Ödev1-Ayşenur Oya Özen.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import statistics\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ilan no</th>\n",
       "      <th>emlak tipi</th>\n",
       "      <th>il</th>\n",
       "      <th>ilçe</th>\n",
       "      <th>fiyat</th>\n",
       "      <th>oda</th>\n",
       "      <th>banyo</th>\n",
       "      <th>kat</th>\n",
       "      <th>ısıtma</th>\n",
       "      <th>m2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8611</td>\n",
       "      <td>satılık müstakil ev</td>\n",
       "      <td>istanbul</td>\n",
       "      <td>kadıköy</td>\n",
       "      <td>1690000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>merkezi</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7885</td>\n",
       "      <td>satılık daire</td>\n",
       "      <td>istanbul</td>\n",
       "      <td>ataşehir</td>\n",
       "      <td>1200000</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>doğalgaz</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8607</td>\n",
       "      <td>satılık daire</td>\n",
       "      <td>ankara</td>\n",
       "      <td>çankaya</td>\n",
       "      <td>795000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>doğalgaz</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7765</td>\n",
       "      <td>satılık villa</td>\n",
       "      <td>istanbul</td>\n",
       "      <td>kadıköy</td>\n",
       "      <td>1345000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>merkezi</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8601</td>\n",
       "      <td>satılık daire</td>\n",
       "      <td>izmir</td>\n",
       "      <td>bornova</td>\n",
       "      <td>468000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>doğalgaz</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8708</td>\n",
       "      <td>satılık daire</td>\n",
       "      <td>istanbul</td>\n",
       "      <td>beyoğlu</td>\n",
       "      <td>1200000</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>doğalgaz</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ilan no           emlak tipi        il      ilçe    fiyat  oda  banyo  kat  \\\n",
       "0     8611  satılık müstakil ev  istanbul   kadıköy  1690000    3      1    8   \n",
       "1     7885        satılık daire  istanbul  ataşehir  1200000    5      2    8   \n",
       "2     8607        satılık daire    ankara   çankaya   795000    3      1    4   \n",
       "3     7765        satılık villa  istanbul   kadıköy  1345000    2      1    3   \n",
       "4     8601        satılık daire     izmir   bornova   468000    3      1    2   \n",
       "5     8708        satılık daire  istanbul   beyoğlu  1200000    3      2    5   \n",
       "\n",
       "     ısıtma   m2  \n",
       "0   merkezi  110  \n",
       "1  doğalgaz  250  \n",
       "2  doğalgaz  115  \n",
       "3   merkezi  100  \n",
       "4  doğalgaz  130  \n",
       "5  doğalgaz  120  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "veriseti={\"ilan no\":[8611,7885,8607,7765,8601,8708],\n",
    "         \"emlak tipi\":[\"satılık müstakil ev\",\"satılık daire\",\"satılık daire\",\"satılık villa\",\"satılık daire\",\"satılık daire\"],\n",
    "         \"il\":[\"istanbul\",\"istanbul\",\"ankara\",\"istanbul\",\"izmir\",\"istanbul\"],\n",
    "         \"ilçe\":[\"kadıköy\",\"ataşehir\",\"çankaya\",\"kadıköy\",\"bornova\",\"beyoğlu\"],\n",
    "         \"fiyat\":[1690000,1200000,795000,1345000,468000,1200000],\n",
    "         \"oda\":[3,5,3,2,3,3],\n",
    "         \"banyo\":[1,2,1,1,1,2],\n",
    "         \"kat\":[8,8,4,3,2,5],\n",
    "         \"ısıtma\":[\"merkezi\",\"doğalgaz\",\"doğalgaz\",\"merkezi\",\"doğalgaz\",\"doğalgaz\"],\n",
    "         \"m2\":[110,250,115,100,130,120]}  \n",
    "df=pd.DataFrame(veriseti)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Feauture tipleri: \n",
    "#emlak tipi:categorical - nominal,il:categorical - nominal,ilçe:categorical - nominal,ısıtma:categorical - nominal\n",
    "#ilan no: numeric-ratio,fiyat:numeric-ratio,oda:numeric-ratio,\n",
    "#banyo:numeric-ratio,kat:numeric-ratio,m2:numeric-ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " MODE \n",
      "    ilan no     emlak tipi        il     ilçe      fiyat  oda  banyo  kat  \\\n",
      "0     7765  satılık daire  istanbul  kadıköy  1200000.0  3.0    1.0  8.0   \n",
      "1     7885            NaN       NaN      NaN        NaN  NaN    NaN  NaN   \n",
      "2     8601            NaN       NaN      NaN        NaN  NaN    NaN  NaN   \n",
      "3     8607            NaN       NaN      NaN        NaN  NaN    NaN  NaN   \n",
      "4     8611            NaN       NaN      NaN        NaN  NaN    NaN  NaN   \n",
      "5     8708            NaN       NaN      NaN        NaN  NaN    NaN  NaN   \n",
      "\n",
      "     ısıtma   m2  \n",
      "0  doğalgaz  100  \n",
      "1       NaN  110  \n",
      "2       NaN  115  \n",
      "3       NaN  120  \n",
      "4       NaN  130  \n",
      "5       NaN  250  \n"
     ]
    }
   ],
   "source": [
    "print(\"\\n MODE \\n\",df.mode(axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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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>sütun_adı</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "      <th>midrange</th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ilan no</td>\n",
       "      <td>8708</td>\n",
       "      <td>7765</td>\n",
       "      <td>8236.5</td>\n",
       "      <td>8.362833e+03</td>\n",
       "      <td>8604.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>fiyat</td>\n",
       "      <td>1690000</td>\n",
       "      <td>468000</td>\n",
       "      <td>1079000.0</td>\n",
