1-1-pandas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\">\n",
    "    <b><h2>Pandas Kütüphanesi</h2></b> <br>\n",
    "    Pandas kütüphanesi veriler üzerindeki yapacağımız işlemlerin kolaylığı için geliştirilmiş bir kütüphanesi. BSD lisanslı açık kaynaklıdır.\n",
    "    <br> Kütüphane yüklü değil ise <i><b>pip install pandas</b></i> ile yükleyebilirsiniz.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bu bölümde işlenecek konular\n",
    "\n",
    "1. [Pandas import etme](#bir)\n",
    "2. [Dosya okuma](#iki)\n",
    "3. [Veri içeriği görme](#uc)\n",
    "4. [Veri istatistiki bilgiler](#dort)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div id=\"bir\" style=\"color:blue;\"> 1. Pandas import etme </div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div id=\"iki\"  style=\"color:blue;\"> 2. Dosya okuma işlemi </div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv('./Data/melbourne-housing-snapshot/melb_data.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div id=\"uc\"  style=\"color:blue;\"> 3. Veri içeriğine genel bir bakış </div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Suburb</th>\n",
       "      <th>Address</th>\n",
       "      <th>Rooms</th>\n",
       "      <th>Type</th>\n",
       "      <th>Price</th>\n",
       "      <th>Method</th>\n",
       "      <th>SellerG</th>\n",
       "      <th>Date</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Postcode</th>\n",
       "      <th>...</th>\n",
       "      <th>Bathroom</th>\n",
       "      <th>Car</th>\n",
       "      <th>Landsize</th>\n",
       "      <th>BuildingArea</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>CouncilArea</th>\n",
       "      <th>Lattitude</th>\n",
       "      <th>Longtitude</th>\n",
       "      <th>Regionname</th>\n",
       "      <th>Propertycount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Abbotsford</td>\n",
       "      <td>85 Turner St</td>\n",
       "      <td>2</td>\n",
       "      <td>h</td>\n",
       "      <td>1480000.0</td>\n",
       "      <td>S</td>\n",
       "      <td>Biggin</td>\n",
       "      <td>3/12/2016</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3067.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yarra</td>\n",
       "      <td>-37.7996</td>\n",
       "      <td>144.9984</td>\n",
       "      <td>Northern Metropolitan</td>\n",
       "      <td>4019.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Abbotsford</td>\n",
       "      <td>25 Bloomburg St</td>\n",
       "      <td>2</td>\n",
       "      <td>h</td>\n",
       "      <td>1035000.0</td>\n",
       "      <td>S</td>\n",
       "      <td>Biggin</td>\n",
       "      <td>4/02/2016</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3067.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>Yarra</td>\n",
       "      <td>-37.8079</td>\n",
       "      <td>144.9934</td>\n",
       "      <td>Northern Metropolitan</td>\n",
       "      <td>4019.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Abbotsford</td>\n",
       "      <td>5 Charles St</td>\n",
       "      <td>3</td>\n",
       "      <td>h</td>\n",
       "      <td>1465000.0</td>\n",
       "      <td>SP</td>\n",
       "      <td>Biggin</td>\n",
       "      <td>4/03/2017</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3067.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>Yarra</td>\n",
       "      <td>-37.8093</td>\n",
       "      <td>144.9944</td>\n",
       "      <td>Northern Metropolitan</td>\n",
       "      <td>4019.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Abbotsford</td>\n",
       "      <td>40 Federation La</td>\n",
       "      <td>3</td>\n",
       "      <td>h</td>\n",
       "      <td>850000.0</td>\n",
       "      <td>PI</td>\n",
       "      <td>Biggin</td>\n",
       "      <td>4/03/2017</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3067.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yarra</td>\n",
       "      <td>-37.7969</td>\n",
       "      <td>144.9969</td>\n",
       "      <td>Northern Metropolitan</td>\n",
       "      <td>4019.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Abbotsford</td>\n",
       "      <td>55a Park St</td>\n",
       "      <td>4</td>\n",
       "      <td>h</td>\n",
       "      <td>1600000.0</td>\n",
       "      <td>VB</td>\n",
       "      <td>Nelson</td>\n",
       "      <td>4/06/2016</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3067.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Yarra</td>\n",
       "      <td>-37.8072</td>\n",
       "      <td>144.9941</td>\n",
       "      <td>Northern Metropolitan</td>\n",
