Divar Clustering and Classification.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Definition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 924,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import xlsxwriter\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn import preprocessing\n",
    "from sklearn import svm\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import average_precision_score\n",
    "from sklearn.metrics import precision_recall_curve\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.metrics import auc\n",
    "from sklearn.metrics import average_precision_score\n",
    "from sklearn.metrics import roc_curve\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from inspect import signature\n",
    "from matplotlib import pyplot\n",
    "\n",
    "%matplotlib inline\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read From Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 925,
   "metadata": {},
   "outputs": [],
   "source": [
    "writer = pd.ExcelWriter('Divar Split.xlsx',  \n",
    "                   engine ='xlsxwriter') \n",
    "df = pd.read_csv('divar_posts_dataset.csv', \n",
    "            header=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preproccessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 926,
   "metadata": {},
   "outputs": [],
   "source": [
    "column_names = ['mileage','price','year']\n",
    "df_vehicle = df[(df['cat2']=='cars') & (df['price']!=-1) & (df['cat3']=='light')]\n",
    "# Correct year column\n",
    "df_vehicle['year'] = df_vehicle['year'].str.replace('[\\W_]+', '')\n",
    "# Convert Toman to Rial\n",
    "df_vehicle['price'] = df_vehicle['price'].apply(lambda x: x * 1000 if x < 100000 else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 927,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_vehicle['mileage'] = pd.to_numeric(df_vehicle['mileage'])\n",
    "df_vehicle['price'] = pd.to_numeric(df_vehicle['price'])\n",
    "df_vehicle['year'] = pd.to_numeric(df_vehicle['year'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 928,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pride = df_vehicle[df_vehicle['brand'] == 'پراید صندوق‌دار::Pride']\n",
    "df_peugeot206 = df_vehicle[df_vehicle['brand'] == 'پژو ۲۰۶‍::Peugeot 206']\n",
    "df_peugeot405 = df_vehicle[df_vehicle['brand'] == 'پژو ۴۰۵::Peugeot 405']\n",
    "df_pride['ID'] = np.arange(len(df_pride))\n",
    "df_peugeot206['ID'] = np.arange(len(df_peugeot206))\n",
    "df_peugeot405['ID'] = np.arange(len(df_peugeot405))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 929,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>پژو 2000فنی تازه تعمیر بدنه بدون خطو خش تخیف ب...</td>\n",
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       "      <td>8500000</td>\n",
       "      <td>پژو مدل 81 مشکی</td>\n",
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       "      <td>1381</td>\n",
       "      <td>0</td>\n",
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       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Thursday 08AM</td>\n",
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       "      <td>2.080630e+13</td>\n",
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       "      <td>125000.0</td>\n",
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       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Sunday 08AM</td>\n",
       "      <td>از لحاظ متوری تمیز . بدون مشکل . کاپوت و گلگیر...</td>\n",
       "      <td>2.611290e+13</td>\n",
       "      <td>2</td>\n",
       "      <td>160.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>21000000</td>\n",
       "      <td>پژو ۴۰۵ TU5 بسیار تمیز</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1392</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>173</th>\n",
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       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
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       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Wednesday 04PM</td>\n",
       "      <td>پژو تمیز و خوش رخ کم کارکرد،بیمه تا خرداد ٩٦،ع...</td>\n",
       "      <td>5.171940e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>18500000</td>\n",
       "      <td>تمیز بدون خط و خش</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1389</td>\n",
       "      <td>3</td>\n",
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       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Monday 08AM</td>\n",
       "      <td>رنگ نوک مدادی متالیک دوگانه سوز ال پی جی بیمه ...</td>\n",
       "      <td>5.492980e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>220.0</td>\n",
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       "      <td>12500000</td>\n",
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       "      <td>4</td>\n",
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       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Tuesday 12PM</td>\n",
       "      <td>پژو405 دوگانه کارخانه دلفینی فوق العاده تمیز ب...</td>\n",
       "      <td>6.721290e+13</td>\n",
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       "      <td>Mashhad</td>\n",
       "      <td>Tuesday 05PM</td>\n",
       "      <td>۴۰۵ مدل ۱۹۹۴ میلادی که میشه ۱۳۷۳ بدون رنگ سقف ...</td>\n",
       "      <td>4.021700e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>379000.0</td>\n",
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       "      <td>7500000</td>\n",
       "      <td>پژو ۴۰۵ فرانسه سفارش روسیه</td>\n",
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       "      <td>1373</td>\n",
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       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Karaj</td>\n",
       "      <td>Thursday 02PM</td>\n",
       "      <td>عقب وجلو پلمپ بیمه تا برج 12 تخفیف 8 سال دوگان...</td>\n",
       "      <td>7.381540e+12</td>\n",
       "      <td>2</td>\n",
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       "      <td>5500000</td>\n",
       "      <td>پژو2000دوگانهCNG</td>\n",
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       "      <td>7</td>\n",
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       "      <td>5.950230e+13</td>\n",
       "      <td>1</td>\n",
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       "      <td>mobile</td>\n",
       "      <td>14000000</td>\n",
       "      <td>پژو 405 دوگانه سوز</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>1151</th>\n",
       "      <td>1151</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Wednesday 08AM</td>\n",
       "      <td>پژو مدل ٨٣ مشکى متالیک بیمه از اول تخفیف لاستی...</td>\n",
       "      <td>4.779760e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>145000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>10500000</td>\n",
       "      <td>پژو ٤٠٥ مدل ٨٣</td>\n",
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       "      <td>1383</td>\n",
       "      <td>9</td>\n",
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       "      <td>1172</td>\n",
       "      <td>True</td>\n",
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       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Wednesday 01PM</td>\n",
       "      <td>با سلام ماشین$NUMهست کاملا فابریکه افتابخوردگی...</td>\n",
       "      <td>1.329780e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>1111.0</td>\n",
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       "      <td>10400000</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>1381</td>\n",
       "      <td>10</td>\n",
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       "      <td>1211</td>\n",
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       "      <td>vehicles</td>\n",
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       "      <td>light</td>\n",
       "      <td>Kermanshah</td>\n",
       "      <td>Thursday 10AM</td>\n",
       "      <td>سلام.ماشین کارکردش واقعی هست.رنگ سفید.زنون.کنس...</td>\n",
       "      <td>2.345380e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>14800.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>30000000</td>\n",
       "      <td>پژو405SLX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1394</td>\n",
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       "      <td>1213</td>\n",
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       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Mashhad</td>\n",
       "      <td>Thursday 11AM</td>\n",
       "      <td>استثنایی بسیار تمیز</td>\n",
       "      <td>3.904190e+13</td>\n",
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       "      <td>18000000</td>\n",
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       "      <td>light</td>\n",
       "      <td>Kermanshah</td>\n",
       "      <td>Thursday 04PM</td>\n",
       "      <td>یه گلگیر رنگ ٬بیمه تا برج ۲تخفیف کامل٬موتور تا...</td>\n",
       "      <td>2.752000e+13</td>\n",
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       "      <td>15000000</td>\n",
       "      <td>پژو ۴۰۵</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1383</td>\n",
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       "      <td>1269</td>\n",
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       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
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       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Friday 03PM</td>\n",
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       "      <td>5.015920e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>11000000</td>\n",
       "      <td>پژو ۴٠۵  gl</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1383</td>\n",
       "      <td>14</td>\n",
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       "    <tr>\n",
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       "      <td>1580</td>\n",
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       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Saturday 02PM</td>\n",
       "      <td>بسیار تمیز بدون خط و خش\\nبازدید = خرید</td>\n",
       "      <td>1.012350e+12</td>\n",
       "      <td>2</td>\n",
       "      <td>35000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>25300000</td>\n",
       "      <td>$NUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1392</td>\n",
       "      <td>15</td>\n",
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       "    <tr>\n",
       "      <th>1742</th>\n",
       "      <td>1742</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Tuesday 06AM</td>\n",
       "      <td>دارای دو مانیتور برای سرنشینان عقب\\nرینگ اسپرت...</td>\n",
       "      <td>2.179580e+13</td>\n",
       "      <td>4</td>\n",
       "      <td>130000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>20000000</td>\n",
       "      <td>پژو اتومات 1388</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1388</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1885</th>\n",
       "      <td>1885</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tabriz</td>\n",
       "      <td>Thursday 07PM</td>\n",
       "      <td>رینگ اسپرت.موتور 6ماه تعمیر شده.سیستم صوتی قوی...</td>\n",
       "      <td>3.924910e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>7500000</td>\n",
       "      <td>پژو$NUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1374</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2130</th>\n",