       "      <td>1.116333e+06</td>\n",
       "      <td>1200000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>oda</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.166667e+00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>banyo</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1.333333e+00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>kat</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>m2</td>\n",
       "      <td>250</td>\n",
       "      <td>100</td>\n",
       "      <td>175.0</td>\n",
       "      <td>1.375000e+02</td>\n",
       "      <td>117.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  sütun_adı      max     min   midrange          mean     median\n",
       "0   ilan no     8708    7765     8236.5  8.362833e+03     8604.0\n",
       "1     fiyat  1690000  468000  1079000.0  1.116333e+06  1200000.0\n",
       "2       oda        5       2        3.5  3.166667e+00        3.0\n",
       "3     banyo        2       1        1.5  1.333333e+00        1.0\n",
       "4       kat        8       2        5.0  5.000000e+00        4.5\n",
       "5        m2      250     100      175.0  1.375000e+02      117.5"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1=pd.DataFrame(veriseti,columns=['ilan no','fiyat','oda','banyo','kat','m2'])\n",
    "def area(df1):\n",
    "   df_out= pd.DataFrame(columns=['sütun_adı','max','min','midrange','mean','median'])\n",
    "   for i, col in enumerate(df1.columns):\n",
    "       report=[]\n",
    "       max_col= df1[col].max()\n",
    "       min_col= df1[col].min()\n",
    "       mean= df1[col].mean()\n",
    "       median= df1[col].median()\n",
    "       midrange= (max_col + min_col)/2       \n",
    "    \n",
    "       report.append(col) \n",
    "       report.append(max_col)\n",
    "       report.append(min_col)\n",
    "       report.append(midrange)\n",
    "       report.append(mean)\n",
    "       report.append(median)\n",
    "       df_out.loc[i] = report\n",
    "   return df_out\n",
    "area(df1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ilan no</th>\n",
       "      <th>fiyat</th>\n",
       "      <th>oda</th>\n",
       "      <th>banyo</th>\n",
       "      <th>kat</th>\n",
       "      <th>m2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>6.000000e+00</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8362.833333</td>\n",
       "      <td>1.116333e+06</td>\n",
       "      <td>3.166667</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>137.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>420.189679</td>\n",
       "      <td>4.287128e+05</td>\n",
       "      <td>0.983192</td>\n",
       "      <td>0.516398</td>\n",
       "      <td>2.529822</td>\n",
       "      <td>56.013391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>7765.000000</td>\n",
       "      <td>4.680000e+05</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>8064.000000</td>\n",
       "      <td>8.962500e+05</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.250000</td>\n",
       "      <td>111.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8604.000000</td>\n",
       "      <td>1.200000e+06</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>117.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8610.000000</td>\n",
       "      <td>1.308750e+06</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>7.250000</td>\n",
       "      <td>127.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8708.000000</td>\n",
       "      <td>1.690000e+06</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>250.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ilan no         fiyat       oda     banyo       kat          m2\n",
       "count     6.000000  6.000000e+00  6.000000  6.000000  6.000000    6.000000\n",
       "mean   8362.833333  1.116333e+06  3.166667  1.333333  5.000000  137.500000\n",
       "std     420.189679  4.287128e+05  0.983192  0.516398  2.529822   56.013391\n",
       "min    7765.000000  4.680000e+05  2.000000  1.000000  2.000000  100.000000\n",
       "25%    8064.000000  8.962500e+05  3.000000  1.000000  3.250000  111.250000\n",
       "50%    8604.000000  1.200000e+06  3.000000  1.000000  4.500000  117.500000\n",
       "75%    8610.000000  1.308750e+06  3.000000  1.750000  7.250000  127.500000\n",
       "max    8708.000000  1.690000e+06  5.000000  2.000000  8.000000  250.000000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#m2 için ; Q1(first quartile, %25)=111.25, Q2=(second quartile ,%50,median )=117.5,  Q3(third quartile,%75)=127.5, \n",
    "#min=100, max=250, IQR=Q3-Q1=127.5-111.25=16,25 (Boxplot'ta daha iyi gözükecek)\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x11ab99610>,\n",
       "  <matplotlib.lines.Line2D at 0x11ab9e750>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x11ab99210>,\n",
       "  <matplotlib.lines.Line2D at 0x11ab91790>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x11ab995d0>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x11aba5650>],\n",
       " 'fliers': [],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 11,
     "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": [
    "Q1 = df[\"m2\"].quantile(0.25)\n",
    "Q3 = df[\"m2\"].quantile(0.75)\n",
    "median=df[\"m2\"].quantile(0.50)\n",
    "IQR = Q3 - Q1\n",
    "outlier1 = Q1 - 1.5 * IQR\n",
    "outlier2= Q3 + 1.5 * IQR\n",
    "          \n",
    "Qs = [Q1, median, Q3, outlier1, outlier2,IQR]\n",
    "Qname = [\"Q1\", \"median\", \"Q3\", \"outlier\", \"outlier\",\"IQR\"]\n",
    "for Q, name in zip(Qs, Qname):\n",
    "       plt.axhline(Q)\n",
    "       plt.text(1.55,Q, name)\n",
    "\n",
    "plt.boxplot(df.m2,showfliers=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}