       "      <td>4019.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Suburb           Address  Rooms Type      Price Method SellerG  \\\n",
       "0  Abbotsford      85 Turner St      2    h  1480000.0      S  Biggin   \n",
       "1  Abbotsford   25 Bloomburg St      2    h  1035000.0      S  Biggin   \n",
       "2  Abbotsford      5 Charles St      3    h  1465000.0     SP  Biggin   \n",
       "3  Abbotsford  40 Federation La      3    h   850000.0     PI  Biggin   \n",
       "4  Abbotsford       55a Park St      4    h  1600000.0     VB  Nelson   \n",
       "\n",
       "        Date  Distance  Postcode  ...  Bathroom  Car  Landsize  BuildingArea  \\\n",
       "0  3/12/2016       2.5    3067.0  ...       1.0  1.0     202.0           NaN   \n",
       "1  4/02/2016       2.5    3067.0  ...       1.0  0.0     156.0          79.0   \n",
       "2  4/03/2017       2.5    3067.0  ...       2.0  0.0     134.0         150.0   \n",
       "3  4/03/2017       2.5    3067.0  ...       2.0  1.0      94.0           NaN   \n",
       "4  4/06/2016       2.5    3067.0  ...       1.0  2.0     120.0         142.0   \n",
       "\n",
       "   YearBuilt  CouncilArea Lattitude  Longtitude             Regionname  \\\n",
       "0        NaN        Yarra  -37.7996    144.9984  Northern Metropolitan   \n",
       "1     1900.0        Yarra  -37.8079    144.9934  Northern Metropolitan   \n",
       "2     1900.0        Yarra  -37.8093    144.9944  Northern Metropolitan   \n",
       "3        NaN        Yarra  -37.7969    144.9969  Northern Metropolitan   \n",
       "4     2014.0        Yarra  -37.8072    144.9941  Northern Metropolitan   \n",
       "\n",
       "  Propertycount  \n",
       "0        4019.0  \n",
       "1        4019.0  \n",
       "2        4019.0  \n",
       "3        4019.0  \n",
       "4        4019.0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div id=\"dort\"  style=\"color:blue;\"> 4. Veri istatistiki bilgiler </div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rooms</th>\n",
       "      <th>Price</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Bedroom2</th>\n",
       "      <th>Bathroom</th>\n",
       "      <th>Car</th>\n",
       "      <th>Landsize</th>\n",
       "      <th>BuildingArea</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>Lattitude</th>\n",
       "      <th>Longtitude</th>\n",
       "      <th>Propertycount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>13580.000000</td>\n",
       "      <td>1.358000e+04</td>\n",
       "      <td>13580.000000</td>\n",
       "      <td>13580.000000</td>\n",
       "      <td>13580.000000</td>\n",
       "      <td>13580.000000</td>\n",
       "      <td>13518.000000</td>\n",
       "      <td>13580.000000</td>\n",
       "      <td>7130.000000</td>\n",
       "      <td>8205.000000</td>\n",
       "      <td>13580.000000</td>\n",
       "      <td>13580.000000</td>\n",
       "      <td>13580.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.937997</td>\n",
       "      <td>1.075684e+06</td>\n",
       "      <td>10.137776</td>\n",
       "      <td>3105.301915</td>\n",
       "      <td>2.914728</td>\n",
       "      <td>1.534242</td>\n",
       "      <td>1.610075</td>\n",
       "      <td>558.416127</td>\n",
       "      <td>151.967650</td>\n",
       "      <td>1964.684217</td>\n",
       "      <td>-37.809203</td>\n",
       "      <td>144.995216</td>\n",
       "      <td>7454.417378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.955748</td>\n",
       "      <td>6.393107e+05</td>\n",
       "      <td>5.868725</td>\n",
       "      <td>90.676964</td>\n",
       "      <td>0.965921</td>\n",
       "      <td>0.691712</td>\n",
       "      <td>0.962634</td>\n",
       "      <td>3990.669241</td>\n",
       "      <td>541.014538</td>\n",
       "      <td>37.273762</td>\n",
       "      <td>0.079260</td>\n",
       "      <td>0.103916</td>\n",
       "      <td>4378.581772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.500000e+04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1196.000000</td>\n",
       "      <td>-38.182550</td>\n",
       "      <td>144.431810</td>\n",
       "      <td>249.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>6.500000e+05</td>\n",
       "      <td>6.100000</td>\n",
       "      <td>3044.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>177.000000</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>1940.000000</td>\n",
       "      <td>-37.856822</td>\n",
       "      <td>144.929600</td>\n",
       "      <td>4380.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.030000e+05</td>\n",
       "      <td>9.200000</td>\n",
       "      <td>3084.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>440.000000</td>\n",