       "      <td>2130</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Mashhad</td>\n",
       "      <td>Tuesday 12PM</td>\n",
       "      <td>مدل۸۵نقره ای فنی سالم به شرط،اتاق سرپا وخوب فق...</td>\n",
       "      <td>3.054940e+13</td>\n",
       "      <td>2</td>\n",
       "      <td>310000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>15400000</td>\n",
       "      <td>پژو۴۰۵تک</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1385</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2150</th>\n",
       "      <td>2150</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Tuesday 06PM</td>\n",
       "      <td>مشکی.بدون خط و خش..بیمه یکماه..فنی سالم.ضبط باند.</td>\n",
       "      <td>1.046010e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>900000</td>\n",
       "      <td>پژو 84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1384</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2312</th>\n",
       "      <td>2312</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Friday 10PM</td>\n",
       "      <td>ماشین سالم و خونگی</td>\n",
       "      <td>4.882940e+13</td>\n",
       "      <td>2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>21200000</td>\n",
       "      <td>پژو ۴۰۵</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1390</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2350</th>\n",
       "      <td>2350</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Saturday 03PM</td>\n",
       "      <td>شیشه دودی-لاستیک کره ای -صندلی چرم</td>\n",
       "      <td>2.444570e+13</td>\n",
       "      <td>4</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>23800000</td>\n",
       "      <td>پژوGLX 405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1393</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2460</th>\n",
       "      <td>2460</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Monday 08AM</td>\n",
       "      <td>تخفیف بیمه کامل-فروش فوری</td>\n",
       "      <td>9.860910e+12</td>\n",
       "      <td>3</td>\n",
       "      <td>395000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>15000000</td>\n",
       "      <td>تاکسی پژو</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1386</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2507</th>\n",
       "      <td>2507</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Tuesday 04AM</td>\n",
       "      <td>پژو405مدل84بیمه تابرج12،دارای تخفیف بیمه،موتور...</td>\n",
       "      <td>5.956590e+12</td>\n",
       "      <td>2</td>\n",
       "      <td>36000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>10500000</td>\n",
       "      <td>فـروشی پژو405نقره ای،مدل84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1384</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2571</th>\n",
       "      <td>2571</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Wednesday 06AM</td>\n",
       "      <td>لبیمه برج 12فقطگلگیر عقب رنگ بدون ظربه</td>\n",
       "      <td>4.094030e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>82000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>20000000</td>\n",
       "      <td>405دوگانه کارخانه</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1391</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2676</th>\n",
       "      <td>2676</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Karaj</td>\n",
       "      <td>Friday 07AM</td>\n",
       "      <td>پژو 405 مدل 93 داشبورد جدید 2 ایربک خاکستری\\nب...</td>\n",
       "      <td>4.009830e+13</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>24600000</td>\n",
       "      <td>پژو 405 خاکستری 93کم کار</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1393</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2695</th>\n",
       "      <td>2695</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Qom</td>\n",
       "      <td>Friday 05PM</td>\n",
       "      <td>با سلام ماشین فوق ازنظر فنی به شرط میدم ، بیمه...</td>\n",
       "      <td>4.733900e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>19500000</td>\n",
       "      <td>پژو فوق‌العاده بیرنگ</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1388</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2770</th>\n",
       "      <td>2770</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Kermanshah</td>\n",
       "      <td>Sunday 07AM</td>\n",
       "      <td>پژو405نقره ای.تکسوز.مدل93.بدون رنگ وخط وخش باک...</td>\n",
       "      <td>5.282310e+13</td>\n",
       "      <td>2</td>\n",
       "      <td>35000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>26500000</td>\n",
       "      <td>پژو93داشبوردجدید</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1393</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2928</th>\n",
       "      <td>2928</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Tuesday 03PM</td>\n",
       "      <td>ماشین از نظر فنی سالم-بدون رنگ-رینگ  اسپرت-بیم...</td>\n",
       "      <td>4.502310e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>163000.0</td>\n",
       "      <td>web</td>\n",
       "      <td>18300000</td>\n",
       "      <td>پژو405مشکی متالیک</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1388</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2948</th>\n",
       "      <td>2948</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Wednesday 03AM</td>\n",
       "      <td>عقب جلو پلمپ سر کاپوت رنگ داره فنی موتور به شر...</td>\n",
       "      <td>3.839390e+13</td>\n",
       "      <td>4</td>\n",
       "      <td>184000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>13000000</td>\n",
       "      <td>پژو405 مدل 83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1383</td>\n",
       "      <td>29</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>944483</th>\n",
       "      <td>944483</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Sunday 08AM</td>\n",
       "      <td>سلام. لطفا زنگ بزنید اطلاعات بدم</td>\n",
       "      <td>2.687890e+12</td>\n",
       "      <td>3</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>19000000</td>\n",
       "      <td>پژو.بدون رنگ89</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1389</td>\n",
       "      <td>10165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>944740</th>\n",
       "      <td>944740</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Thursday 05PM</td>\n",
       "      <td>سند دست اول . کارکرد واقعی و چند لکه رنگ.موتور...</td>\n",
       "      <td>3.077740e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>230000.0</td>\n",
       "      <td>web</td>\n",
       "      <td>6500000</td>\n",
       "      <td>پژو 405 glx</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1373</td>\n",
       "      <td>10166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>944937</th>\n",
       "      <td>944937</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Monday 12PM</td>\n",
       "      <td>پژو فوق‌العاده سالم و استثنائی</td>\n",
       "      <td>2.043380e+12</td>\n",
       "      <td>3</td>\n",
       "      <td>270.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>19800000</td>\n",
       "      <td>پژو</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1389</td>\n",
       "      <td>10167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945193</th>\n",
       "      <td>945193</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Saturday 11AM</td>\n",
       "      <td>فروش جهت فروش</td>\n",
       "      <td>6.132260e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>15000000</td>\n",
       "      <td>پژو 405 مدل 93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1393</td>\n",
       "      <td>10168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945198</th>\n",
       "      <td>945198</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Karaj</td>\n",
       "      <td>Saturday 12PM</td>\n",
       "      <td>سلام ماشین دارای لاستیک کره ای نو ،روکش و کف پ...</td>\n",
       "      <td>8.340650e+12</td>\n",
       "      <td>4</td>\n",
       "      <td>140000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>22000000</td>\n",
       "      <td>405  tu5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1390</td>\n",
       "      <td>10169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945230</th>\n",
       "      <td>945230</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Sunday 05AM</td>\n",
       "      <td>بدون رنگ بدون خط وخش، کارکرد$NUMواقعی، دارای ر...</td>\n",
       "      <td>2.149320e+13</td>\n",
       "      <td>4</td>\n",
       "      <td>62000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>23000000</td>\n",
       "      <td>پژو ۴۰۵ کم کارکرد</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1389</td>\n",
       "      <td>10170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945240</th>\n",
       "      <td>945240</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Mashhad</td>\n",
       "      <td>Sunday 08AM</td>\n",
       "      <td>کمی رنگ دارد شاستی سالم فنی سالم</td>\n",
       "      <td>6.062930e+13</td>\n",
       "      <td>2</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>17500000</td>\n",
       "      <td>پڑو405 سفید مدل90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1390</td>\n",
       "      <td>10171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945275</th>\n",
       "      <td>945275</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Karaj</td>\n",
       "      <td>Sunday 07PM</td>\n",
       "      <td>سلام تاکسی پژو برون شهری مدل86فوقلعاده سالم بی...</td>\n",
       "      <td>1.123360e+13</td>\n",
       "      <td>4</td>\n",
       "      <td>550.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>18000000</td>\n",
       "      <td>تاکسی پژو 405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1386</td>\n",
       "      <td>10172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945299</th>\n",
       "      <td>945299</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Karaj</td>\n",
       "      <td>Monday 12PM</td>\n",
       "      <td>چن لکه رنگ دارد  فنی بسیار سالم اتاق بدون صدا ...</td>\n",
       "      <td>3.952280e+13</td>\n",
       "      <td>4</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>19500000</td>\n",
       "      <td>پژواس ال ایکس</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1389</td>\n",
       "      <td>10173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945354</th>\n",
       "      <td>945354</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Tuesday 01PM</td>\n",
       "      <td>سلام.اخر84با1سال بیمه.1سال معاینه.5سال تخفیف.س...</td>\n",
       "      <td>1.752780e+13</td>\n",
       "      <td>4</td>\n",
       "      <td>173000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>9700000</td>\n",
       "      <td>پژو405عنابی اخر84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1384</td>\n",
       "      <td>10174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945409</th>\n",
       "      <td>945409</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Wednesday 03PM</td>\n",
       "      <td>باسلام\\nخودروبسیار تمیز درحد 90.\\nدزگیر.10سال ...</td>\n",
       "      <td>8.885060e+12</td>\n",
       "      <td>3</td>\n",
       "      <td>113.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>15000000</td>\n",
