data has been used in many machine learning papers that address regression\n",
      "problems.   \n",
      "     \n",
      ".. topic:: References\n",
      "\n",
      "   - Belsley, Kuh & Welsch, 'Regression diagnostics: Identifying Influential Data and Sources of Collinearity', Wiley, 1980. 244-261.\n",
      "   - Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning. In Proceedings on the Tenth International Conference of Machine Learning, 236-243, University of Massachusetts, Amherst. Morgan Kaufmann.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.datasets import load_boston\n",
    "\n",
    "raw_data = load_boston()\n",
    "print(raw_data.DESCR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "scrolled": true
   },
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>PRICE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00632</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.0900</td>\n",
       "      <td>1.0</td>\n",
       "      <td>296.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>396.90</td>\n",
       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02731</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02729</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.06263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.593</td>\n",
       "      <td>69.1</td>\n",
       "      <td>2.4786</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>391.99</td>\n",
       "      <td>9.67</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>0.04527</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.120</td>\n",
       "      <td>76.7</td>\n",
       "      <td>2.2875</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.08</td>\n",
       "      <td>20.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>0.06076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.976</td>\n",
       "      <td>91.0</td>\n",
       "      <td>2.1675</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.64</td>\n",
       "      <td>23.9</td>\n",
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       "      <td>0.10959</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.794</td>\n",
       "      <td>89.3</td>\n",
       "      <td>2.3889</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>393.45</td>\n",
       "      <td>6.48</td>\n",
       "      <td>22.0</td>\n",
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       "      <th>505</th>\n",
       "      <td>0.04741</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.030</td>\n",
       "      <td>80.8</td>\n",
       "      <td>2.5050</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>7.88</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>506 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
       "0    0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0   \n",
       "1    0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0   \n",
       "2    0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0   \n",
       "3    0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0   \n",
       "4    0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0   \n",
       "..       ...   ...    ...   ...    ...    ...   ...     ...  ...    ...   \n",
       "501  0.06263   0.0  11.93   0.0  0.573  6.593  69.1  2.4786  1.0  273.0   \n",
       "502  0.04527   0.0  11.93   0.0  0.573  6.120  76.7  2.2875  1.0  273.0   \n",
       "503  0.06076   0.0  11.93   0.0  0.573  6.976  91.0  2.1675  1.0  273.0   \n",
       "504  0.10959   0.0  11.93   0.0  0.573  6.794  89.3  2.3889  1.0  273.0   \n",
       "505  0.04741   0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0   \n",
       "\n",
       "     PTRATIO       B  LSTAT  PRICE  \n",
       "0       15.3  396.90   4.98   24.0  \n",
       "1       17.8  396.90   9.14   21.6  \n",
       "2       17.8  392.83   4.03   34.7  \n",
       "3       18.7  394.63   2.94   33.4  \n",
       "4       18.7  396.90   5.33   36.2  \n",
       "..       ...     ...    ...    ...  \n",
       "501     21.0  391.99   9.67   22.4  \n",
       "502     21.0  396.90   9.08   20.6  \n",
       "503     21.0  396.90   5.64   23.9  \n",
       "504     21.0  393.45   6.48   22.0  \n",
       "505     21.0  396.90   7.88   11.9  \n",
       "\n",
       "[506 rows x 14 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(raw_data.data, columns=raw_data.feature_names)\n",
    "df[\"PRICE\"] = raw_data.target\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Binning & Smooting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data içinde bulunan \"DIS\" değişkeninde Evin Bostondaki iş merkezlerine uzaklığı ağırlıklı olarak hesaplanmış. Bu değişkeni farklı yöntemler kullanarak Ayrıklaştırmak istiyoruz.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
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     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
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    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bu scatterplotı Ayrıklaştırma işlemi yapıldıktan sonraki hali ile karşılaştırabilirsiniz\n",
    "DIS = df.DIS\n",
    "x = np.arange(len(DIS))\n",
    "plt.scatter(x, DIS)\n",
    "plt.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Soru"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x196c421ee48>"
      ]
     },
     "execution_count": 60,
     "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": [
    "# y değişkeninin için pd.cut fonksiyonunu kullanarak df.DIS 'ın ayrıklaştırılmış hali ile doldurun \n",
    "# NOT: bins parametresi için \"3\", labels için \"[0,1,2]\" ve retbins için \"True\" değerlerini kullanın\n",
    "new_DIS, bins = pd.cut(df.DIS, bins = 3, retbins = True, labels = [0,1,2]) \n",
    "x = np.arange(len(new_DIS))\n",
    "plt.scatter(x, new_DIS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>pd.cut</b> fonksiyonu, değişkeni ayrıklaştırırken aşağıdaki stratejilerden hangisini kullandı?<br>\n",
    "-- Equal-frequency(Eşit frekans)<br>\n",
    "-- Equal-width (eşit aralıklar)\n",
    "\n",