       "      <td>126.000000</td>\n",
       "      <td>1970.000000</td>\n",
       "      <td>-37.802355</td>\n",
       "      <td>145.000100</td>\n",
       "      <td>6555.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.330000e+06</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>3148.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>651.000000</td>\n",
       "      <td>174.000000</td>\n",
       "      <td>1999.000000</td>\n",
       "      <td>-37.756400</td>\n",
       "      <td>145.058305</td>\n",
       "      <td>10331.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.000000e+06</td>\n",
       "      <td>48.100000</td>\n",
       "      <td>3977.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>433014.000000</td>\n",
       "      <td>44515.000000</td>\n",
       "      <td>2018.000000</td>\n",
       "      <td>-37.408530</td>\n",
       "      <td>145.526350</td>\n",
       "      <td>21650.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Rooms         Price      Distance      Postcode      Bedroom2  \\\n",
       "count  13580.000000  1.358000e+04  13580.000000  13580.000000  13580.000000   \n",
       "mean       2.937997  1.075684e+06     10.137776   3105.301915      2.914728   \n",
       "std        0.955748  6.393107e+05      5.868725     90.676964      0.965921   \n",
       "min        1.000000  8.500000e+04      0.000000   3000.000000      0.000000   \n",
       "25%        2.000000  6.500000e+05      6.100000   3044.000000      2.000000   \n",
       "50%        3.000000  9.030000e+05      9.200000   3084.000000      3.000000   \n",
       "75%        3.000000  1.330000e+06     13.000000   3148.000000      3.000000   \n",
       "max       10.000000  9.000000e+06     48.100000   3977.000000     20.000000   \n",
       "\n",
       "           Bathroom           Car       Landsize  BuildingArea    YearBuilt  \\\n",
       "count  13580.000000  13518.000000   13580.000000   7130.000000  8205.000000   \n",
       "mean       1.534242      1.610075     558.416127    151.967650  1964.684217   \n",
       "std        0.691712      0.962634    3990.669241    541.014538    37.273762   \n",
       "min        0.000000      0.000000       0.000000      0.000000  1196.000000   \n",
       "25%        1.000000      1.000000     177.000000     93.000000  1940.000000   \n",
       "50%        1.000000      2.000000     440.000000    126.000000  1970.000000   \n",
       "75%        2.000000      2.000000     651.000000    174.000000  1999.000000   \n",
       "max        8.000000     10.000000  433014.000000  44515.000000  2018.000000   \n",
       "\n",
       "          Lattitude    Longtitude  Propertycount  \n",
       "count  13580.000000  13580.000000   13580.000000  \n",
       "mean     -37.809203    144.995216    7454.417378  \n",
       "std        0.079260      0.103916    4378.581772  \n",
       "min      -38.182550    144.431810     249.000000  \n",
       "25%      -37.856822    144.929600    4380.000000  \n",
       "50%      -37.802355    145.000100    6555.000000  \n",
       "75%      -37.756400    145.058305   10331.000000  \n",
       "max      -37.408530    145.526350   21650.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 13580 entries, 0 to 13579\n",
      "Data columns (total 21 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Suburb         13580 non-null  object \n",
      " 1   Address        13580 non-null  object \n",
      " 2   Rooms          13580 non-null  int64  \n",
      " 3   Type           13580 non-null  object \n",
      " 4   Price          13580 non-null  float64\n",
      " 5   Method         13580 non-null  object \n",
      " 6   SellerG        13580 non-null  object \n",
      " 7   Date           13580 non-null  object \n",
      " 8   Distance       13580 non-null  float64\n",
      " 9   Postcode       13580 non-null  float64\n",
      " 10  Bedroom2       13580 non-null  float64\n",
      " 11  Bathroom       13580 non-null  float64\n",
      " 12  Car            13518 non-null  float64\n",
      " 13  Landsize       13580 non-null  float64\n",
      " 14  BuildingArea   7130 non-null   float64\n",
      " 15  YearBuilt      8205 non-null   float64\n",
      " 16  CouncilArea    12211 non-null  object \n",
      " 17  Lattitude      13580 non-null  float64\n",
      " 18  Longtitude     13580 non-null  float64\n",
      " 19  Regionname     13580 non-null  object \n",
      " 20  Propertycount  13580 non-null  float64\n",
      "dtypes: float64(12), int64(1), object(8)\n",
      "memory usage: 2.2+ MB\n"
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    "data.info()"
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