       "      <td>پژو405 دوگانه</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1385</td>\n",
       "      <td>10175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945480</th>\n",
       "      <td>945480</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Karaj</td>\n",
       "      <td>Thursday 05PM</td>\n",
       "      <td>با سلام.پژو 405 مدل اسفند91 بیمه داردباتخفیف. ...</td>\n",
       "      <td>2.269270e+13</td>\n",
       "      <td>4</td>\n",
       "      <td>80000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>14000000</td>\n",
       "      <td>فروش پژو 405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1392</td>\n",
       "      <td>10176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945481</th>\n",
       "      <td>945481</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Thursday 05PM</td>\n",
       "      <td>2 سال تخفیف بیمه تا 96/7 \\nشیشه دودی دزدگیر ژا...</td>\n",
       "      <td>2.694700e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>44000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>25800000</td>\n",
       "      <td>پژو نوک مدادی داشبورد جدید</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1393</td>\n",
       "      <td>10177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945527</th>\n",
       "      <td>945527</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Kermanshah</td>\n",
       "      <td>Friday 01PM</td>\n",
       "      <td>ماشین 1سال بیمه 6سال تخفیف،لاستیک 90،دوگانه دس...</td>\n",
       "      <td>3.238220e+13</td>\n",
       "      <td>2</td>\n",
       "      <td>271000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>16300000</td>\n",
       "      <td>پزو405تمیز</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1385</td>\n",
       "      <td>10178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945575</th>\n",
       "      <td>945575</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Saturday 04PM</td>\n",
       "      <td>بیمه تابرج١٢.شش سال تخفیف بیمه.موتوروگیربکس بش...</td>\n",
       "      <td>3.366330e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>213.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>7500000</td>\n",
       "      <td>پژو٤٠٥مدل٧٨دوگانهlpg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1378</td>\n",
       "      <td>10179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945666</th>\n",
       "      <td>945666</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Mashhad</td>\n",
       "      <td>Monday 08AM</td>\n",
       "      <td>یک گلگیر رنگ. بیمه 10ماه. تخفیف از اول.</td>\n",
       "      <td>3.692680e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>130.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>17700000</td>\n",
       "      <td>پژو405مدل 1388</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1388</td>\n",
       "      <td>10180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945674</th>\n",
       "      <td>945674</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Karaj</td>\n",
       "      <td>Monday 10AM</td>\n",
       "      <td>همه قطعات موتور یا تعویض یا تعمیر شده \\nخریدار...</td>\n",
       "      <td>5.107310e+12</td>\n",
       "      <td>2</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>7000000</td>\n",
       "      <td>پژو دوهزار موتور تازه تعمیر</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1379</td>\n",
       "      <td>10181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945732</th>\n",
       "      <td>945732</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Mashhad</td>\n",
       "      <td>Tuesday 01PM</td>\n",
       "      <td>پژو405 یک گلگیر رنگ بیمه برج 4 لاستیک نو قیمت ...</td>\n",
       "      <td>2.424900e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>34000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>25500000</td>\n",
       "      <td>پژو405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1394</td>\n",
       "      <td>10182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945767</th>\n",
       "      <td>945767</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Ahvaz</td>\n",
       "      <td>Wednesday 05AM</td>\n",
       "      <td>شرایطی  ۳چکه  تماس بگیرید توضیح میدم</td>\n",
       "      <td>1.485240e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>29000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>20000000</td>\n",
       "      <td>پژو    s l x    tu5   95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1395</td>\n",
       "      <td>10183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945862</th>\n",
       "      <td>945862</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Thursday 08PM</td>\n",
       "      <td>405 جی ال ایکس \\nبدون رنگ \\nتک سوز \\nرنگ نوک م...</td>\n",
       "      <td>5.786380e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>43000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>24000000</td>\n",
       "      <td>فروش ماشین</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1392</td>\n",
       "      <td>10184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945911</th>\n",
       "      <td>945911</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Mashhad</td>\n",
       "      <td>Friday 08PM</td>\n",
       "      <td>فنی بسیارسالم بیمه تا اول ده داره از اول تخفیف...</td>\n",
       "      <td>4.426480e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>19200000</td>\n",
       "      <td>٤٠٥دوگانه کارخانه</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1388</td>\n",
       "      <td>10185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946101</th>\n",
       "      <td>946101</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Qom</td>\n",
       "      <td>Tuesday 06AM</td>\n",
       "      <td>با سلام دو ماهه گرفتمش بدون هیچگونه خط و خشی</td>\n",
       "      <td>1.454000e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>29300000</td>\n",
       "      <td>پژو خاکستری</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1395</td>\n",
       "      <td>10186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946165</th>\n",
       "      <td>946165</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Wednesday 08AM</td>\n",
       "      <td>فرانسوی اصل دوگانه سوزرنگ بژکاملاخانگی کولربخا...</td>\n",
       "      <td>4.298660e+12</td>\n",
       "      <td>0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>7000000</td>\n",
       "      <td>پژو405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1378</td>\n",
       "      <td>10187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946176</th>\n",
       "      <td>946176</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Wednesday 10AM</td>\n",
       "      <td>پژو405 مشکی،کم کارکرد،یکسال بیمه،فنی کاملا سالم</td>\n",
       "      <td>3.078690e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>177000.0</td>\n",
       "      <td>web</td>\n",
       "      <td>12000000</td>\n",
       "      <td>پژو405مشکی مدل 1383</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1383</td>\n",
       "      <td>10188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946334</th>\n",
       "      <td>946334</td>\n",
       "      <td>False</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Kermanshah</td>\n",
       "      <td>Saturday 03AM</td>\n",
       "      <td>ﺑﺎ ﺳﻼﻡ.\\nﺩﻭﮔﺎﻧﻪ ﺳﻲ اﻥ ﺟﻲ, ﻻﺳﺘﻴﻜﻬﺎ ﻧﻮ, ﺑﻴﻤﻪ ﺗﺎ ...</td>\n",
       "      <td>1.004410e+13</td>\n",
       "      <td>4</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>10500000</td>\n",
       "      <td>ﭘﮋﻭ 405 ﺟﻲ اﻝ اﻳﻜﺲ ﺩﻭﮔﺎﻧﻪ ﺩﺳﺖ</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1383</td>\n",
       "      <td>10189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946473</th>\n",
       "      <td>946473</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Monday 09PM</td>\n",
       "      <td>پژو405دوگانه سوز رنگ نوک مدادی بدون کوچکترین خ...</td>\n",
       "      <td>3.687270e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>web</td>\n",
       "      <td>29500000</td>\n",
       "      <td>پژو405دوگانه سوز</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1394</td>\n",
       "      <td>10190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946817</th>\n",
       "      <td>946817</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Qom</td>\n",
       "      <td>Monday 05PM</td>\n",
       "      <td>لاستیک جلونو، باطری نو، دیسک وصفحه زانتیایی، ت...</td>\n",
       "      <td>6.453000e+13</td>\n",
       "      <td>3</td>\n",
       "      <td>214000.0</td>\n",
       "      <td>web</td>\n",
       "      <td>12500000</td>\n",
       "      <td>پژو جی ال آی دوگانه</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1384</td>\n",
       "      <td>10191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946989</th>\n",
       "      <td>946989</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Saturday 01PM</td>\n",
       "      <td>بدون ضربه کاملا خانگی ساعت تماس 8صبح تا 11شب</td>\n",
       "      <td>6.396820e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>36000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>23000000</td>\n",
       "      <td>خودرو 405مدل 94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1394</td>\n",
       "      <td>10192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947426</th>\n",
       "      <td>947426</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Isfahan</td>\n",
       "      <td>Sunday 08AM</td>\n",
       "      <td>ماشین فوق العاده تمییز، یک کاپوت رنگ شدگی دارد...</td>\n",
       "      <td>5.229880e+13</td>\n",
       "      <td>0</td>\n",
       "      <td>160000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>17200000</td>\n",
       "      <td>پژو جی ال ایکس تمییز</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1388</td>\n",
       "      <td>10193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947582</th>\n",
       "      <td>947582</td>\n",
       "      <td>True</td>\n",
       "      <td>پژو ۴۰۵::Peugeot 405</td>\n",
       "      <td>vehicles</td>\n",
       "      <td>cars</td>\n",
       "      <td>light</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Monday 01PM</td>\n",
       "      <td>پژو GLX تاکسی گردشی  مدل ۱۳۹۰ بسیار کم کارکرد\\...</td>\n",
       "      <td>1.561510e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>mobile</td>\n",
       "      <td>25900000</td>\n",
       "      <td>پژو 405 GLX تاکسی گردشی</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1390</td>\n",
       "      <td>10194</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10195 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0  archive_by_user                 brand      cat1  cat2  \\\n",