    "IPUCU: değişkenin min-max değerlerini ve value_count dağılımlarını kontrol edebilirsiniz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Min: 1.1296 Max: 12.1265\n",
      "Sınır değerleri: [ 1.1186031   4.79523333  8.46086667 12.1265    ]\n",
      "\n",
      " Ayrık değerlerin görülme sayısı\n",
      "0    365\n",
      "1    125\n",
      "2     16\n",
      "Name: DIS, dtype: int64 \n",
      "\n",
      "\n",
      "Equal-width\n"
     ]
    }
   ],
   "source": [
    "print(\"Min:\", df.DIS.min(),\"Max:\", df.DIS.max())\n",
    "print(\"Sınır değerleri:\", bins)\n",
    "print(\"\\n Ayrık değerlerin görülme sayısı\")\n",
    "print(new_DIS.value_counts(), \"\\n\\n\")\n",
    "\n",
    "print(\"Equal-width\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Soru "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x196c42914c8>"
      ]
     },
     "execution_count": 62,
     "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": [
    "# aynı işlemi pd.qcut kullanarak yapın\n",
    "# NOT: q parametresi için \"3\", labels için \"[0,1,2]\" ve retbins için \"True\" değerlerini kullanın\n",
    "new_DIS, bins = pd.qcut(df.DIS, q = 3, retbins = True, labels = [0,1,2])\n",
    "x = np.arange(len(new_DIS))\n",
    "plt.scatter(x, new_DIS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>pd.qcut</b> fonksiyonu, değişkeni ayrıklaştırırken aşağıdaki stratejilerden hangisini kullandı?<br>\n",
    "-- Equal-frequency(Eşit frekans)<br>\n",
    "-- Equal-width (eşit aralıklar)\n",
    "\n",
    "IPUCU: değişkenin min-max değerlerini ve value_count dağılımlarını kontrol edebilirsiniz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Min: 1.1296 Max: 12.1265\n",
      "Sınır değerleri: [ 1.1296      2.38403333  4.3257     12.1265    ]\n",
      "\n",
      " Ayrık değerlerin görülme sayısı\n",
      "2    169\n",
      "0    169\n",
      "1    168\n",
      "Name: DIS, dtype: int64 \n",
      "\n",
      "\n",
      "Equal-frequency\n"
     ]
    }
   ],
   "source": [
    "print(\"Min:\", df.DIS.min(),\"Max:\", df.DIS.max())\n",
    "print(\"Sınır değerleri:\", bins)\n",
    "print(\"\\n Ayrık değerlerin görülme sayısı\")\n",
    "print(new_DIS.value_counts(), \"\\n\\n\")\n",
    "\n",
    "print(\"Equal-frequency\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature Generation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bu bölümde var olan değişkenlerden yeni değişkenler üretelim."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "        - CRIM     per capita crime rate by town\n",
    "        - ZN       proportion of residential land zoned for lots over 25,000 sq.ft.\n",
    "        - INDUS    proportion of non-retail business acres per town\n",
    "        - CHAS     Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n",
    "        - NOX      nitric oxides concentration (parts per 10 million)\n",
    "        - RM       average number of rooms per dwelling\n",
    "        - AGE      proportion of owner-occupied units built prior to 1940\n",
    "        - DIS      weighted distances to five Boston employment centres\n",
    "        - RAD      index of accessibility to radial highways\n",
    "        - TAX      full-value property-tax rate per $10,000\n",
    "        - PTRATIO  pupil-teacher ratio by town\n",
    "        - B        1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town\n",
    "        - LSTAT    % lower status of the population\n",
    "        - MEDV     Median value of owner-occupied homes in $1000's"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>PRICE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00632</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.0900</td>\n",
       "      <td>1.0</td>\n",
       "      <td>296.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>396.90</td>\n",
       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02731</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02729</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>0.06263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.593</td>\n",
       "      <td>69.1</td>\n",
       "      <td>2.4786</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>391.99</td>\n",
       "      <td>9.67</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>0.04527</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.120</td>\n",
       "      <td>76.7</td>\n",
       "      <td>2.2875</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.08</td>\n",
       "      <td>20.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>0.06076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.976</td>\n",
       "      <td>91.0</td>\n",
       "      <td>2.1675</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.64</td>\n",
       "      <td>23.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>0.10959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.794</td>\n",
       "      <td>89.3</td>\n",
       "      <td>2.3889</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>393.45</td>\n",
       "      <td>6.48</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>0.04741</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.030</td>\n",
       "      <td>80.8</td>\n",
       "      <td>2.5050</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>7.88</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>506 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
       "0    0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0   \n",
       "1    0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0   \n",
       "2    0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0   \n",
       "3    0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0   \n",
       "4    0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0   \n",
       "..       ...   ...    ...   ...    ...    ...   ...     ...  ...    ...   \n",
       "501  0.06263   0.0  11.93   0.0  0.573  6.593  69.1  2.4786  1.0  273.0   \n",
       "502  0.04527   0.0  11.93   0.0  0.573  6.120  76.7  2.2875  1.0  273.0   \n",
       "503  0.06076   0.0  11.93   0.0  0.573  6.976  91.0  2.1675  1.0  273.0   \n",
       "504  0.10959   0.0  11.93   0.0  0.573  6.794  89.3  2.3889  1.0  273.0   \n",
       "505  0.04741   0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0   \n",
       "\n",
       "     PTRATIO       B  LSTAT  PRICE  \n",
       "0       15.3  396.90   4.98   24.0  \n",
       "1       17.8  396.90   9.14   21.6  \n",
       "2       17.8  392.83   4.03   34.7  \n",
       "3       18.7  394.63   2.94   33.4  \n",
       "4       18.7  396.90   5.33   36.2  \n",
       "..       ...     ...    ...    ...  \n",
       "501     21.0  391.99   9.67   22.4  \n",
       "502     21.0  396.90   9.08   20.6  \n",
       "503     21.0  396.90   5.64   23.9  \n",
       "504     21.0  393.45   6.48   22.0  \n",
       "505     21.0  396.90   7.88   11.9  \n",
       "\n",
       "[506 rows x 14 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_FG = df.copy()\n",
    "df_FG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# seçtiğiniz iki değişkenin toplamından yeni bir değişken üretin\n",
    "df_FG[\"DIS + PTRATIO\"] = df_FG[\"DIS\"] + df_FG[\"PTRATIO\"] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "# seçtiğiniz iki değişkenin farkından yeni bir değişken üretin\n",
    "df_FG[\"DIS - PTRATIO\"] = df_FG[\"DIS\"] - df_FG[\"PTRATIO\"] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# seçtiğiniz iki değişkenin bölümünden yeni bir değişken üretin\n",
    "df_FG[\"DIS / PTRATIO\"] = df_FG[\"DIS\"] / df_FG[\"PTRATIO\"] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# seçtiğiniz iki değişkenin çarpımından yeni bir değişken üretin\n",
    "df_FG[\"DIS * PTRATIO\"] = df_FG[\"DIS\"] * df_FG[\"PTRATIO\"] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>CRIM</th>\n",
       "      <th>ZN</th>\n",
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       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
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       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "      <td>19.3900</td>\n",
       "      <td>-11.2100</td>\n",
       "      <td>0.267320</td>\n",
       "      <td>62.57700</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02731</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>17.8</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.7671</td>\n",
       "      <td>-12.8329</td>\n",
       "      <td>0.279051</td>\n",
       "      <td>88.41438</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02729</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "      <td>22.7671</td>\n",
       "      <td>-12.8329</td>\n",
       "      <td>0.279051</td>\n",
       "      <td>88.41438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "      <td>24.7622</td>\n",
       "      <td>-12.6378</td>\n",
       "      <td>0.324182</td>\n",
       "      <td>113.36314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
       "      <td>24.7622</td>\n",
       "      <td>-12.6378</td>\n",
       "      <td>0.324182</td>\n",
       "      <td>113.36314</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
       "0  0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0   \n",
       "1  0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0   \n",
       "2  0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0   \n",
       "3  0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0   \n",
       "4  0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0   \n",
       "\n",
       "   PTRATIO       B  LSTAT  PRICE  DIS + PTRATIO  DIS - PTRATIO  DIS / PTRATIO  \\\n",
       "0     15.3  396.90   4.98   24.0        19.3900       -11.2100       0.267320   \n",
       "1     17.8  396.90   9.14   21.6        22.7671       -12.8329       0.279051   \n",
       "2     17.8  392.83   4.03   34.7        22.7671       -12.8329       0.279051   \n",
       "3     18.7  394.63   2.94   33.4        24.7622       -12.6378       0.324182   \n",
       "4     18.7  396.90   5.33   36.2        24.7622       -12.6378       0.324182   \n",
       "\n",
       "   DIS * PTRATIO  \n",
       "0       62.57700  \n",
       "1       88.41438  \n",
       "2       88.41438  \n",
       "3      113.36314  \n",
       "4      113.36314  "
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_FG.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sklearn kütüphanesindeki PolynomialFeatures'ı kullanarak yeni featurelar üretin (NOT:Hedef değişkeni(PRICE) yeni featureları üretirken kullanmayın.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>PRICE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00632</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.0900</td>\n",
       "      <td>1.0</td>\n",
       "      <td>296.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>396.90</td>\n",
       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02731</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02729</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>0.06263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.593</td>\n",
       "      <td>69.1</td>\n",
       "      <td>2.4786</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>391.99</td>\n",
       "      <td>9.67</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>0.04527</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.120</td>\n",
       "      <td>76.7</td>\n",
       "      <td>2.2875</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.08</td>\n",
       "      <td>20.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>0.06076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.976</td>\n",
       "      <td>91.0</td>\n",
       "      <td>2.1675</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.64</td>\n",
       "      <td>23.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>0.10959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.794</td>\n",
       "      <td>89.3</td>\n",
       "      <td>2.3889</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>393.45</td>\n",