       "18              18            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "38              38            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "101            101            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "173            173            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "285            285            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "799            799            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "811            811            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "896            896             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1120          1120             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1151          1151             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1172          1172             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1211          1211            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1213          1213            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1227          1227            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1269          1269            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1580          1580            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1742          1742             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "1885          1885            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2130          2130             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2150          2150            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2312          2312             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2350          2350             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2460          2460             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2507          2507             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2571          2571             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2676          2676             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2695          2695             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2770          2770             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2928          2928             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "2948          2948            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "...            ...              ...                   ...       ...   ...   \n",
       "944483      944483             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "944740      944740             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "944937      944937             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945193      945193             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945198      945198             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945230      945230            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945240      945240            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945275      945275            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945299      945299            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945354      945354             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945409      945409             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945480      945480             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945481      945481             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945527      945527            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945575      945575             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945666      945666             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945674      945674            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945732      945732            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945767      945767             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945862      945862             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "945911      945911             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "946101      946101             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "946165      946165            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "946176      946176            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "946334      946334            False  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "946473      946473             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "946817      946817             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "946989      946989             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "947426      947426             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "947582      947582             True  پژو ۴۰۵::Peugeot 405  vehicles  cars   \n",
       "\n",
       "         cat3        city      created_at  \\\n",
       "18      light       Karaj  Wednesday 11AM   \n",
       "38      light      Tehran   Thursday 08AM   \n",
       "101     light      Shiraz     Sunday 08AM   \n",
       "173     light      Tehran  Wednesday 04PM   \n",
       "285     light      Tehran     Monday 08AM   \n",
       "799     light      Shiraz    Tuesday 12PM   \n",
       "811     light     Mashhad    Tuesday 05PM   \n",
       "896     light       Karaj   Thursday 02PM   \n",
       "1120    light      Tehran    Tuesday 11AM   \n",
       "1151    light      Tehran  Wednesday 08AM   \n",
       "1172    light      Shiraz  Wednesday 01PM   \n",
       "1211    light  Kermanshah   Thursday 10AM   \n",
       "1213    light     Mashhad   Thursday 11AM   \n",
       "1227    light  Kermanshah   Thursday 04PM   \n",
       "1269    light      Tehran     Friday 03PM   \n",
       "1580    light      Tehran   Saturday 02PM   \n",
       "1742    light      Tehran    Tuesday 06AM   \n",
       "1885    light      Tabriz   Thursday 07PM   \n",
       "2130    light     Mashhad    Tuesday 12PM   \n",
       "2150    light      Shiraz    Tuesday 06PM   \n",
       "2312    light      Tehran     Friday 10PM   \n",
       "2350    light      Tehran   Saturday 03PM   \n",
       "2460    light      Tehran     Monday 08AM   \n",
       "2507    light      Shiraz    Tuesday 04AM   \n",
       "2571    light      Shiraz  Wednesday 06AM   \n",
       "2676    light       Karaj     Friday 07AM   \n",
       "2695    light         Qom     Friday 05PM   \n",
       "2770    light  Kermanshah     Sunday 07AM   \n",
       "2928    light      Tehran    Tuesday 03PM   \n",
       "2948    light      Tehran  Wednesday 03AM   \n",
       "...       ...         ...             ...   \n",
       "944483  light      Tehran     Sunday 08AM   \n",
       "944740  light      Tehran   Thursday 05PM   \n",
       "944937  light      Tehran     Monday 12PM   \n",
       "945193  light      Tehran   Saturday 11AM   \n",
       "945198  light       Karaj   Saturday 12PM   \n",
       "945230  light      Tehran     Sunday 05AM   \n",
       "945240  light     Mashhad     Sunday 08AM   \n",
       "945275  light       Karaj     Sunday 07PM   \n",
       "945299  light       Karaj     Monday 12PM   \n",
       "945354  light      Tehran    Tuesday 01PM   \n",
       "945409  light      Tehran  Wednesday 03PM   \n",
       "945480  light       Karaj   Thursday 05PM   \n",
       "945481  light      Tehran   Thursday 05PM   \n",
       "945527  light  Kermanshah     Friday 01PM   \n",
       "945575  light      Shiraz   Saturday 04PM   \n",
       "945666  light     Mashhad     Monday 08AM   \n",
       "945674  light       Karaj     Monday 10AM   \n",
       "945732  light     Mashhad    Tuesday 01PM   \n",
       "945767  light       Ahvaz  Wednesday 05AM   \n",
       "945862  light      Tehran   Thursday 08PM   \n",
       "945911  light     Mashhad     Friday 08PM   \n",
       "946101  light         Qom    Tuesday 06AM   \n",
       "946165  light      Shiraz  Wednesday 08AM   \n",
       "946176  light      Tehran  Wednesday 10AM   \n",
       "946334  light  Kermanshah   Saturday 03AM   \n",
       "946473  light      Tehran     Monday 09PM   \n",
       "946817  light         Qom     Monday 05PM   \n",
       "946989  light      Shiraz   Saturday 01PM   \n",
       "947426  light     Isfahan     Sunday 08AM   \n",
       "947582  light      Tehran     Monday 01PM   \n",
       "\n",
       "                                                     desc            id  \\\n",
       "18      پژو 2000فنی تازه تعمیر بدنه بدون خطو خش تخیف ب...  5.172880e+13   \n",
       "38         بیمه یکسال ده سال تخفیف دور رنگ شاسی پلمپ سالم  2.080630e+13   \n",
       "101     از لحاظ متوری تمیز . بدون مشکل . کاپوت و گلگیر...  2.611290e+13   \n",
       "173     پژو تمیز و خوش رخ کم کارکرد،بیمه تا خرداد ٩٦،ع...  5.171940e+13   \n",
       "285     رنگ نوک مدادی متالیک دوگانه سوز ال پی جی بیمه ...  5.492980e+13   \n",
       "799     پژو405 دوگانه کارخانه دلفینی فوق العاده تمیز ب...  6.721290e+13   \n",
       "811     ۴۰۵ مدل ۱۹۹۴ میلادی که میشه ۱۳۷۳ بدون رنگ سقف ...  4.021700e+13   \n",
       "896     عقب وجلو پلمپ بیمه تا برج 12 تخفیف 8 سال دوگان...  7.381540e+12   \n",
       "1120                                   پژو 405 دوگانه سوز  5.950230e+13   \n",
       "1151    پژو مدل ٨٣ مشکى متالیک بیمه از اول تخفیف لاستی...  4.779760e+13   \n",
       "1172    با سلام ماشین$NUMهست کاملا فابریکه افتابخوردگی...  1.329780e+13   \n",
       "1211    سلام.ماشین کارکردش واقعی هست.رنگ سفید.زنون.کنس...  2.345380e+13   \n",
       "1213                                  استثنایی بسیار تمیز  3.904190e+13   \n",
       "1227    یه گلگیر رنگ ٬بیمه تا برج ۲تخفیف کامل٬موتور تا...  2.752000e+13   \n",
       "1269    فنی کاملا سالم بدون هیچ عیب و نقصی بیمه تا 12/...  5.015920e+13   \n",
       "1580               بسیار تمیز بدون خط و خش\\nبازدید = خرید  1.012350e+12   \n",
       "1742    دارای دو مانیتور برای سرنشینان عقب\\nرینگ اسپرت...  2.179580e+13   \n",
       "1885    رینگ اسپرت.موتور 6ماه تعمیر شده.سیستم صوتی قوی...  3.924910e+13   \n",
       "2130    مدل۸۵نقره ای فنی سالم به شرط،اتاق سرپا وخوب فق...  3.054940e+13   \n",
       "2150    مشکی.بدون خط و خش..بیمه یکماه..فنی سالم.ضبط باند.  1.046010e+13   \n",
       "2312                                   ماشین سالم و خونگی  4.882940e+13   \n",
       "2350                   شیشه دودی-لاستیک کره ای -صندلی چرم  2.444570e+13   \n",
       "2460                            تخفیف بیمه کامل-فروش فوری  9.860910e+12   \n",
       "2507    پژو405مدل84بیمه تابرج12،دارای تخفیف بیمه،موتور...  5.956590e+12   \n",
       "2571               لبیمه برج 12فقطگلگیر عقب رنگ بدون ظربه  4.094030e+13   \n",
       "2676    پژو 405 مدل 93 داشبورد جدید 2 ایربک خاکستری\\nب...  4.009830e+13   \n",
       "2695    با سلام ماشین فوق ازنظر فنی به شرط میدم ، بیمه...  4.733900e+13   \n",
       "2770    پژو405نقره ای.تکسوز.مدل93.بدون رنگ وخط وخش باک...  5.282310e+13   \n",
       "2928    ماشین از نظر فنی سالم-بدون رنگ-رینگ  اسپرت-بیم...  4.502310e+13   \n",
       "2948    عقب جلو پلمپ سر کاپوت رنگ داره فنی موتور به شر...  3.839390e+13   \n",
       "...                                                   ...           ...   \n",
       "944483                   سلام. لطفا زنگ بزنید اطلاعات بدم  2.687890e+12   \n",
       "944740  سند دست اول . کارکرد واقعی و چند لکه رنگ.موتور...  3.077740e+13   \n",
       "944937                     پژو فوق‌العاده سالم و استثنائی  2.043380e+12   \n",
       "945193                                      فروش جهت فروش  6.132260e+13   \n",
       "945198  سلام ماشین دارای لاستیک کره ای نو ،روکش و کف پ...  8.340650e+12   \n",
       "945230  بدون رنگ بدون خط وخش، کارکرد$NUMواقعی، دارای ر...  2.149320e+13   \n",
       "945240                   کمی رنگ دارد شاستی سالم فنی سالم  6.062930e+13   \n",
       "945275  سلام تاکسی پژو برون شهری مدل86فوقلعاده سالم بی...  1.123360e+13   \n",