       "      <td>6.48</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>0.04741</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.030</td>\n",
       "      <td>80.8</td>\n",
       "      <td>2.5050</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>7.88</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>506 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
       "0    0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0   \n",
       "1    0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0   \n",
       "2    0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0   \n",
       "3    0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0   \n",
       "4    0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0   \n",
       "..       ...   ...    ...   ...    ...    ...   ...     ...  ...    ...   \n",
       "501  0.06263   0.0  11.93   0.0  0.573  6.593  69.1  2.4786  1.0  273.0   \n",
       "502  0.04527   0.0  11.93   0.0  0.573  6.120  76.7  2.2875  1.0  273.0   \n",
       "503  0.06076   0.0  11.93   0.0  0.573  6.976  91.0  2.1675  1.0  273.0   \n",
       "504  0.10959   0.0  11.93   0.0  0.573  6.794  89.3  2.3889  1.0  273.0   \n",
       "505  0.04741   0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0   \n",
       "\n",
       "     PTRATIO       B  LSTAT  PRICE  \n",
       "0       15.3  396.90   4.98   24.0  \n",
       "1       17.8  396.90   9.14   21.6  \n",
       "2       17.8  392.83   4.03   34.7  \n",
       "3       18.7  394.63   2.94   33.4  \n",
       "4       18.7  396.90   5.33   36.2  \n",
       "..       ...     ...    ...    ...  \n",
       "501     21.0  391.99   9.67   22.4  \n",
       "502     21.0  396.90   9.08   20.6  \n",
       "503     21.0  396.90   5.64   23.9  \n",
       "504     21.0  393.45   6.48   22.0  \n",
       "505     21.0  396.90   7.88   11.9  \n",
       "\n",
       "[506 rows x 14 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_polyfe = df.copy()\n",
    "df_polyfe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>78.9</td>\n",
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       "      <td>7064.820</td>\n",
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       "      <td>384.48</td>\n",
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       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>316.84</td>\n",
       "      <td>6992.374</td>\n",
       "      <td>71.734</td>\n",
       "      <td>617.66</td>\n",
       "      <td>154315.4089</td>\n",
       "      <td>1583.1049</td>\n",
       "      <td>13631.201</td>\n",
       "      <td>16.2409</td>\n",
       "      <td>139.841</td>\n",
       "      <td>1204.09</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>349.69</td>\n",
       "      <td>7379.581</td>\n",
       "      <td>54.978</td>\n",
       "      <td>624.58</td>\n",
       "      <td>155732.8369</td>\n",
       "      <td>1160.2122</td>\n",
       "      <td>13180.642</td>\n",
       "      <td>8.6436</td>\n",
       "      <td>98.196</td>\n",
       "      <td>1115.56</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>349.69</td>\n",
       "      <td>7422.030</td>\n",
       "      <td>99.671</td>\n",
       "      <td>676.94</td>\n",
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       "      <td>2115.4770</td>\n",
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       "      <td>28.4089</td>\n",
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       "      <th>501</th>\n",
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       "      <td>0.0</td>\n",
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       "      <td>6.593</td>\n",
       "      <td>69.1</td>\n",
       "      <td>2.4786</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>441.00</td>\n",
       "      <td>8231.790</td>\n",
       "      <td>203.070</td>\n",
       "      <td>470.40</td>\n",
       "      <td>153656.1601</td>\n",
       "      <td>3790.5433</td>\n",
       "      <td>8780.576</td>\n",
       "      <td>93.5089</td>\n",
       "      <td>216.608</td>\n",
       "      <td>501.76</td>\n",
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       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.04527</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.120</td>\n",
       "      <td>76.7</td>\n",
       "      <td>2.2875</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>441.00</td>\n",
       "      <td>8334.900</td>\n",
       "      <td>190.680</td>\n",
       "      <td>432.60</td>\n",
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       "      <td>3603.8520</td>\n",
       "      <td>8176.140</td>\n",
       "      <td>82.4464</td>\n",
       "      <td>187.048</td>\n",
       "      <td>424.36</td>\n",
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       "      <th>503</th>\n",
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       "      <td>6.976</td>\n",
       "      <td>91.0</td>\n",
       "      <td>2.1675</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>441.00</td>\n",
       "      <td>8334.900</td>\n",
       "      <td>118.440</td>\n",
       "      <td>501.90</td>\n",
       "      <td>157529.6100</td>\n",
       "      <td>2238.5160</td>\n",
       "      <td>9485.910</td>\n",
       "      <td>31.8096</td>\n",
       "      <td>134.796</td>\n",
       "      <td>571.21</td>\n",
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       "      <th>504</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.10959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.794</td>\n",
       "      <td>89.3</td>\n",
       "      <td>2.3889</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>441.00</td>\n",
       "      <td>8262.450</td>\n",
       "      <td>136.080</td>\n",
       "      <td>462.00</td>\n",
       "      <td>154802.9025</td>\n",
       "      <td>2549.5560</td>\n",
       "      <td>8655.900</td>\n",
       "      <td>41.9904</td>\n",
       "      <td>142.560</td>\n",
       "      <td>484.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.04741</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.030</td>\n",
       "      <td>80.8</td>\n",
       "      <td>2.5050</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>441.00</td>\n",
       "      <td>8334.900</td>\n",
       "      <td>165.480</td>\n",
       "      <td>249.90</td>\n",
       "      <td>157529.6100</td>\n",
       "      <td>3127.5720</td>\n",
       "      <td>4723.110</td>\n",
       "      <td>62.0944</td>\n",
       "      <td>93.772</td>\n",
       "      <td>141.61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>506 rows × 120 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     0        1     2      3    4      5      6     7       8    9    ...  \\\n",
       "0    1.0  0.00632  18.0   2.31  0.0  0.538  6.575  65.2  4.0900  1.0  ...   \n",
       "1    1.0  0.02731   0.0   7.07  0.0  0.469  6.421  78.9  4.9671  2.0  ...   \n",
       "2    1.0  0.02729   0.0   7.07  0.0  0.469  7.185  61.1  4.9671  2.0  ...   \n",
       "3    1.0  0.03237   0.0   2.18  0.0  0.458  6.998  45.8  6.0622  3.0  ...   \n",
       "4    1.0  0.06905   0.0   2.18  0.0  0.458  7.147  54.2  6.0622  3.0  ...   \n",
       "..   ...      ...   ...    ...  ...    ...    ...   ...     ...  ...  ...   \n",
       "501  1.0  0.06263   0.0  11.93  0.0  0.573  6.593  69.1  2.4786  1.0  ...   \n",
       "502  1.0  0.04527   0.0  11.93  0.0  0.573  6.120  76.7  2.2875  1.0  ...   \n",
       "503  1.0  0.06076   0.0  11.93  0.0  0.573  6.976  91.0  2.1675  1.0  ...   \n",
       "504  1.0  0.10959   0.0  11.93  0.0  0.573  6.794  89.3  2.3889  1.0  ...   \n",
       "505  1.0  0.04741   0.0  11.93  0.0  0.573  6.030  80.8  2.5050  1.0  ...   \n",
       "\n",
       "        110       111      112     113          114        115        116  \\\n",
       "0    234.09  6072.570   76.194  367.20  157529.6100  1976.5620   9525.600   \n",
       "1    316.84  7064.820  162.692  384.48  157529.6100  3627.6660   8573.040   \n",
       "2    316.84  6992.374   71.734  617.66  154315.4089  1583.1049  13631.201   \n",
       "3    349.69  7379.581   54.978  624.58  155732.8369  1160.2122  13180.642   \n",
       "4    349.69  7422.030   99.671  676.94  157529.6100  2115.4770  14367.780   \n",
       "..      ...       ...      ...     ...          ...        ...        ...   \n",
       "501  441.00  8231.790  203.070  470.40  153656.1601  3790.5433   8780.576   \n",
       "502  441.00  8334.900  190.680  432.60  157529.6100  3603.8520   8176.140   \n",
       "503  441.00  8334.900  118.440  501.90  157529.6100  2238.5160   9485.910   \n",
       "504  441.00  8262.450  136.080  462.00  154802.9025  2549.5560   8655.900   \n",
       "505  441.00  8334.900  165.480  249.90  157529.6100  3127.5720   4723.110   \n",
       "\n",
       "         117      118      119  \n",
       "0    24.8004  119.520   576.00  \n",
       "1    83.5396  197.424   466.56  \n",
       "2    16.2409  139.841  1204.09  \n",
       "3     8.6436   98.196  1115.56  \n",
       "4    28.4089  192.946  1310.44  \n",
       "..       ...      ...      ...  \n",
       "501  93.5089  216.608   501.76  \n",
       "502  82.4464  187.048   424.36  \n",
       "503  31.8096  134.796   571.21  \n",
       "504  41.9904  142.560   484.00  \n",
       "505  62.0944   93.772   141.61  \n",
       "\n",
       "[506 rows x 120 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# PolynomialFeatures kullandığınız python kodunu buraya yazabilirsiniz.\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "poly_features = PolynomialFeatures(degree = 2, interaction_only=False)\n",
    "pd.DataFrame(poly_features.fit_transform(df_polyfe))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Normalizasyon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
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       "        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>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>PRICE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00632</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.0900</td>\n",
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       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02731</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02729</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>0.06263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.593</td>\n",
       "      <td>69.1</td>\n",
       "      <td>2.4786</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>391.99</td>\n",
       "      <td>9.67</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>0.04527</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.120</td>\n",
       "      <td>76.7</td>\n",
       "      <td>2.2875</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.08</td>\n",
       "      <td>20.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>0.06076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.976</td>\n",
       "      <td>91.0</td>\n",
       "      <td>2.1675</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.64</td>\n",
       "      <td>23.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>0.10959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.794</td>\n",
       "      <td>89.3</td>\n",
       "      <td>2.3889</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>393.45</td>\n",
       "      <td>6.48</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>0.04741</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.030</td>\n",
       "      <td>80.8</td>\n",
       "      <td>2.5050</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>7.88</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>506 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
       "0    0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0   \n",
       "1    0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0   \n",
       "2    0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0   \n",
       "3    0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0   \n",