       "945299  چن لکه رنگ دارد  فنی بسیار سالم اتاق بدون صدا ...  3.952280e+13   \n",
       "945354  سلام.اخر84با1سال بیمه.1سال معاینه.5سال تخفیف.س...  1.752780e+13   \n",
       "945409  باسلام\\nخودروبسیار تمیز درحد 90.\\nدزگیر.10سال ...  8.885060e+12   \n",
       "945480  با سلام.پژو 405 مدل اسفند91 بیمه داردباتخفیف. ...  2.269270e+13   \n",
       "945481  2 سال تخفیف بیمه تا 96/7 \\nشیشه دودی دزدگیر ژا...  2.694700e+13   \n",
       "945527  ماشین 1سال بیمه 6سال تخفیف،لاستیک 90،دوگانه دس...  3.238220e+13   \n",
       "945575  بیمه تابرج١٢.شش سال تخفیف بیمه.موتوروگیربکس بش...  3.366330e+13   \n",
       "945666            یک گلگیر رنگ. بیمه 10ماه. تخفیف از اول.  3.692680e+13   \n",
       "945674  همه قطعات موتور یا تعویض یا تعمیر شده \\nخریدار...  5.107310e+12   \n",
       "945732  پژو405 یک گلگیر رنگ بیمه برج 4 لاستیک نو قیمت ...  2.424900e+12   \n",
       "945767               شرایطی  ۳چکه  تماس بگیرید توضیح میدم  1.485240e+13   \n",
       "945862  405 جی ال ایکس \\nبدون رنگ \\nتک سوز \\nرنگ نوک م...  5.786380e+13   \n",
       "945911  فنی بسیارسالم بیمه تا اول ده داره از اول تخفیف...  4.426480e+13   \n",
       "946101       با سلام دو ماهه گرفتمش بدون هیچگونه خط و خشی  1.454000e+13   \n",
       "946165  فرانسوی اصل دوگانه سوزرنگ بژکاملاخانگی کولربخا...  4.298660e+12   \n",
       "946176    پژو405 مشکی،کم کارکرد،یکسال بیمه،فنی کاملا سالم  3.078690e+13   \n",
       "946334  ﺑﺎ ﺳﻼﻡ.\\nﺩﻭﮔﺎﻧﻪ ﺳﻲ اﻥ ﺟﻲ, ﻻﺳﺘﻴﻜﻬﺎ ﻧﻮ, ﺑﻴﻤﻪ ﺗﺎ ...  1.004410e+13   \n",
       "946473  پژو405دوگانه سوز رنگ نوک مدادی بدون کوچکترین خ...  3.687270e+13   \n",
       "946817  لاستیک جلونو، باطری نو، دیسک وصفحه زانتیایی، ت...  6.453000e+13   \n",
       "946989       بدون ضربه کاملا خانگی ساعت تماس 8صبح تا 11شب  6.396820e+13   \n",
       "947426  ماشین فوق العاده تمییز، یک کاپوت رنگ شدگی دارد...  5.229880e+13   \n",
       "947582  پژو GLX تاکسی گردشی  مدل ۱۳۹۰ بسیار کم کارکرد\\...  1.561510e+13   \n",
       "\n",
       "        image_count   mileage platform     price  \\\n",
       "18                0  290000.0      web   8500000   \n",
       "38                3  125000.0   mobile   8500000   \n",
       "101               2     160.0   mobile  21000000   \n",
       "173               3  120000.0   mobile  18500000   \n",
       "285               0     220.0   mobile  12500000   \n",
       "799               0    1234.0   mobile  18500000   \n",
       "811               3  379000.0   mobile   7500000   \n",
       "896               2  130000.0   mobile   5500000   \n",
       "1120              1  130000.0   mobile  14000000   \n",
       "1151              3  145000.0   mobile  10500000   \n",
       "1172              3    1111.0   mobile  10400000   \n",
       "1211              1   14800.0   mobile  30000000   \n",
       "1213              1  130000.0   mobile  18000000   \n",
       "1227              3  257000.0   mobile  15000000   \n",
       "1269              0     235.0   mobile  11000000   \n",
       "1580              2   35000.0   mobile  25300000   \n",
       "1742              4  130000.0   mobile  20000000   \n",
       "1885              1       3.0   mobile   7500000   \n",
       "2130              2  310000.0   mobile  15400000   \n",
       "2150              0   30000.0   mobile    900000   \n",
       "2312              2     130.0   mobile  21200000   \n",
       "2350              4   42000.0   mobile  23800000   \n",
       "2460              3  395000.0   mobile  15000000   \n",
       "2507              2   36000.0   mobile  10500000   \n",
       "2571              1   82000.0   mobile  20000000   \n",
       "2676              2      30.0   mobile  24600000   \n",
       "2695              1  120000.0   mobile  19500000   \n",
       "2770              2   35000.0   mobile  26500000   \n",
       "2928              3  163000.0      web  18300000   \n",
       "2948              4  184000.0   mobile  13000000   \n",
       "...             ...       ...      ...       ...   \n",
       "944483            3  117000.0   mobile  19000000   \n",
       "944740            0  230000.0      web   6500000   \n",
       "944937            3     270.0   mobile  19800000   \n",
       "945193            0   45000.0   mobile  15000000   \n",
       "945198            4  140000.0   mobile  22000000   \n",
       "945230            4   62000.0   mobile  23000000   \n",
       "945240            2   30000.0   mobile  17500000   \n",
       "945275            4     550.0   mobile  18000000   \n",
       "945299            4   11000.0   mobile  19500000   \n",
       "945354            4  173000.0   mobile   9700000   \n",
       "945409            3     113.0   mobile  15000000   \n",
       "945480            4   80000.0   mobile  14000000   \n",
       "945481            0   44000.0   mobile  25800000   \n",
       "945527            2  271000.0   mobile  16300000   \n",
       "945575            3     213.0   mobile   7500000   \n",
       "945666            3     130.0   mobile  17700000   \n",
       "945674            2  200000.0   mobile   7000000   \n",
       "945732            1   34000.0   mobile  25500000   \n",
       "945767            3   29000.0   mobile  20000000   \n",
       "945862            0   43000.0   mobile  24000000   \n",
       "945911            3  200000.0   mobile  19200000   \n",
       "946101            0    8000.0   mobile  29300000   \n",
       "946165            0  200000.0   mobile   7000000   \n",
       "946176            3  177000.0      web  12000000   \n",
       "946334            4  300000.0   mobile  10500000   \n",
       "946473            0   22000.0      web  29500000   \n",
       "946817            3  214000.0      web  12500000   \n",
       "946989            1   36000.0   mobile  23000000   \n",
       "947426            0  160000.0   mobile  17200000   \n",
       "947582            1  120000.0   mobile  25900000   \n",
       "\n",
       "                                title type  year     ID  \n",
       "18                    پژو مدل 81 مشکی  NaN  1381      0  \n",
       "38                       پژو405 مدل84  NaN  1384      1  \n",
       "101            پژو ۴۰۵ TU5 بسیار تمیز  NaN  1392      2  \n",
       "173                 تمیز بدون خط و خش  NaN  1389      3  \n",
       "285                  پژو 405 مدل 1383  NaN  1383      4  \n",
       "799             پژو405 دوگانه کارخانه  NaN  1387      5  \n",
       "811        پژو ۴۰۵ فرانسه سفارش روسیه  NaN  1373      6  \n",
       "896                  پژو2000دوگانهCNG  NaN  1380      7  \n",
       "1120               پژو 405 دوگانه سوز  NaN  1386      8  \n",
       "1151                   پژو ٤٠٥ مدل ٨٣  NaN  1383      9  \n",
       "1172                   405تعویض با۱۱۱  NaN  1381     10  \n",
       "1211                        پژو405SLX  NaN  1394     11  \n",
       "1213    بدون رنگ  موتوری سالم وکم کار  NaN  1386     12  \n",
       "1227                          پژو ۴۰۵  NaN  1383     13  \n",
       "1269                      پژو ۴٠۵  gl  NaN  1383     14  \n",
       "1580                             $NUM  NaN  1392     15  \n",
       "1742                  پژو اتومات 1388  NaN  1388     16  \n",
       "1885                          پژو$NUM  NaN  1374     17  \n",
       "2130                         پژو۴۰۵تک  NaN  1385     18  \n",
       "2150                           پژو 84  NaN  1384     19  \n",
       "2312                          پژو ۴۰۵  NaN  1390     20  \n",
       "2350                       پژوGLX 405  NaN  1393     21  \n",
       "2460                        تاکسی پژو  NaN  1386     22  \n",
       "2507       فـروشی پژو405نقره ای،مدل84  NaN  1384     23  \n",
       "2571                405دوگانه کارخانه  NaN  1391     24  \n",
       "2676         پژو 405 خاکستری 93کم کار  NaN  1393     25  \n",
       "2695             پژو فوق‌العاده بیرنگ  NaN  1388     26  \n",
       "2770                 پژو93داشبوردجدید  NaN  1393     27  \n",
       "2928                پژو405مشکی متالیک  NaN  1388     28  \n",
       "2948                    پژو405 مدل 83  NaN  1383     29  \n",
       "...                               ...  ...   ...    ...  \n",
       "944483                 پژو.بدون رنگ89  NaN  1389  10165  \n",
       "944740                    پژو 405 glx  NaN  1373  10166  \n",
       "944937                            پژو  NaN  1389  10167  \n",
       "945193                 پژو 405 مدل 93  NaN  1393  10168  \n",
       "945198                       405  tu5  NaN  1390  10169  \n",
       "945230              پژو ۴۰۵ کم کارکرد  NaN  1389  10170  \n",
       "945240              پڑو405 سفید مدل90  NaN  1390  10171  \n",
       "945275                  تاکسی پژو 405  NaN  1386  10172  \n",
       "945299                  پژواس ال ایکس  NaN  1389  10173  \n",
       "945354              پژو405عنابی اخر84  NaN  1384  10174  \n",
       "945409                  پژو405 دوگانه  NaN  1385  10175  \n",
       "945480                   فروش پژو 405  NaN  1392  10176  \n",
       "945481     پژو نوک مدادی داشبورد جدید  NaN  1393  10177  \n",
       "945527                     پزو405تمیز  NaN  1385  10178  \n",
       "945575           پژو٤٠٥مدل٧٨دوگانهlpg  NaN  1378  10179  \n",
       "945666                 پژو405مدل 1388  NaN  1388  10180  \n",
       "945674    پژو دوهزار موتور تازه تعمیر  NaN  1379  10181  \n",
       "945732                         پژو405  NaN  1394  10182  \n",
       "945767       پژو    s l x    tu5   95  NaN  1395  10183  \n",
       "945862                     فروش ماشین  NaN  1392  10184  \n",
       "945911              ٤٠٥دوگانه کارخانه  NaN  1388  10185  \n",
       "946101                    پژو خاکستری  NaN  1395  10186  \n",
       "946165                         پژو405  NaN  1378  10187  \n",
       "946176            پژو405مشکی مدل 1383  NaN  1383  10188  \n",
       "946334  ﭘﮋﻭ 405 ﺟﻲ اﻝ اﻳﻜﺲ ﺩﻭﮔﺎﻧﻪ ﺩﺳﺖ  NaN  1383  10189  \n",
       "946473               پژو405دوگانه سوز  NaN  1394  10190  \n",
       "946817            پژو جی ال آی دوگانه  NaN  1384  10191  \n",
       "946989                خودرو 405مدل 94  NaN  1394  10192  \n",
       "947426           پژو جی ال ایکس تمییز  NaN  1388  10193  \n",
       "947582        پژو 405 GLX تاکسی گردشی  NaN  1390  10194  \n",
       "\n",
       "[10195 rows x 18 columns]"
      ]
     },
     "execution_count": 929,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_peugeot405"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 930,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1c6f2264c88>"
      ]
     },
     "execution_count": 930,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bMCT4hGk86HU8uwheTPNO37W3Z35ffzkVY9bIAc711qzawayRA4if49R6FRFR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\n9PeDkFXVw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pgGHJvfHfNL8uAWONy9fLPF6l3PwDgST0UZQVGCrLTK34KiRG2Z27N5lmUF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\nKoYNRAzDMAzDqBj/A4P2h0CDzlcJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c6f2264d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df_peugeot405.loc[:,['mileage','price','year']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Normalize Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 931,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = preprocessing.StandardScaler()\n",
    "# Fit data on the scaler object\n",
    "def NormalizeData(df,column_names):\n",
    "    scaled_df = scaler.fit_transform(df[column_names])\n",