       "4    0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0   \n",
       "..       ...   ...    ...   ...    ...    ...   ...     ...  ...    ...   \n",
       "501  0.06263   0.0  11.93   0.0  0.573  6.593  69.1  2.4786  1.0  273.0   \n",
       "502  0.04527   0.0  11.93   0.0  0.573  6.120  76.7  2.2875  1.0  273.0   \n",
       "503  0.06076   0.0  11.93   0.0  0.573  6.976  91.0  2.1675  1.0  273.0   \n",
       "504  0.10959   0.0  11.93   0.0  0.573  6.794  89.3  2.3889  1.0  273.0   \n",
       "505  0.04741   0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0   \n",
       "\n",
       "     PTRATIO       B  LSTAT  PRICE  \n",
       "0       15.3  396.90   4.98   24.0  \n",
       "1       17.8  396.90   9.14   21.6  \n",
       "2       17.8  392.83   4.03   34.7  \n",
       "3       18.7  394.63   2.94   33.4  \n",
       "4       18.7  396.90   5.33   36.2  \n",
       "..       ...     ...    ...    ...  \n",
       "501     21.0  391.99   9.67   22.4  \n",
       "502     21.0  396.90   9.08   20.6  \n",
       "503     21.0  396.90   5.64   23.9  \n",
       "504     21.0  393.45   6.48   22.0  \n",
       "505     21.0  396.90   7.88   11.9  \n",
       "\n",
       "[506 rows x 14 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_norm = df.copy()\n",
    "df_norm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sklearn kütüphanesindeki Min-max scalerı kullanarak datayı normalize edip yeni bir dataframe içine atayın "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            0     1         2    3         4         5         6         7  \\\n",
      "0    0.000000  0.18  0.067815  0.0  0.314815  0.577505  0.641607  0.269203   \n",
      "1    0.000236  0.00  0.242302  0.0  0.172840  0.547998  0.782698  0.348962   \n",
      "2    0.000236  0.00  0.242302  0.0  0.172840  0.694386  0.599382  0.348962   \n",
      "3    0.000293  0.00  0.063050  0.0  0.150206  0.658555  0.441813  0.448545   \n",
      "4    0.000705  0.00  0.063050  0.0  0.150206  0.687105  0.528321  0.448545   \n",
      "..        ...   ...       ...  ...       ...       ...       ...       ...   \n",
      "501  0.000633  0.00  0.420455  0.0  0.386831  0.580954  0.681771  0.122671   \n",
      "502  0.000438  0.00  0.420455  0.0  0.386831  0.490324  0.760041  0.105293   \n",
      "503  0.000612  0.00  0.420455  0.0  0.386831  0.654340  0.907312  0.094381   \n",
      "504  0.001161  0.00  0.420455  0.0  0.386831  0.619467  0.889804  0.114514   \n",
      "505  0.000462  0.00  0.420455  0.0  0.386831  0.473079  0.802266  0.125072   \n",
      "\n",
      "            8         9        10        11        12        13  \n",
      "0    0.000000  0.208015  0.287234  1.000000  0.089680  0.422222  \n",
      "1    0.043478  0.104962  0.553191  1.000000  0.204470  0.368889  \n",
      "2    0.043478  0.104962  0.553191  0.989737  0.063466  0.660000  \n",
      "3    0.086957  0.066794  0.648936  0.994276  0.033389  0.631111  \n",
      "4    0.086957  0.066794  0.648936  1.000000  0.099338  0.693333  \n",
      "..        ...       ...       ...       ...       ...       ...  \n",
      "501  0.000000  0.164122  0.893617  0.987619  0.219095  0.386667  \n",
      "502  0.000000  0.164122  0.893617  1.000000  0.202815  0.346667  \n",
      "503  0.000000  0.164122  0.893617  1.000000  0.107892  0.420000  \n",
      "504  0.000000  0.164122  0.893617  0.991301  0.131071  0.377778  \n",
      "505  0.000000  0.164122  0.893617  1.000000  0.169702  0.153333  \n",
      "\n",
      "[506 rows x 14 columns]\n"
     ]
    }
   ],
   "source": [
    "# python kodu\n",
    "from sklearn import preprocessing \n",
    "min_max_scaler = MinMaxScaler()\n",
    "scaled_df = min_max_scaler.fit_transform(df_norm)\n",
    "df_sc = pd.DataFrame(scaled_df)\n",
    "print(df_sc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sklearn kütüphanesindeki StandardScalerı kullanarak datayı standardize edip yeni bir dataframe içine atayın "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            0         1         2         3         4         5         6  \\\n",
      "0   -0.419782  0.284830 -1.287909 -0.272599 -0.144217  0.413672 -0.120013   \n",
      "1   -0.417339 -0.487722 -0.593381 -0.272599 -0.740262  0.194274  0.367166   \n",
      "2   -0.417342 -0.487722 -0.593381 -0.272599 -0.740262  1.282714 -0.265812   \n",
      "3   -0.416750 -0.487722 -1.306878 -0.272599 -0.835284  1.016303 -0.809889   \n",
      "4   -0.412482 -0.487722 -1.306878 -0.272599 -0.835284  1.228577 -0.511180   \n",
      "..        ...       ...       ...       ...       ...       ...       ...   \n",
      "501 -0.413229 -0.487722  0.115738 -0.272599  0.158124  0.439316  0.018673   \n",
      "502 -0.415249 -0.487722  0.115738 -0.272599  0.158124 -0.234548  0.288933   \n",
      "503 -0.413447 -0.487722  0.115738 -0.272599  0.158124  0.984960  0.797449   \n",
      "504 -0.407764 -0.487722  0.115738 -0.272599  0.158124  0.725672  0.736996   \n",
      "505 -0.415000 -0.487722  0.115738 -0.272599  0.158124 -0.362767  0.434732   \n",
      "\n",
      "            7         8         9        10        11        12        13  \n",
      "0    0.140214 -0.982843 -0.666608 -1.459000  0.441052 -1.075562  0.159686  \n",
      "1    0.557160 -0.867883 -0.987329 -0.303094  0.441052 -0.492439 -0.101524  \n",
      "2    0.557160 -0.867883 -0.987329 -0.303094  0.396427 -1.208727  1.324247  \n",
      "3    1.077737 -0.752922 -1.106115  0.113032  0.416163 -1.361517  1.182758  \n",
      "4    1.077737 -0.752922 -1.106115  0.113032  0.441052 -1.026501  1.487503  \n",
      "..        ...       ...       ...       ...       ...       ...       ...  \n",
      "501 -0.625796 -0.982843 -0.803212  1.176466  0.387217 -0.418147 -0.014454  \n",
      "502 -0.716639 -0.982843 -0.803212  1.176466  0.441052 -0.500850 -0.210362  \n",
      "503 -0.773684 -0.982843 -0.803212  1.176466  0.441052 -0.983048  0.148802  \n",
      "504 -0.668437 -0.982843 -0.803212  1.176466  0.403225 -0.865302 -0.057989  \n",