    "    scaled_df = pd.DataFrame(scaled_df, columns=column_names)\n",
    "    return scaled_df\n",
    "scaled_df_peugeot405 = NormalizeData(df_peugeot405,column_names)\n",
    "scaled_df_peugeot206 = NormalizeData(df_peugeot206,column_names)\n",
    "scaled_df_pride = NormalizeData(df_pride,column_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 932,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        mileage     price      year\n",
      "0      1.569163 -1.355543 -1.163313\n",
      "1      0.024590 -1.355543 -0.564264\n",
      "2     -1.144043  0.592023  1.033201\n",
      "3     -0.022215  0.202510  0.434152\n",
      "4     -1.143481 -0.732322 -0.763947\n",
      "5     -1.133989  0.202510  0.034785\n",
      "6      2.402296 -1.511348 -2.760778\n",
      "7      0.071396 -1.822958 -1.362996\n",
      "8      0.071396 -0.498614 -0.164898\n",
      "9      0.211811 -1.043932 -0.763947\n",
      "10    -1.135140 -1.059513 -1.163313\n",
      "11    -1.006997  1.994269  1.432567\n",
      "12     0.071396  0.124607 -0.164898\n",
      "13     1.260249 -0.342809 -0.763947\n",
      "14    -1.143341 -0.966030 -0.763947\n",
      "15    -0.817904  1.261985  1.033201\n",
      "16     0.071396  0.436217  0.234469\n",
      "17    -1.145513 -1.511348 -2.561095\n",
      "18     1.756384 -0.280487 -0.364581\n",
      "19    -0.864709 -2.539662 -0.564264\n",
      "20    -1.144324  0.623184  0.633835\n",
      "21    -0.752377  1.028277  1.232884\n",
      "22     2.552073 -0.342809 -0.164898\n",
      "23    -0.808543 -1.043932 -0.564264\n",
      "24    -0.377935  0.436217  0.833518\n",
      "25    -1.145260  1.152921  1.232884\n",
      "26    -0.022215  0.358315  0.234469\n",
      "27    -0.817904  1.448951  1.232884\n",
      "28     0.380310  0.171349  0.234469\n",
      "29     0.576892 -0.654419 -0.763947\n",
      "...         ...       ...       ...\n",
      "10165 -0.050298  0.280412  0.434152\n",
      "10166  1.007500 -1.667153 -2.760778\n",
      "10167 -1.143013  0.405056  0.434152\n",
      "10168 -0.724293 -0.342809  1.232884\n",
      "10169  0.165006  0.747828  0.633835\n",
      "10170 -0.565156  0.903633  0.434152\n",
      "10171 -0.864709  0.046704  0.633835\n",
      "10172 -1.140392  0.124607 -0.164898\n",
      "10173 -1.042569  0.358315  0.434152\n",
      "10174  0.473921 -1.168576 -0.564264\n",
      "10175 -1.144483 -0.342809 -0.364581\n",
      "10176 -0.396657 -0.498614  1.033201\n",
      "10177 -0.733655  1.339888  1.232884\n",
      "10178  1.391303 -0.140262 -0.364581\n",
      "10179 -1.143547 -1.511348 -1.762363\n",
      "10180 -1.144324  0.077865  0.234469\n",
      "10181  0.726669 -1.589250 -1.562679\n",
      "10182 -0.827265  1.293146  1.432567\n",
      "10183 -0.874070  0.436217  1.632250\n",
      "10184 -0.743016  1.059438  1.033201\n",
      "10185  0.726669  0.311573  0.234469\n",
      "10186 -1.070652  1.885206  1.632250\n",
      "10187  0.726669 -1.589250 -1.762363\n",
      "10188  0.511365 -0.810224 -0.763947\n",
      "10189  1.662774 -1.043932 -0.763947\n",
      "10190 -0.939598  1.916367  1.432567\n",
      "10191  0.857724 -0.732322 -0.564264\n",
      "10192 -0.808543  0.903633  1.432567\n",
      "10193  0.352227 -0.000037  0.234469\n",
      "10194 -0.022215  1.355468  0.633835\n",
      "\n",
      "[10195 rows x 3 columns]\n"
     ]
    }
   ],
   "source": [
    "print(scaled_df_peugeot405)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot after normalize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 933,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1c6e12426a0>"
      ]
     },
     "execution_count": 933,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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aiMRSKRlajXQhd79bwMCnN5or/NceGAGXKzWC5RU4FF7TREI0tuhS6vNYlRTT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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c6e1242e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(scaled_df_peugeot405)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 934,
   "metadata": {},
   "outputs": [],
   "source": [
    "Nc = range(1, 20)\n",
    "kmeans_peugeot405 = [KMeans(n_clusters=i) for i in Nc]\n",
    "kmeans_peugeot206 = [KMeans(n_clusters=i) for i in Nc]\n",
    "kmeans_pride = [KMeans(n_clusters=i) for i in Nc]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Find Best Number of Clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 935,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def findBestNumberOfClusters(kmeans,df):    \n",
    "    score = [kmeans[i].fit(df).score(df) for i in range(len(kmeans))]\n",
    "    plt.plot(Nc,score)\n",
    "    plt.xlabel('Number of Clusters')\n",
    "    plt.ylabel('Score')\n",
    "    plt.title('Elbow Curve')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Peugeot 405"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 936,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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REYVOylTV1AMwXaEjIllMoZMildV1DM7PZWzpoHQ3RUQkbRQ6KVJVU8e0kcXk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\nxz2rAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c687e84b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "findBestNumberOfClusters(kmeans_peugeot405, scaled_df_peugeot405)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Peugeot 206"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 937,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Kiwr4rwuPpFjncUQkJjqnkwe+/vuXWLVuKzctnM9+1TqPIyLx0Z+8I9x9yxv51ZNvcOkJ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c6e115b208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "findBestNumberOfClusters(kmeans_peugeot206, scaled_df_peugeot206)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pride"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 938,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9ULGNb/3+DSpr6jmzbATf/IfjmTaqOO6wRKQPi2UKXjP7npmtNrMVZvYbMxuasO8mM6s0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\noFT/XjaXyAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c6881dccc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "findBestNumberOfClusters(kmeans_pride, scaled_df_pride)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implement Kmeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 939,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "number_cluster_405 = 8\n",
    "number_cluster_206 = 7\n",
    "number_cluster_pride = 10\n",
    "\n",
    "kmeans_peugeot405 = KMeans(n_clusters = number_cluster_405, random_state=0).fit(scaled_df_peugeot405)\n",
    "kmeans_peugeot206 = KMeans(n_clusters = number_cluster_206, random_state=0).fit(scaled_df_peugeot206)\n",
    "kmeans_pride = KMeans(n_clusters = number_cluster_pride, random_state=0).fit(scaled_df_pride)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 940,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def dfAfterKmeans(kmeans, df):\n",
    "    dist = kmeans.transform(df)**2\n",
    "    df['sqdist'] = dist.sum(axis=1).round(2)\n",
    "    df['cluster'] = kmeans.labels_\n",
    "    df['ID'] = np.arange(len(df))\n",
    "    return df\n",
    "scaled_df_peugeot405 = dfAfterKmeans(kmeans_peugeot405, scaled_df_peugeot405)\n",
    "scaled_df_peugeot206 = dfAfterKmeans(kmeans_peugeot206, scaled_df_peugeot206)\n",
    "scaled_df_pride = dfAfterKmeans(kmeans_pride, scaled_df_pride)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 941,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        mileage     price      year  sqdist  cluster     ID\n",
      "0      1.569163 -1.355543 -1.163313   54.32        7      0\n",
      "1      0.024590 -1.355543 -0.564264   32.38        4      1\n",
      "2     -1.144043  0.592023  1.033201   58.85        5      2\n",
      "3     -0.022215  0.202510  0.434152   31.40        3      3\n",
      "4     -1.143481 -0.732322 -0.763947   38.76        0      4\n",
      "5     -1.133989  0.202510  0.034785   39.72        5      5\n",
      "6      2.402296 -1.511348 -2.760778  123.03        7      6\n",
      "7      0.071396 -1.822958 -1.362996   49.34        6      7\n",
      "8      0.071396 -0.498614 -0.164898   24.33        4      8\n",
      "9      0.211811 -1.043932 -0.763947   29.12        4      9\n",
      "10    -1.135140 -1.059513 -1.163313   45.33        0     10\n",
      "11    -1.006997  1.994269  1.432567  103.18        1     11\n",
      "12     0.071396  0.124607 -0.164898   25.89        3     12\n",
      "13     1.260249 -0.342809 -0.763947   35.81        4     13\n",
      "14    -1.143341 -0.966030 -0.763947   40.65        0     14\n",
      "15    -0.817904  1.261985  1.033201   66.81        1     15\n",
      "16     0.071396  0.436217  0.234469   31.54        3     16\n",
      "17    -1.145513 -1.511348 -2.561095   85.90        6     17\n",
      "18     1.756384 -0.280487 -0.364581   45.70        2     18\n",
      "19    -0.864709 -2.539662 -0.564264   70.21        6     19\n",
      "20    -1.144324  0.623184  0.633835   51.69        5     20\n",
      "21    -0.752377  1.028277  1.232884   65.09        1     21\n",
      "22     2.552073 -0.342809 -0.164898   72.08        2     22\n",
      "23    -0.808543 -1.043932 -0.564264   34.72        0     23\n",
      "24    -0.377935  0.436217  0.833518   41.97        5     24\n",
      "25    -1.145260  1.152921  1.232884   74.56        1     25\n",
      "26    -0.022215  0.358315  0.234469   30.73        3     26\n",
      "27    -0.817904  1.448951  1.232884   76.67        1     27\n",
      "28     0.380310  0.171349  0.234469   29.40        3     28\n",
      "29     0.576892 -0.654419 -0.763947   27.67        4     29\n",
      "...         ...       ...       ...     ...      ...    ...\n",
      "10165 -0.050298  0.280412  0.434152   32.19        3  10165\n",
      "10166  1.007500 -1.667153 -2.760778   90.40        7  10166\n",
      "10167 -1.143013  0.405056  0.434152   45.81        5  10167\n",
      "10168 -0.724293 -0.342809  1.232884   49.64        5  10168\n",
      "10169  0.165006  0.747828  0.633835   41.31        3  10169\n",
      "10170 -0.565156  0.903633  0.434152   44.92        5  10170\n",
      "10171 -0.864709  0.046704  0.633835   40.47        5  10171\n",
      "10172 -1.140392  0.124607 -0.164898   38.27        5  10172\n",
      "10173 -1.042569  0.358315  0.434152   43.34        5  10173\n",
      "10174  0.473921 -1.168576 -0.564264   30.68        4  10174\n",
      "10175 -1.144483 -0.342809 -0.364581   36.28        0  10175\n",
      "10176 -0.396657 -0.498614  1.033201   41.58        5  10176\n",
      "10177 -0.733655  1.339888  1.232884   72.45        1  10177\n",
      "10178  1.391303 -0.140262 -0.364581   37.41        2  10178\n",
      "10179 -1.143547 -1.511348 -1.762363   62.86        6  10179\n",
      "10180 -1.144324  0.077865  0.234469   40.55        5  10180\n",
      "10181  0.726669 -1.589250 -1.562679   50.86        7  10181\n",
      "10182 -0.827265  1.293146  1.432567   77.95        1  10182\n",
      "10183 -0.874070  0.436217  1.632250   68.14        1  10183\n",
      "10184 -0.743016  1.059438  1.033201   60.88        1  10184\n",
      "10185  0.726669  0.311573  0.234469   33.20        3  10185\n",
      "10186 -1.070652  1.885206  1.632250  106.41        1  10186\n",
      "10187  0.726669 -1.589250 -1.762363   55.02        7  10187\n",
      "10188  0.511365 -0.810224 -0.763947   28.18        4  10188\n",
      "10189  1.662774 -1.043932 -0.763947   48.47        2  10189\n",
      "10190 -0.939598  1.916367  1.432567   99.15        1  10190\n",
      "10191  0.857724 -0.732322 -0.564264   29.90        4  10191\n",
      "10192 -0.808543  0.903633  1.432567   68.68        1  10192\n",
      "10193  0.352227 -0.000037  0.234469   28.10        3  10193\n",
      "10194 -0.022215  1.355468  0.633835   54.98        1  10194\n",
      "\n",
      "[10195 rows x 6 columns]\n"
     ]
    }
   ],
   "source": [
    "print(scaled_df_peugeot405)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 942,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mileage    1116\n",
       "price      1116\n",
       "year       1116\n",
       "sqdist     1116\n",
       "cluster    1116\n",
       "ID         1116\n",
       "dtype: int64"
      ]
     },
     "execution_count": 942,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaled_df_peugeot405.loc[scaled_df_peugeot405.cluster == 0].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize Clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 943,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c686c9db00>"
      ]
     },
     "execution_count": 943,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Uffgh5hr7tzVzWTnuffrgPWpUi+Uo/Wg+lV8uRjaacO/Xj5gl36HSOPVFWxDOGae1lMmy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\nMMYYA8D/A4111CorRQ9ZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c68814b048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(scaled_df_peugeot405.cluster,scaled_df_peugeot405.price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 944,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c687ec4908>"
      ]
     },
     "execution_count": 944,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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59qK85dR9ZrxPPDq1jtEBo0kpTgGsBumrw64m2jOaayOupbCxkH+n\n/ftybVVB4TfT1XWNm5sbI0eOlBXM6eh7ehxBc3MztV1k5O2qpoFarcbHx0dSHiqVivj4+C7X0dTU\nhNlsRnceCRsv5wlhJDAPyBQEoSPK6UlRFFef5R2FS0RWdRYpRSnSl3qzqZl309+loKFAciE1W8ws\n3LuQq0KvIqs6i+m9p7O5cDNFjUUM8xvGrrJdfHPkGxzUDszpN4cAfQA7SnZw/6b7UQtqZvWdRXyv\neCxYzraUC4ohOxtDVjaOw4aiO5leQEHht9CnTx90Oh1tJ4MhBUHg+uuvJzAw0OYqqX///jQ2Nspy\nD/Xp04cBAwaQlXXKn8bJyYnExETS09Nl4/bv358xY8awb98+ysrK8PDwwMXFRRo7NTVVGiMqKuq8\nlAFcXi+jX+AiRSYpdBt7tT2GdoONfJDPINbnr5fJagw11BprbWRv7H2Dzw5+BoCd2o73JrzHj8d/\n5ES9Nd10a3sry44t46HBD/FLyS8AtIvtfH3460tqPK7+5FMqXn3V+qBWE/DmQlyuuOLsLykodIO2\nTpHxoihy+PBhAgMDmT17NikpKVRVVREVFcWQIUOwWCzo9Xpyc3Px9fVl9OjR2NvbM2vWLNLT03Fw\ncMDd3Z2UlBRGjhxJVVUVJpOJoUOHSkFtBoOBzEyrW/Yvv/zC7Nmzba6TTo9+7g6X3aiscHnpShkI\nCMztN5ftxdvZXrJdkk/vPZ2ChgJZTMLVYVfzxaEvpGdju5EPD3woS3MN0GJuIbvG9v7T29EbFaqL\nfkoQ29qoeu+9U4L2dqrefkdRCAq/mSVLltjItm/fTlJSEvn5+bi5uZGYmCgVtlGr1YwaNYpRo0bJ\n3omOjiY6Opqff/6ZLVu2SPKxY8eSlHQqU3Bra6uU9wis8Qjbtm2zuTIymUwy19fuoCgEBRtERN5J\nfweNSsP4oPHYqe0YEzSGqeFTMVvMhLqGklGRwQCfAYwPGs/SY/LkXi3mFpKCkjhUfSq/e5hrGNdG\nXCurpaxVaUnwS8BOZUerpfXi7sliwWI0ymSWTgY4BYVfi/G0nyuwnhK++eYbySNo48aN3HbbbV3W\nRehMe3s7+/fvl8n27NkjUwjt7e2ySmogP6F0pqWlRVEICr8NBxz48MCH0vPD8Q8zNXwqGws2klmZ\nSXyveJn30Pig8VLtA4AR/iNoNbcyPng8JU0lhLmEcWPfG9lTsYcpYVMoaCxAr9UzpNcQbkm+hTZL\n1z/MFxKVvT1uM6ZT9/0Pksz9potbmEehZzBjxgw+/vhjmSwoKEjmHmo2m0lNTWXy5Mmkp6djMpkY\nMGAAbm5utLe3k5mZSXV1NZGRkdjZ2cm8heztraVmGxsbycjIQBRFm2R2Q4cOJTk5WZb1VBAEvL29\nz2svikLo4XTl8tmK/Gt9Zc5Kmtqa+CjzIwA+OfgJCwYvYH7sfIqbihkdOJpwt3CaTc246lz54MAH\nkjF6QvAEFsQv4C8r/0JDmzXMxF/vz0dXfsRNq266JMqgA99nnsFhwACrUXl4onJdpHBB8PHxwd7e\nXnIlBWsMwDfffCPrZzab+fDDD6mrqwOsRW3uvvtu1q9fLxmUU1JSiI+PlwLdVCoVEyZMoLm5mQ8+\n+ICmJutVrKOjIxMnTqS+vp4+ffoQGRnJ4MGD+e9//0tdXR0ODg7cf//9570XRSH0dLrh7u/l4MVX\n2V/JZF9mf0mYaxiPbnlUKp7ztyF/Y1vRNlkMwcaCjfg7+UvKAKCkuYSNBRupMdRcmD10E0Gjwe0M\nWSEVFH4tR44ckSkDsKakDg0NJS8vDzjlLtrZ8GswGEhNTZV5F4E1ZfX8+fPZsWMHOp0OFxcXDh06\nJCkDsF4FqdVqpkyZInv3oYd+W45QJT9AD8dR52gjG+E3Qspf5Kxz5oFBD6BRyb8dNCoN76W/JykD\ngPcz3rfJeyQgoFPZur5pBA3XRlx7xnVdrNTYCgoXmjPlKZozZw7XXnstSUlJ3HPPPV1e32g0Glme\nIrBe9Sxbtozs7GwyMjL49NNPpVNFZ7oKOCstLWXnzp2SIjpflBNCD8dR7Ugj8kCZK0OuZJjfMLYV\nbSO+Vzy93XpzV9xdvLbnNanPXXF38WmmPOWu0WxkXr957C3fi8livcucETmDudFzWXliJRUt1mCa\nSLdIKlorKGkqISkoiRZTC2ll8jRWpysggPqVP9O4cSO6kBA8b7sVi7GNmk8/xVxZgcs11+CclISl\nrY3azz+n9UAmjkOG4D5nNoJaTUNyMg1r16ELCsTj9tvRnPT4sLS0UL1oEcbDR9CPGIHbDbMQBIG6\n5ctp2rwFu4hwPG67DbWzMy1791KzaBHGvHy0Af54zJuH069ID6Dw56KrugVms5kff/yRsLAwKVrY\nzc2NXr16ScnonJ2dSUxMxGAwyK6IIiIi2LhxozSWxWKhqakJDw8Pamqsp2p3d3fi4uKorq5m586d\ntLW1UVtbS2FhofSeVqvlqaeeOq+9XLb0178GJf31hSd28bmLxIwJHMO7E94lozKDfeX7UAkqBngP\nIL0iXVb1bHrv6Tw/8nkKGwrZVryNEJcQBnkPIr8xHx9HH7YVbUOr0nKw6iBLDp9y1RvpP1Lm3tpB\n5/TXtd98S9mzz0rPDgMGYK6rxZRfIMkC33uXxvUbqF92Kumexy23YBcVRekTT0gy++hown60ekYV\n3n8/TRtO/fJ5PXA/amdnyl86FT3tmJCAz9/+Rt6NN0Jn7w5BIPizT9EnJp7zn6HCn5dnO/1cdsWo\nUaOYOHEiYHUFzc7Opry8HIvFgr+/P9HR0eTm5lJdXU3v3r1paWnhk08+kY2RmJhIUlIS2dnZiKJI\nv379EEWRt99+W2aAPp1//vOfqNXq33/6a4U/DtuKtlFnqMPbwZsvs7+UvvQnh07mjXFvsKNkB1Ut\nVRQ1FvHq7le5e8DdzOk3h5SiFCb+MFHKfvpm0psM7jWYV3a/Ihu/K2VwOvWdassCtGZk2PZZtpzG\nTv7bAPUrVmB3WvoAQ1YWhqNH0fr50bRx02n9f0LlJHfTa0lLo/a7b+XKAEAUqV/xk6IQFM5Kenq6\npBA6ahxv337qZz4nJ4fp06fT2trK6tWr0ev1MvuDk5MTCQkJtLS0kJ+fT319PRaLBa1We1ZlAPD6\n66/z2GOPdXutikJQOCd6rR4HrQMfHPhAUgYAyXnJ3Nr/VuzV9mwp2gLAnvI95Nbn8t7E93gx7UUp\nQK3WWMvLu17mu2u+w9Pekzqj7Z3o2VB7ecoFGg2Y5VXYNN5eaNzcMHfKAaP28kTjedq7ajVqNzdU\ndnaonJywdMoto/H0ROXkRGfPcsHeHm0v3y7XpTl9XQoKp3F6CurO6SUAMjIyCAsLY1mnk62joyOz\nZ8+mra2NyMhItFot77zzjnRldOLECRK78SESFxd3XmvtllFZsDJXEIT/O/kcLAjCsPOaSeEPQ6hL\nKHqN9StZJai4d8C96FQ66o22SbzqjHWsy1snk/1S/AsNxgZKm0tl8qKmIgDuG3gfdmo7wGorCHeR\n1zruCu/770fVqZasy9SpuHeqSKXx88Pj9vn4/OMfcPIrTLCzw+dvf8PrvntRd1IKLpMnU/L3x8i/\n5VZcrrpKKqKjcnTE++EFeD/4AKqT+WEQBLwfeACPeXOl8psdqN3dcZ8375xrV/hzc80115yxTavV\nEhAQwAcffMCSJUsoLS21MQYLgsCRI0dkso4v//79+2NnZ0dpaamkDDooLy8/Yz3nDiZNmnQ+W+n2\nCeE9wAKMB54DGrGmrR56XrMp/CHIa8hjesR0hvoO5avsr3htz2t8e+Rb5kTNYVXuKqlSWrBzMEN9\nh+Lv5E9F66mTg4e9B3qtnqSgJDYWnLqfH+43nFkrZ5Fdk02Icwg3Rd1EvbGe9w+8f841WZqaZJHF\nDatWEbF6Fe433YipogLHoUNR6XToAgNwHDYUY3Y29nFxkvG494b1tOzZC2oVhXffAycDeFr37yfg\nv2+isrfHYdAg1CcVQe9Nm2jdtxddWJiUBC948SKOJ41HPOli2F5bS+vevWi7qKmr0HPoSG/dmbCw\nMIYPH05NTQ1r1qwBrB5ARUVFXH311SxdupQO++3QoUO7TELn5uZGU1MTZWVluLi4IAgCnW2+7u7u\nTJs2jeLiYtra2li8ePFv3kt3FUKCKIqDBUHYDyCKYq0gCOeXRk/hD8WOkh00m5vJqrH6SBc2FrI4\nazEfX/kxq06swmQxcaLuBFN/nMoQ3yHkN+RTa6zFQePA6MDRXLviWrQqLWMDx9LQ1sCQXkNIr0iX\n8hnlN+bzw7EfcLd379Z6GjdvlgtMJppSUvCYPRu7yEhZk9bHB62Pj0ymcnDAafQoapYskZRBB4bM\nTHz+9jeZTO2kx2nMGJmsafNmSRlI69q0GRdFIfRoOtsDOigoKOCWW27h66+/lslbWlpwdHTk3nvv\nJScnB29vbyIiImhpaeHYsWOUlZUhCAKJiYlUVlby448/0t7ejkajIS4ujszMTCwWCx4eHow5+fN5\ntnQYpaWlUqW17tBdhWASBEHNyTAmQRC84RLmLFa45IS5hpFVLQ+YKW0uJcw1jMeGPsbEHybS2Ga9\ne/8p5yceiX+E+F7xlDSV8Pdtf5feya3P5afpPxHsEsyIJSNk4x2vO871kdfLKqqdCbvwrq6VBIof\neQSLwYj77Nk4jTq3C6hdWJiNTBd27isrgLqltjWc7MJtx1PoWTg6OtrECXRcC3l5ecmugwRBoKys\njNTUVIxGI0OHDiUiIgK9Xs/dd99NWVkZDg4OuLm58cYbb0g5i8xmM0VFRTz88MM0NDTg5+cnu3rq\nnMaiM+dbQrO7gWlvAcsAH0EQXgR+AV46r5kU/jDotXoeG/YYw3zlZqLebr3xcvDiUPUhSRl0sKts\nF3HecWRUyr1/2sV2KcZgmJ98vME+g/nroL/ipz/3F4zrNdfg3HEfqlbjOnMmFa+9RsPqZJo2baLw\n7rtpPZkOuPbrrzk2ZixHR4yk6gNrTqaOeIPGTZtxvmKi1W4gCDhPmoRdVBR5N9zI4YGDKPzr/Zhr\namhvaKDo4Yc5PHAQudddT2tmJq3p6fJFCQLu824+59oV/tz4nHYaBat76WuvvYZOpyPo5JWjRqNh\nxIgRrFu3joaGBoxGI7/88ov01b9mzRoWLVrE559/TlZWliwyGawFb5ydnTGZTPzvf//jxRdfZNmy\nZRgMBlasWNHl2jq8mrpLt04Ioih+JQjCXmAC1hoG00VRtM1lrPCnoNnUzJLsJbjoXLgi5Ar2lu8l\n2DmYUJdQ/rPrP1wRcgValVYKPgOI8ojCYDYQ5WFr5PJ28Gbh3oU4aZ1I8EvgWO0xerv1Rq/Vc9+G\n+8Bs84oNgk5H4JsLMZU/gaDT0rhuPfU/dvpib2+nca21VnPZv56TxJULF2LfL4rqjz6mZffJk4gg\n4Pfvl9APH4HGx5sTU6bSdsJau6Fp40bKHRxQ6fU0Jlvvfg2HDlH04EPYR/XFcOjUqcm+f3/UTt3P\nJKnw5+TAgQNdypuamti8eTO33norrq6uODg4dFkCs7CwkNbWVtLSrB9ORqORpUuX0q9fPw4dOpUx\neMCAAZhMJr799ltaW635xjIyMrCzs7NRHh10JMbrLt1SCIIgeAAVwNedZFpRFE1nfkvhj0xHSusQ\nlxC+m/od1628jvTKdKntwUEP8vHBj2kwNjDUdyipJal8nPkxoS6hJAUlkVKUglatZV6/eTy38zkq\nW62uoFqVlq+nfM2TvzzJrrJd570ubS/r15jW39+mTePnR8vJiM/ONK7fcEoZAIgiDatW4zZ9Ouaa\nGkkZdNCydy8qvTylh7m0FN9n/o+KV16l7cQJdBER+L3w/HmvX+HPR1dG5c4UFBRI9/2BgYE27YGB\ngRw9elQma29vJzo6Gj8/PwoLC3FxcWHw4MFUVlZKyqCD0tJSm8psHWzYsEGKgegO3bUh7AOCgFqs\nJwQ3oFQQhArgTlEUbX8LFf4U5Dfk89nBz2Qup63mVoztRjbP2ozBbODxlMelP+55DXkA/HLjL2jU\nGjbmb5SUAYDJYmJJ9hKO1sp/AbpL66EstCHB6EeNxGXKFBpWrQLAYfAgnCdMwFxWZvOOfWws/PAD\ndPLQUDk40N7YCIKALiSEtvx8qc1hwABUTnrajp+qOKXx8cFp1Cicx43DmJuL2N6Ofe/ev2oPCn8u\nTvf+6ar9o48+wmAwEB8fz7Rp09i0aRNtbW3ExcURFxdHS0uL7DSgUqkICgoiNDSUjIwMjhw5wu7d\nu4mNjbXJrBoUFMSwYcN48803beY+H2UA3bchrAGuFkXRSxRFT2Ay8B1wH1aXVIU/MZ4OtsFXzjpn\ntCotzjpnDlUdkrXlNeQhImKntsPFzsXmXR9HH5y1zue1htZDWRweNJi8667j2NBhVPznPwS8/hrh\nyatxnTGd1syDHB8/gdqvv8bnsb+jdnVFpdfjdd99uM/6C27XXyeNpXJ0RLC35+iIkRwbOQpdaCh2\nffuCIKAfNQrfp57E59FHcRo/HlQq7CJ7E/DmQgSNhsK77+HE5KvJnXoNR0eOwlxdfV77UPjzMXjw\n4C7l9vb2jBo1ii1btlBcXEx1dTXr1q3Dzs6OyZMno1ar2bNnDx999BFRUVHEx8ejVqtxcXFhxowZ\nuLi4sGvXLio7BVpmZmYybtw4PDw8UKlUxMTEMHbsWNzc3LpcQ/V5/nx294QwRBTFezoeRFFcJwjC\nS6IoPiIIgt15zajwh2JC8ARGB4xmS+EWDlRZ70rDXcPp59GPtvY2dGodw3yHkZyXLL3Tz6MfTjon\nLKIFTwdPhvQawp5yaw6qIOcgxgaOxcPBg7f2vUWTqQmtoMV0jtvH4ocfRuw4KosiNYsW43nnnbRX\nVVG/7FRai/oVP+H373/TJ00eDer3/PO4TptGW1ExKr2e4gcflNqatm7F/z8v43qtPPtq0Hvvyp6b\ntm+naetW6bm9upqSfzxO8Mcfnesfo8KfmMOnpUbp4PHHH+fAgQM21c2OHj1Kdna2VOWspKSErVu3\nMn36dKZMmUJmZiZFRUVoNBoaGxttxnVxceHBBx/EaDRSW1uLRqM5YwqL8/Uy6q5CqBEE4R9AR8WH\nG4Dak66oivvpn5CF4xayo2QHy44vY2PBRqLco3hlzCsUNBSw6NAibl5zMx72Hvw36b88mfAkFiyk\nlqbSz6Mf/0z8J4UNhdyz4R4KGgvQqXTcEn0Lcd5xLD22lJtW34SAwLSIacyPnc+05dPOuZ7O6Sg6\naD2Qibms1EZuPHqU6k8+sWY3DQzE+6EH0YWE4Dh0KI5Dh1Lz1Ve275zBba9j7oo336Rp6zabtrbc\n3DVtTSAAACAASURBVHOuvTuIoojFIqJWn/nQXl/ZQtpPudRXthIxyJtBVwQjqJQ04Zebs+UT8vW1\nTXni4uJiU/KyosIa2JmcnMzuk/autLQ04uPjZf0cHR2JiIjg8OHDLFu2DKPRiLOzMxMmTOhy/vz8\n/C6zsZ6J7iqE2cAzwHKsNoRfTsrUwKxuz6bwh6HeWM/SY0ulqOTDtYc5WHWQTQWbpPxENYYaXkp7\nif8m/ZeKlgrqjfVUtVbRaGpk8cHFFDRaM5G2Wdr47uh39NL3YkeJtTi4iMiKnBXE94rvegGnYR8T\nQ2vnTLdqNfrRozAXF9vkNbIYWql41Zqq23DgAK2ZmUSsSUZsb6c1PR27iN427+g7BaGZq6owHs/B\nIbY/Kr2eoocW0LpvX5fr0o8dayP7/OkUGqtM6PRw5+vjz7m37B2l7Fx2HGOzmT4JvRg3Jwq1RkVj\njYGGqlZ8w1xRqQVWvpVBfaX1lFSR14AgCAy6MviM4757jzVx31//d+41KPx6nJ2daWhosJE3Njbi\n4+PDFVdcwZYtWzCbzfTu3Zvw8HAOHjxIbW2t1DcyMhKz2cy+037Ojh07xty5c9mzZw8Wi4XRo0ej\n1Wr5+eefpVrO/8/eeYdHVaZ9+D5TMzPJTMqkEUhCEhJKaNJBqmKh2LDvqh/up+KublHXdV133XXd\nVbe5a18botgbioqAIr1DIJCQ3vtMMmnTy/n+OMkkkwmQCIjyzX1dXGTeOec9ZyBznvd9yu/p6OgI\nOq+bjEHGuQaadmoG7j7O2yWDumKI7xUx6hiancF+xoKWAr8x6KaqvYo6a2AmQ01HDX/Z8xdymqTG\n4CWtJTyw9QHClYFbVbvHTrEleBXet/jteITPnx9gEBRGIzKFAlVKCkOfform/76Iz+kk+sc/DpC/\nBnBXV9Ox6RsaH30UT2MjyGTolyzGXVmFz+0i+qab0U2VaiRaP/yI+j/+EdxuZHo9Q/72t+MaAwSB\nqBsD+zJ3P4QBXFbp9YkeyB0tDr5ZXYDok4KSBbsaiEkKx+vxseeTMkQRdAYVs2/I8huDbsoPm/o1\nCLvXl3Lg454g+bMrNjFqTgILbhx93PsI8e05nkF48sknWbJkCbNmzWLq1KmsWbOGvLw8iouLMRqN\npKen09raitFoRBAETCYTCoUiwMWkUqlQKBSUl5fjdDopLS1l0aJFQWmmvY1LbzweT7+yGMdjoOJ2\nsYIg/F0QhC8EQdjU/WfAVwnxveXOCXcGjSkEBddmXYtRYwwYX5i6kHlD5wWMXZByAUfNRwPGKtor\nmD10dsBYRmQGV424KqATmlqu5oaRN2BQGYLu4ZrMawJem596KuC1p7ER+xHpuhHz5zPkH//AeMcd\n6M6fhTI1JeBYQaWibe1ayRgA+Hy0f7GOoc89y7AXXkCm0eCqrkZ0uWj829/80ha+9nbML74YIIwX\ngCjS8Ps/9P/eADFVdfiNQTf1pW3sXVvuT4qytrko3F2PXBn4dTXEafqds7cx6ObY1uDsqxCnh9ra\n2n7HfT4fGzZswOPxUFdXF5BFZDabSUlJITExkcLCQjZv3syLL77ImDFj/McIgsC8efPYuHGjfzfg\n9Xr5+uuvGd6n4n706P6NfX+pqCdioC6jN4F3gSXACuAWINipG+IHx3UjrwMBXsp9CavbSoYhg7vP\nu5sRUSN45aJXeP7w8zTZmlictpjL0i9j/rD5PHvoWY6YjzApfhJ3jr+TP3j+wJcVX/rnHBU9ihXj\nV6BRaNhUtYkUfQo/m/AzEsMT+ff8f/NWwVuEycO4NftW0iLTePWSV3nywJPkmnKRC3KuzryauyYG\nNggX3cFBZ3tBAZqx2bSuWUP9g78Dnw+UShIeeghH7hGcRUUIYWHEP/Ab2j//IvBkj4f2detoeuJv\n0twyGXG/uR9fW6Ciq7epiYQ/Pkz9g78LkMnuxlVTc9