      "505 -0.613246 -0.982843 -0.803212  1.176466  0.441052 -0.669058 -1.157248  \n",
      "\n",
      "[506 rows x 14 columns]\n"
     ]
    }
   ],
   "source": [
    "# python kodu\n",
    "from sklearn import preprocessing \n",
    "scaler = preprocessing.StandardScaler()\n",
    "std_sc_df = scaler.fit_transform(df_norm)\n",
    "df_std = pd.DataFrame(std_sc_df)\n",
    "print(df_std)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sklearn kütüphanesindeki RobustScalerı kullanarak datayı standardize edip yeni bir dataframe içine atayın "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            0     1         2    3         4         5         6         7  \\\n",
      "0   -0.069593  1.44 -0.571650  0.0  0.000000  0.496612 -0.250765  0.285777   \n",
      "1   -0.063755  0.00 -0.202943  0.0 -0.394286  0.287940  0.028542  0.569789   \n",
      "2   -0.063760  0.00 -0.202943  0.0 -0.394286  1.323171 -0.334353  0.569789   \n",
      "3   -0.062347  0.00 -0.581720  0.0 -0.457143  1.069783 -0.646279  0.924391   \n",
      "4   -0.052144  0.00 -0.581720  0.0 -0.457143  1.271680 -0.475025  0.924391   \n",
      "..        ...   ...       ...  ...       ...       ...       ...       ...   \n",
      "501 -0.053930  0.00  0.173509  0.0  0.200000  0.521003 -0.171254 -0.236007   \n",
      "502 -0.058759  0.00  0.173509  0.0  0.200000 -0.119919 -0.016310 -0.297887   \n",
      "503 -0.054450  0.00  0.173509  0.0  0.200000  1.039973  0.275229 -0.336744   \n",
      "504 -0.040867  0.00  0.173509  0.0  0.200000  0.793360  0.240571 -0.265053   \n",
      "505 -0.058164  0.00  0.173509  0.0  0.200000 -0.241870  0.067278 -0.227459   \n",
      "\n",
      "        8         9        10        11        12        13  \n",
      "0   -0.20 -0.087855 -1.339286  0.261902 -0.637681  0.351097  \n",
      "1   -0.15 -0.227390 -0.446429  0.261902 -0.221889  0.050157  \n",
      "2   -0.15 -0.227390 -0.446429  0.066675 -0.732634  1.692790  \n",
      "3   -0.10 -0.279070 -0.125000  0.153016 -0.841579  1.529781  \n",
      "4   -0.10 -0.279070 -0.125000  0.261902 -0.602699  1.880878  \n",
      "..    ...       ...       ...       ...       ...       ...  \n",
      "501 -0.20 -0.147287  0.696429  0.026382 -0.168916  0.150470  \n",
      "502 -0.20 -0.147287  0.696429  0.261902 -0.227886 -0.075235  \n",
      "503 -0.20 -0.147287  0.696429  0.261902 -0.571714  0.338558  \n",
      "504 -0.20 -0.147287  0.696429  0.096414 -0.487756  0.100313  \n",
      "505 -0.20 -0.147287  0.696429  0.261902 -0.347826 -1.166144  \n",
      "\n",
      "[506 rows x 14 columns]\n"
     ]
    }
   ],
   "source": [
    "# python kodu\n",
    "from sklearn import preprocessing\n",
    "robust_scaler = RobustScaler()\n",
    "robust_df = RobustScaler().fit_transform(df_norm)\n",
    "df_rs = pd.DataFrame(robust_df)\n",
    "print(df_rs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Correlation & Covariance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bu hücrede değişkenlerin birbiri ile olan korelasyonları heatmap kullanarak görselleştirildi.<br>\n",
    "Aşağıdaki sorular bu görseli incelemeye ve yorumlamaya yönelik olacaktır.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,12))\n",
    "sns.heatmap(df.corr(), vmin=-1, vmax=1, square=True, annot=True, fmt='.2f')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Aşağıda örnek iki değişken için scatter plot çizilmiştir."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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UHm3jsXVb+Pm6rXxw1gQumDWRb/zjszzwTAsMgfPfdSK3XD6b2pHD+Ob/fo6lz23h0lMn8vU/PhWAhk1t3P34Rl5qe4PjhlYz9vgaPnHGVKbWHs+ytVto27WH2pHD+NDvTWTGhFEAfPbvV/CLf9nGjAnHsehjc3ls3RZ+8NRLjBxazZy60Tzz4nbe2LOfYTVDqBt7HCeOrOH/bGhDwBnTx9KuKn5v4khCVWze/gYNv32Nd44eyvbdb7N7zz6at+9mfxya38wTj+d9J9fyx+99Jy+2vcmcujEHayn2J3c+warmncytG82fnTeTH69s4Z0nDOeqM6Ye7N+wqY3HN2zj5HHHsb8dqqtg47Y3OXfmOOqn1x5cf2C5WNPW11ndvKPT8b/0o1U8uv5VLjzlRL798bksWrb+sO/lZ/9+Bb98YRt/cNIYVre8xo7dbzN59FCe/NqFXW67bdceWra/xZSxI6gdOexgjZte3UlD82tceupE1m5+jWde2sG8qWP4h8+c3aPXTSkdx7LBa9oNPz34+MW/+XBu4yxe1czSNVu49LSJXDa3rk+3rYjovldvNiwNAV4ALgRagBXAwohYV9Tnz4HZEfFnkq4EPhIRH+9qu/X19dHQ0FBWLQ+vfpnP3b+60/U1gg1/3fU38IOLfsULW98oa1wo7HK9b0Yt/9zU1uPnXH3WSdz71G/LHisPV591EjcvOO3gcvGLvrP+G1vf6HK+Jwwfwmu73z64fM6MWu771JkA3Lh4Dfc+fWju5Y5fjuJtP7z6Zb7yUCM1VVXsa2/npHeM6NH3uzc/+B3HuvXy2cyfM7ns7djAK/V6zCMMzrzlUbbs3HtwedLooTz1tQvL2oaklRFRX2pdnoeG5gFNEbExIvYC9wMLOvRZANyTPX4QuECS+rKItl17+OIDz3bZZ1/AomXrO13/2LotvQoBgHYoKwSAYyYEoFBL09bXgcKeQE/6dzff4hAAeKKpjYZNbTRtff2wEOg4/pd+tKqc0ntUa9PW12nbtYevPNTI7n3tvL5nP7v3tff4+33VXU+WNWapsb78UCNtu/b0Zgo2gDr7o6Qv/1iBwp5AcQgAvLJzL4tXNffZGHkGwWSguNKWrK1kn4jYD7wG1Hbog6RrJTVIamhtbS2riJbtb9Heg72ehxu3dLru5+u2ljVmpVndvAOAVc07cxvj8Q3bDo7T2fiPrn+1z8dd3byDlu1vUVPVux+FZ14qXXNnSo1VU1VFy/a3ejW+Vb6la0r/buqsvTfyDIJSf9l3/I3ckz5ExN0RUR8R9ePHjy+riCljR1DVg52MBbMndrrug7MmlDVmpZlTNwaAuXWjcxvj3JnjDo7T2fgXnnJin487p24MU8aOYF97e6+eP29q6Zo7U2qsfe3tTBk7olfjW+W79LTSv5s6a++NPIOgBSg+ozEF2NxZH0nVwAnA7/qyiNqRw/jOx97bZZ8a0eUJ4wtmTeTdE47v1fhVFI6Bl+Pqs07q1Vh5uPqskw6eVP3xn5/To/7dzfeE4UMOWz5nRi3102uZMWHUEXMvHv/bH59bTuk9qnXGhFHUjhzGrZfPZnhNFaOGVTO8pqrH3+9yTxiXGuvW7E0GNrh0di6gr88RXDa3jkmjhx7WNmn00D49YZznyeJqCieLLwBepnCy+KqIWFvU5zrgtKKTxR+NiI91td3enCwGv2vI7xryu4YsH4PlXUNdnSzOLQiygS8Bvkvh7aN/FxHflHQz0BARSyQNB+4DTqewJ3BlRGzsapu9DQIzs5R1FQS5XkcQEY8Aj3Rou7Ho8W7gT/KswczMuuYri83MEucgMDNLnIPAzCxxDgIzs8Q5CMzMEucgMDNLXK7XEeRBUivwUk6bHwdsy2nbxxLPs7J4npUlr3lOjYiS9+gZdEGQJ0kNnV1wUUk8z8rieVaWgZinDw2ZmSXOQWBmljgHweHuHugC+onnWVk8z8rS7/P0OQIzs8R5j8DMLHEOAjOzxCUTBJLqJC2XtF7SWkmfy9rfIelRSRuyf8dm7ZJ0u6QmSY2S+vbjsXIiabikZyQ9m83zL7P26ZJ+nc3zR5KGZu3DsuWmbP20gay/XJKGSPqNpKXZcsXNU9KLktZIWi2pIWurqNctgKQxkh6U9C/Zz+lZFTrPd2ffywNfOyV9fiDnmkwQAPuBL0bEKcCZwHWSZgE3AI9FxEzgsWwZ4GJgZvZ1LfC9/i+5V/YA74+I9wJzgIsknQn8LbAom+d24Jqs/zXA9oiYASzK+g0mnwPWFy1X6jzPj4g5Re8vr7TXLcBtwD9FxHuA91L4vlbcPCPi+ex7OQf4feBN4CcM5FwjIskv4GHgQuB5YFLWNgl4Pnt8F7CwqP/BfoPlCzgOWAWcQeFKxeqs/SxgWfZ4GXBW9rg666eBrr2H85uS/cC8H1gKqELn+SIwrkNbRb1ugdHApo7fk0qbZ4l5fxB4cqDnmtIewUHZYYHTgV8DEyLiFYDs3xOzbpOB5qKntWRtx7zscMlq4FXgUeD/ATsiYn/WpXguB+eZrX8N6PrT548d3wW+DLRny7VU5jwD+LmklZKuzdoq7XV7MtAK/CA71Pd9ScdTefPs6Ergh9njAZtrckEgaSTwEPD5iNjZVdcSbYPivbYR8XYUdjunAPOAU0p1y/4dlPOUdCnwakSsLG4u0XVQzzNzdkTMpXCI4DpJ53bRd7DOsxqYC3wvIk4H3uDQoZFSBus8D8rOX80Hftxd1xJtfTrXpIJAUg2FEPhfEfGPWfNWSZOy9ZMo/BUNhdStK3r6FGBzf9XaFyJiB/ArCudExkg68BnVxXM5OM9s/QnA7/q30l45G5gv6UXgfgqHh75L5c2TiNic/fsqhWPJ86i8120L0BIRv86WH6QQDJU2z2IXA6siYmu2PGBzTSYIJAn4H8D6iPhO0aolwJ9mj/+UwrmDA+1XZ2fszwReO7DbdiyTNF7SmOzxCOADFE66LQeuyLp1nOeB+V8B/DKyA5HHsoj4akRMiYhpFHavfxkRn6DC5inpeEmjDjymcEz5OSrsdRsRW4BmSe/Omi4A1lFh8+xgIYcOC8FAznWgT5b040mZP6SwO9UIrM6+LqFwnPgxYEP27zuy/gLuoHB8fQ1QP9Bz6OE8ZwO/yeb5HHBj1n4y8AzQRGFXdFjWPjxbbsrWnzzQc+jFnM8DllbiPLP5PJt9rQW+nrVX1Os2q30O0JC9dhcDYytxnln9xwFtwAlFbQM2V99iwswscckcGjIzs9IcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGY9IKm26G6RWyS9XLQ8VNJHJIWk9xQ9p17Sczp0B9R/JWmjpNEDNxOzI/nto2ZlknQTsCsivl3U9gCFG4U9FhE3FbXfSeGK2Vsk/RNwT0T8ELNjSHX3XcysK9n9q84GzqdwFehNRau/BqyStB+ocQjYschBYHb0LqNwH/0XJP1O0tyIWAWF+z1J+lvgTmDWgFZp1gmfIzA7egsp3PiO7N+FHdZfDGzFQWDHKO8RmB0FSbUU7nx6qqQAhgAh6csREdntsk8APgT8RNKyiHhzAEs2O4L3CMyOzhXAvRExNSKmRUQdhU/a+sPs7q//GbguItZQuJvk1wewVrOSHARmR2chhc8IKPYQcBXwH4DFEbEua78JuFLSzP4rz6x7fvuomVnivEdgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmifv/I0V6jnswqz8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter(\"TAX\",\"CHAS\")\n",
    "plt.show()\n",
    "# scatter plot çizerken buradan kopya çekebilirsiniz :)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Yukarıdaki heatmapten birbiri ile pozitif yüksek korelasyona sahip iki değişken için scatter plot çiziniz. Bir iki cümle ile görseli yorumlamaya çalışınız. Not:Yorum yaparken değişkenlerin yukarıdaki açıklamalarından faydalanabilirsiniz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yukarıda heatmap üzerinde korelasyon değerlerini incelediğimde ele aldığım iki değikenin yüksek korelasyona sahip olup değerinin 0.91'dir. Yani emlak vergi oranları ile otoyollara erişebilirlik indexi arasında pozitif korelasyon vardır.\n"
     ]
    }
   ],
   "source": [
    "# python kodu buraya\n",
    "df.plot.scatter(\"TAX\",\"RAD\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Yukarıda heatmap üzerinde korelasyon değerlerini incelediğimde ele aldığım iki değikenin yüksek korelasyona sahip olup değerinin 0.91'dir. Yani emlak vergi oranları ile otoyollara erişebilirlik indexi arasında pozitif korelasyon vardır.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Heatmapten faydalanarak negatif korelasyonlu iki değişken için scatter plot çiziniz. Sonucu yorumlayınız"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yukarıda heatmap üzerinde korelasyon değerlerini incelediğimde ele aldığım iki değikenin negatif korelasyona sahip olup değerinin -0.77'dir. Yani istihdam merkezine ağırlıklı yakınlık ile nitrik asit konsantrasyonu arasında negatif korelasyon vardır.\n"
     ]
    }
   ],
   "source": [
    "# python kodu buraya\n",
    "df.plot.scatter(\"DIS\", \"NOX\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Yukarıda heatmap üzerinde korelasyon değerlerini incelediğimde ele aldığım iki değikenin negatif korelasyona sahip olup değerinin -0.77'dir. Yani istihdam merkezine ağırlıklı yakınlık ile nitrik asit konsantrasyonu arasında negatif korelasyon vardır.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Heatmapten faydalanarak düşük korelasyonlu iki değişken için scatter plot çiziniz. Sonucu yorumlayınız."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "scrolled": true
   },
   "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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yukarıda heatmap üzerinde korelasyon değerlerini incelediğimde ele aldığım iki değikenin negatif korelasyona sahip olup değerinin -0.04'dir.Yani emlak vergi oranları ile yolun nehri sıfırlayıp(1) ya da sıfırlamayıp (0) olduğunu belirten değişken arasında negatif korelasyon vardır.\n"
     ]
    }
   ],
   "source": [
    "# python kodu buraya\n",
    "df.plot.scatter(\"TAX\", \"CHAS\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Yukarıda heatmap üzerinde korelasyon değerlerini incelediğimde ele aldığım iki değikenin negatif korelasyona sahip olup değerinin -0.04'dir.Yani emlak vergi oranları ile yolun nehri sıfırlayıp(1) ya da sıfırlamayıp (0) olduğunu belirten değişken arasında negatif korelasyon vardır.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Soru"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Adım 1 :</b>df.cov() methodunu kullanarak datasetteki covariance değerlerini hesaplayın.<br> \n",
    "sns.heatmap ile bu methodu görselleştirin (IPUCU: Yukarıda korelasyon gösteriminde kullanılan yöntemin aynısı)\n",
    "heatmap için vmin ve vmax parametrelerini kullanmayın."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap için python kodunu bu hücreye yazın\n",
    "plt.figure(figsize=(12,12))\n",
    "sns.heatmap(df.cov(), vmin=-1, vmax=1, square=True, annot=True, fmt='.2f')\n",
    "plt.show()\n",
    "\n",
    "# Bilgi: Kovaryans değerinden anlam çıkartmak korelasyona göre daha zor çıkan grafikten bunu farkedebilirsiniz."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Adım 2 :</b> Şimdi sklearn.preprocessing paketi içindeki StandardScaler objesini kullanarak datayı standardize edin ve bunu ayrı bir dataframede tutun. Standardize edilmiş dataframe objesinin Kovaryans değerini tekrar hesaplatıp görselleştirin.\n",
    "\n",
    "<br>IPUCU : standardScalerdan gelen dönüştürülmüş datayı tekrar pandas DataFrame objesine çevirin ve bunu yaparken kolon adlarını kaybetmemeye çalışın örn: pd.DataFrame(standardize_numpy_datası, columns=df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap için python kodunu bu hücreye yazın\n",
    "from sklearn import preprocessing \n",
    "std_scaler = preprocessing.StandardScaler()\n",
    "std_df = scaler.fit_transform(df)\n",
    "df_stdsc = pd.DataFrame(std_df, columns = df.columns)\n",
    "plt.figure(figsize=(20,20))\n",
    "sns.heatmap(df_stdsc.cov(), square=True, annot=True, fmt='.2f')\n",
    "plt.show()\n",
    "\n",
    "# Bilgi: Ortaya çıkan grafik korelasyon grafiğine benziyor mu? :)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}