J/42dXbCImScesq0cwbFQ0Pq+Pwj2NNNd2\nEj88ArlChtfTsxuLGRJOWU7g18vR6Wb2tSPY/n4xHpeP6CE6piwezq6PSzm2s44wnZLpV6STNiG4\nTWOIs4fD4cDlcvUbHDabzRw92rOYEkWR1tZWbrnlFvbu3YtWqyU2NjboXJvNxuWXX8727dtpaGgg\nLS2NOXPm+AvbelNdXU1qauqA73egBiFGFMVXBEH4hSiKW4AtgiBsOelZIX4QXJd1HddlXRc0nhaZ\nxt/n/j1gLEIVwQNTHwgYe3Dag3hFL7vrdzM6ejQPTX8ImSBjefZylmcvDzh2QfICFiQHulAyozJ5\n/sITK56qMzNx9s7mEASir7kagKZ//lMyBgBuNy2vvkr6+i9p/eQTvO3thM+dCzJZQHGaOisLy7vv\n9Rgan4/m519AN2c21q3b/Mfply5Bv3Ah4bNm0fzmW5j/2dMhDiTX1UBorrWy7oUj/M/js9j2bhEF\nu3tW7Nlzk6grbsXe4WLUzCFMuiSZ8lwT5uoet8CIKfGMnjWEjMnx2NqcRMZryd9ex8H10m7A3uFm\n/UtHufkvM4OuHeLMEhER0e8DHyQffncgWKPR+IvKBEEgKyur3yrnzz//HLPZDEjNdbKzszncqyHU\nyJEjiYyMZMmSJdTU1NDQ0NCvywoYUM+E3gxY3K7r73pBEBYDdUBwyV2I/5dEhUXxr3n/OqPXCMoC\nEkWcZeWoUlPwtQV+GbytrTQ88mcsb0ltOk3/+CfJL79E4uOP0f7Z58h0WuLuvZfKHwf2MvB2dpL4\n+ONYVr2OPfcw6owRxNxxBwCCRoO1n5zugewQunE7vdQWt1K4J9B9U1fcyg1/mEZrk42vVubzwt2V\nGIfqyJqWgNPuQamWs+fTMnZ+UMKYuUnMWpaBIAjUlQQKqvm8Ig1lwT0rQpxZtFptvwYhMzMTlUrF\nzp07mTJlCrfeeis7d+70F6hlZGRQUFDAkS4NLplMRkpKCt/0UvbtVjq9+OKLKSoqQq/X+3scfPPN\nN2zpSoPu22Oh9/mD0TMaaGHao4IgGIB7gfuAl4FfDfgqIUKcKn3bVwJlixbhMZkxXHVlwLh+8SIs\n77zjfy06nZhffAlBrsC2dy8d6zdQfvU16GYFrqYNS5eijI5GHhmJbe8+LG+8QdlFF+MsKcH01FPY\nX3st6B7E46wM+0OulGEcGo5MEfi1U3TFBr55o4DGcsm4mWusWBptTF06nOJ9jTitHjxuH4e/qqZ4\nnxQLiU8NLPoTBFCo5AO+nxCnh8bu2FQfioqKOHr0KBs2bGDNmjUYjUaioqIwmUzs2LGDmpoarrzy\nSq644gqysrKYNWsW8fHxQfMolUo8Hg8VFRUcPnyY559/nvr6+gDZ7ePJZ/QnzX0iBppl9FnXj23A\n/EFdIUSIM0jH+i9JeOgh1CNG4MjNRTN5Mrrp07G8FahD77PbaHzsMcSu/G9fezvO0jIS//IXbHv3\nEDYmm6jrr8Pb1obpySf9BsjT1ITp6WewHTw1dRadQUXm9EQcnW4mLkxm/xcVAMhkApMXpQLQWBG4\n02mqbKepItgV0FjRTvrEOMKjwkgdZ6Qqvxm1RsGMKzOoLew/2yTE2SU/P59du3axaZOUi2M2m1m9\nejU//elP2bx5M62trRQWFhIeHk5ycjJVVVLKtlarJTs7m1dffdUvj9He3s62bduCCt7643iurOMx\nUHG7TOB5IF4UxWxBEMYBl4mi+OigrhYixOlGoaBl1Sq8nZ3ErFjh73cQPm8enZs3+w+LXHY19Q8+\nGHCqp6mJyGVXEbnsqp6x2lq/0fCPNTQgNxjwmszB1x+AmuSSX2Xz9StF5KyvJGd9Jdlzklh2/yQq\n85qpOtrM16uOkTymicQ0AzW9HuhDMiJJTI+UKn96JSLFDAnnzT/upqNZ0rNJm2jkktvHIggCB76s\nOOn9hDi9GAwG2tpO7KpTKpWU9ylidDgc7NixI6CXQmdnJzNmzCA7O5uSkhKSkpLwer1BOwCr1cr4\n8eM51FeSvQ9XXHHFoD7LQGMILwG/Bv4LIIpiriAIbwEhgxDiu0EuD3IbhY0dS/Nrr+GpqgagZdXr\nDH/vXVTp6UTdcD2yyEhkYWr0ixahmzqVjo0b6dzUky2tX7wIAJ/djvm557Dt20/YuLGoR43Eeayg\n13GLUSYNoeYXvwwoZgP8LTdPxKGvK7C39xiZo1trGXfBUEr2N9HaKFW5Fu9rJGNSHMljYqgvbcU4\nNJwwnYLNbxYwYnIcjeXteFw+xs4bSpvJ7jcGAGU5ZhrL20lIMzB61hB2rykLuocQZ47LLruMN954\nI2AsPT2dyspKPF2/L/Pnz/d3RetGEIR+pSWsVit79+7F4/FQVFREdHQ0cXFx/mpmgLFjxzJx4kRS\nUlJobGwkPT2dN/upwB8sAzUIWlEU9wpCQJn8AFTsQ4Q4TfSzPfbY7X5jACDabLR+8CHuhgY6uvrY\nyvR6om68EYD439yPLDwcb3Mzupkzib5Fam7T8OijtHV1Q7MfOoR29vlE3XwTrooKIi68kKhru4rx\n5fIgg+Dt9SU9Ho7W4JTZ1ka73xh001TZzk2PzkT0ibz9yB7qS7pWnaUwc1kGExdKRWjfvBGsqW/v\ncLHjwxKObhl4kDvE6eGDDz4IGistLeW+++5j69attLe3I5fLmTFjBnV1dZSWlqJSqVi4cCHZ2dns\n37/fv8OIiIjAbrf7DQlAS0sLl19+OfX19VgsFkaPHs3EiRMB/H8fj+rqan+DnoEwUINgFgQhnZ4W\nmlcDwSIyg0QQhFeRahuaRFHMPtX5Qvz/QhFpCFqVeDs7/cYApFhBy8rXCBszhsbHHwePB0VcHPEP\n/AZBIf36d2zYGDCHbcdOkl94AUEeGKAVFArErgKhwZA0IRxzVc950UN0JI+OJjxaTWdLz3hcirTb\naKm3YmkINBZlOSa/QciakcixXQ3+grbwKDUOm5tDG6sGfW8hTp0+C2U/+/fvZ+9eSRa+oKCA+vp6\nbrrpJjo7O/F4PBgMBgRB4I477uDIkSOIosjYsWP7DQTr9fqAh39ubi6FhYUYjUZmzJhBQz+y7zD4\njmkDzTL6GZK7aKQgCLXAL4HgEtfB8xpwyWmYJ8S5Tj9fuiGPPopmwgT/a7nRSMS8eUHHeTs6aPrH\nP/yre09TE6Zelc+qPisoZVISglyObd8+au+9j7rf/Q5HURHht90WNLd8AKuv9Kxklt49npHTE0ib\nEEtEdBg7Pyxh9rWZRMZLjXjih+uRKWR8+eIRWuo6g6uSY6Wq5Kq8ZnI31ZCSHU36ebFMWJjMsvsn\nYa7qv2NWiDPPjV070N5otVoO9GnWdPjwYRoaGnj99df597//zVNPPUV1dTVarZbJkyfj9Xr55JNP\nEEURrbanQVNycnJAZfLevXv56KOPyMvLY8uWLbz99tvk5OT0e2/9ieudiIFmGZUBFwqCoANkoigO\nLnR9/Hm3CoKQejrmCnGO008DErleT8rrq2j7/HM8zS1EXXM1Mr2esOxsHN0VoHI5ERctpPOrrwLO\nddfV48jPp339BrTTp+Our8drsSDT60n4wx9w5OdTufxWvxHp2LCRsCmTg+7B19Jy0lv/6Mkcbv/n\nXJx2Dxte7pEvqMpv4YaHp+G2e3j7kT3+lNPSHBNj5w4lf3sdXo+PyHgtU5cOp6bQwtpnDvsDzBq9\nih/fPApVmIIhIyLJ/SbkLjobdGcE9SYsLCxIvlqtVrNu3Tp/LMBisbBmzRruvvtuvvzyS7/KKUB2\ndjZpaWmo1WqMRiM+n89fa9A3kFxZWUlUVNRp+SwnNAiCINxznHEARFE8s9VIIUKcgJpf30/4lCmY\nn30W0e3GumULQ599huTXVtL63vt4mprQL7oUzbhxWN5YjaOrAAggLHsM5ddc649NaCZPJuF3D6JK\nTUWm0QTsKAB8HR3Ytm0PugfRaj35jXqgpqCFoj4Faa2NNpoq2nFY3VjbemU2ieB2eLjotjEc+qoK\npUpOm8lOyf7GgGwje7uLmgKLJIfhExkxJZ7qYy04OkOdbb9Ltm3bFjRmsVi47rrreO+99/wZQgsW\nLPCnnXbT3NyM2+0OqljOz89n6tSpvP/++3R0dKDT6bjmmmtITU1Fpwvs4y2Xy5k+fXq/GUfNzc3E\nHE+Lqx9OtkMYXFurM4AgCLcDt4O0dQoRohuZVovpP//x7x5s+/bRsup1Ii5aiG3PHtwNDcijogjL\nzmbYC89jfuG/uMrLCV8wn84dOwIC1fb9+0EQkGkk14wiNlgTSBYeju84qpInQ2tQozX06SUlgFav\nQq4I9tzKFALrXzyKzyt9tppjFkbNSgw6Tq6U8fYje/xZR/HD9SGD8B3TX/tMURRRKBT84he/oLq6\nmoSEBIxGI5WVlQH6RcnJySiVSiIiIvwCdiA1tvniiy/8Owyr1cpnn33GXXfdxfz586murva30Zw9\ne3ZQT+YT3duJOKFBEEXxT4Oa7QwgiuKLwIsAkydPHtynC3FOI1MoglxJztISLP/7rr9mwFRYiEyr\nJXLZVcj1egSlEjweZP1IAgu9xvSLFtH26ac48iR5bu30abgtrUEGQRiAllHS6Egay9sYOjKKqvxm\nfyB53Pyh6KLU6I0aRs9KJH+HlKcRGa9FE6HyGwMAn09ErVUSlajDUi/tSkZOT8Bc3RGQgtrtdgrx\n3aHVagN6HHezevVqbrnlFhISEvjqq69obm4mPT2dcePGUVFRQXR0NMOGDaOiooKLLrqI9957D4/H\ng1wu55JLLuHjPjLuzc3NmEwmtmzZgk6nIyMjg7lz57Jt27Z+NZEANJr+FXGPx8lcRveLovg3QRCe\nJmCzKiGK4s/7OS1EiO8EYdxYZDt3BiiUqtPT6fhyfcBxnZs3S5IVG6Vsos5vvsFwxeUIGo2/LWfE\nJZegTktD9HppeOTPtH74ISgUGK65mqhrrqHm7p/3yGf3QjT3U6zWh9r8VmrzpeKjSZemED/cwKGN\nVeRuqqFobyOzrx3B/JtGEZ9moHhfI/pYDdqIYIMVM1THlKXD2fVRCS21VgxxWpy2UPb32eZEmTxH\njhyhvLzc36/AZDIxb948UlJSWLt2LRUVFWzbto358+dzzz33sHv3bhoaGqiurvZ3RusmMzOTN998\n01/I1tzcTGxsbMCOoy9hAyic7M3JXEbdCc/76ccgnCqCILwNzAOMgiDUAA+LovjK6b5OiHOT9mee\nIXXV65ifeQZPSwuGKy5Hf/HFmF98yd/TAECVmhIkZWHdtZv0dV/Q9tnnuMrKUCYn425owLZ3L63v\nvisd5PHQ9v4HaCdM6NcYfBsOf1VN9lwfdcXSl9rR6WbT6wWotEo2ry6QNjwFFsLCFQwfb6T8sGRw\n0ibEkn5eHHs/LSd3kxQ8rim0kDwmGoVajscpub90BlVgPCLEGafpBLUocrk8qHlNUVGRX/W0mx07\ndmAwGNi6tadNq9FoZMqUKVRVVTF06FDGjRvHypUrA84rLi5Gp9MdV6IiLy+PcePGDfiznMxltLbr\nx3zgQSC11zki8PqAr9T//Dec/KgQIY6HgDIhniH/+DvmZ5+j44t1eM1m4n/zG0z/+hc+mw3NxInE\n3Hkn7V+sw9vri6mIj0em1WJZvRpPVw635bXXiLjooqCreFtbEVSqIEmLb4PPJ2KqCUwR9Xp85G+v\nDfB+OTo9jJgSj3FYOFV5zai1CqytTgp3B5b/VOe3cM1vJ1O8rwmfT6TqWHPIIHzHaDSafvsqx8bG\nMnPmTA4fPhzQQzk2NpaKioqAY0VRDHL7mM1mrrrqKhYvXgxIUhdKpRJ3r8VOXFwcM2bM4KOPPupX\n22jEiBGD+iwDrUNYDawErkIqJFsCLB3UlUKEON1YrZife466Bx6gZeVKbPv3Y37ueZwlxaS+9y5h\n48djz82l9u6fE/2/P4Gurb1MpyPu3ntpX7/ebwxAevAHNeKRy9FMnEj0T34Cx5EYHgyjzx9C8ujo\ngDG1TkF0oi7o2IayNvZ9VkFjeQfHdtaz9qnDaPWqPucqiRkawcxlGbjsHix1x2/4HuLMkJKSEjSm\nUqm48847iYqKYunSpX7XTWJiIgsWLGDGjBkBx0+bNo2IiMAcHkEQ0Ol0bN68mccff5ynn36aUaNG\noVZLyQlDhgxh7Nix1NTUMHlycEo0HF8W+3gMtFLZJIrip4OaOUSI7wBnSWlA4xuAji/X466qwtHV\nVMSekwM+H+nrv6Tpib/hLC6m9b33CMsOLo5XjxhB/EMPYXnjDYSwMNRZWVTefEuQZMVgiE/XEZ8c\nRUKagfjhesoPmxg+3oipuoOIqDBmLssgMk5L2SGzP2CcMSmO5j47idZGG3NvyGLHRyV4nF5kMoFZ\nV2cgk0lp4H2rm0N8N/R1/4D0IF67di01NTWkpKTws5/9DI/HQ25uLm+99RZRUVFcfvnlWCwWjEYj\nbrebsLAwwsPD/f2SZ82aRX19PZt7iTTm5uayfPlyIiMj8Xg8vPDCCwE7hr7I5YOTQx+oQXhYEISX\nga8Bf26UKIofDepqIUKcZsIXLMBVXY2nvseVohw6FFtOYE62/fBhWl5bRcd6KeDsKivDWVqKKj0d\nV2kpAIqEBDwtzbira4j+358QPm8eJfMXnJIxAGgstRKmDSNzWgJvP7IHj0vKSx8+3siiO8dhabBy\nYH0laROMGJekYojTEjssgq9X5QfMI5MLpJ8XCwIU7WkgNiWC4eN6spxSx8WEGuScBfpbhTudTn/1\nsMlkwul0kpCQ4G9+09jYSH19PT/5yU94+eWX/R3PYmJiWLp0KTExMRiNRr7qU1AJUF9f72+kcyJj\nAJJ6amRk5IA/y0ANwnJgJKAEunVYRSBkEEKcNbRz5kiqpjotTY89js9mQx4ZSfxvH8D87LNYd+7y\nH6sZP57OLZsDzncWFJC+YT32nBxEt5v2dV/S8rKU09Cxfj2RN954ysagm8qjzSjVcr8xACg/bKYi\n18z6V/L8QWGtXsUND08DJPdSXXEb7WY7MrnAjCvTKd7fxLZ3pZzz+tI2zNWdXHnveVgarIiiSNpE\nI2U5J898CnH6mDRpEmVlgQqzffP/CwsLgySy29ra2LFjR0D7y+bmZhwOBzExMVgsFoYMGRJ0vW6x\num7X0YkYjDGAgRuE8aIojh3UzCFCnGE0o0ZScuGFeE1mFImJJPzxYSIuugiPyYRu7ly8VhuO/Hw0\n48Yx5C+P0vjE33BX9sgMyKOjUSYmokpOxmOxUP/Q7wPmt+7ciSo1FVefAOC3ITJO6xej6035YZPf\nGADY2l0U7m6gaF8jTRXtKNQyJi9KZey8oWj1Kt5/LNA9VlfcSmlOExtfycfr6b9rVogzi6qfmpa+\nxMbGEhsbGyBzoVAo+j23ra2NZ555hubmZrRaLWPHjqW4uBiFQsH06dM5cOAAa9asYciQIURHR9Ny\nAvkUt9s9KIG7gRqE3YIgjBZFMf/kh4YI8d3Q/N8X/T976uuxvP0OgkJB7a/vl6qQBYGEP/2RqGuv\nRXS7MVx5Ja7yclwVFcgjI9HNmkXx7DmgUBDzk58g02rx9coWURqNDHnicUzPP4+7phbb7t3f6j61\nehXzfzwSURQpP2z2F5wlZUZiiNcGHV95tNnfKc3j9JGzsYrxF0irQk2foLJcIaNoT0PIGJxFjteH\noDseYDAYuOSSS3A4HNTW1tLQ0IBKpeKSSy4hPT2d/fv3++MQBoOBiooKmrv6d9tsNsrLy/n1r3+N\nXC7nnXfe8dcmmEwmRo4cycKFC5HL5bzV1UO8N3l5eUzoJQB5MgZqEM4HbhEEoRwphiAAoiiKA09w\nDRHiDOMsLaXp3//pkaQQRUz//g+a8eOpvv0OqZZArSbugd+gGjaMmp/d5T+36YkniF7+P7Sseh18\nPmQ6HVG33EzHli1EzJ9P+Lx5FIz5dgrttnYXpTlN1Ba2kjI2BkOshqh4HZlT47F3usnbVke7SXog\nxA/X43EHpg963T7azXbCdErOuziFhrI2nFYPCDBlSSrNtQPQUwrxnSOTybjppptQqVS88847WK1W\nlEolixcvZvz48djtdgoLC1m4cCGdnZ0oFArGjx/PSy+9FDBPZ2cnDocDnU4XJFFRXFzM9ddff9x7\nWLdu3RkxCCGJ6hDfe8LnzcXaR4DOZ7XS+Pd/9BSWOZ2Yn3ueyOuuDTpfERdPxsYNOEtLkWk0VN+x\nwr9jCF+w4Fvf17Dxen8xWXNtJ8mjo5m8aDjrX86j4ogZTbiSCRcOIykziuQx0Rz+uqanOQ5Sv4Pw\nSDVrnzpEVX4LukgV45YMJ2taPIZYLY3l7ZQdMuF1h3YJ3yfa29vZv38/VqsVa5cIotvtZvPmzSQm\nJrJq1Sp/UDgrK4sbbpDKsjIzM/19FEBKL21qaiI8PByj0RhQCBfbj+ZWb+69995B3fNA5a8rBzVr\niBDfAerx41GEh+NubEA7ZQpx995L88sv0/zCf/3HRF59NdadOwPO87W3E5YRXLATNmY0yOWEz5lD\n3W9+E+A+6ty0CUGvR2wfvFZQ9eHAc6ryW9j7WTkVuVLw197h5ujWWiYvSsXSYMPt8pA20Uhrox29\nUcP0K9LY93kFVfmSr9ja6uLw19VMuHAYe9eWUbingagELfHD9cQPN7BpVXBHtRBnjrlz57Jly5Z+\n32ttbfUbg26sVis7d+4MyBAqLCyksbERl8uFSqUiMzMTi8VCdHQ09fX1rFq1CoBRo0Zht9vp6OhA\nr9eTnZ3NCy+8EFD41pu+vZhPxkB3CCFCfO9wHj6ME4j/7QNE33IL7qYmUCoJv2ABglpN+MyZGK68\nEtPTTwcYCc3EicgMevSXXUbnN98gKBTo5sym5q67JWORnY0iLnjl9W2MAUBcSgRNlT3SAnpjGObq\nwLk8Lh+FexrY8X4Jvq7gc0p2DIt/Knllm6oCpQlcdg8HN1Rx4IsK/1hbk53EdMO3uscQ357jyUYA\njB49GqvVyu5e8af09PR+jz127FhAzcHkyZORy+UUFhYGHLNixQpUKhU+n4/nnnvuhA99hWJwD6m9\nEQAAIABJREFUj/iQQQjxg6f51ZUYrriCiquvwdO1nZZFRBB3zz0IcjmRV1+D6HDiOHoU5fBU7PsP\nULNCavgXNm4cw154ntILF/p3BI6jR9HNmSNVNnet4sLGjg3opzAYBF0H4VFqOi1ONBFK5v14JI1l\nbdQV9biFwnRKKvNa/MYApOByS72V6EQdQ7Oi/IFmkDSLWuoCC9fcTi+2jpD09XdNf1pGMpmMCy+8\nkOnTp+Pz+QgLC6OsrIzExETmzZtHY2MjBQUF/od5cnIyx44F7uwOHjxIZmZm0Nw2m42EhAQOHjx4\n0h2Ay+UalFE49Vr8ECHONnIZHV995TcGIDW0afvkE+r/9CdKFy6k5bXXQKFAnZ6Oq7zcf5wjN5fW\nDz8KcA+BJGMx/IP3iblzBfEPPohnAKqmx6MxH1wODwtuHsUtj83CYNSgClMwfIIRrV5F/HA9i346\nDrk8uE1oW5ONDa/k0VzXSUp2DBq9isR0A4t+Oo7YYX2kDmQC6RNP7FMOcfrpr0+LXq8nPDwcj8eD\nQqFgzpw5zJo1y1+VnJqayu23387EiRMZM2YMF154YVCBmyAIZPeppjcYDPh8Pvbu3TsgJdPB9lQO\n7RBC/OAx3n47gjr4y+Fpbqb17Xf8r227dwf0POhG0IShHDYMd3W1f0w7dSre5maib74Z2959AZXQ\n3waX3cvB9ZUYYjV8+p9D/jTRUTMTWXDzKADEhclU5bX430sdG8NXK/NxOaSsI0GAK+89D7VWyZHN\nNXg9XpKyIqktakWtUZAyNob3/7r/lO4zxODp28EMpNjBRx99hNFo5LbbbuPjjz/2p4tu3LiR5cuX\nU1lZ6a9mzsvLY9KkSTQ0NPiL2qZOnerXPqqvryciIgK3283q1asBaRcyfvx48vPz8Xq9/e4WPB7P\nGalDCBHie4l22jTML76I9rzzUGeOwFlUDEjyFep+fLXyqKiAegOZwYBMqSR83lychYV4mltQZ2TQ\n8sYbtLz8MoJaTcxt/3ta7rXdZOfghsqAmoFju+qZdGkKR7bUUpZjIi4lnPjhBhLSDbjtHiqONPuP\nFUU4trOe0oNNfiOhUMm49sHJyBUy3n5k7xkQqQ9xMnbs2HHc98xmM7t27Qroa+Byudi1axfFxcUB\nxxYXF3PHHXdQWlpKfHw8FRUVPP3004C0M7j++usDUlJ9Ph8Wi4X7778fn8/HY489FnR9u90+qCY5\nIYMQ4geNbc8eANrrPif8oosw/vRniG43EQvm47PbafrnvxB7uYO0k84jbNQoXOXlyLRaXGVlNDz8\nR+lNuZyhzz5D418fg652hqLTSesnn6KdMiVIRG+wpE2MxWHt4+MX4dBX1RzdUgtAR7ODjhYnM65M\nD0g97cbe6fYbA5CC0ZVHW4iM04aMwVniZG0q+9Mb8ng8QXLVHo+HhIQEEhISaG1t9e8EQKpe3rlz\nZ9AuwOv1nnAHcDKto76EDEKIcwbbrl0Me+o/QJe76IMPiVi4EE+TVIMg02hp+MPD0s8REQz5x99p\n6d1wxOul5bVVAbEIAK/JRPKX6751YVpMko6ho6KZumQ4NQUWagot/od3ytiYgAwkgE6LE0uDDV2U\nmvSJsZTmmACpaG34uBh/umo3mnAliekGZHIhoO1miO+Gq6++mjfeeKPf98LDw5k5cyZVVVVUd7kk\nZTIZU6ZMISYmhm3btvmPHTNmDBs2bECn0xEfHx80l8PhIDs7O6BD2rRp08jPz6eyshJBEIKMU3/z\nnIiQQQjxw0Uu76lKBsKysgDw2e1UXHsd7lpp1S1oNAz77wtU/c9y/7G+jg4sq9+UHPO9vkSCTMCw\ndCmt77/vHzMsXYIwSBnh3ugT5My6KoOcjVWU5pgYNjIavTGMuBQ9WdMS2PpuUUAGkVItZ/v7xdQU\nWECQpLDPuziF2OQI3E4vx3Y10FAq7R5iksKpK7KQv72OtImxtNRZaakLVS5/l6Snp7N48WLWrVuH\nKIpkZ2djNBoRBIGJEyei0+m46aabOHToEO3t7YwZM4bExESGDx9OYmIiNTU16HQ6vv76a/8OwGg0\nBukUjRs3jtGjR5ORkYHJZCIzM5Py8vKAVFW1Wo3T6USj0fCrX/1q0J8lZBBC/HDxelEOHYq7pgbV\n8OEYrrwSb2cn1u3b/cYAQLTbaft4DfTZbotOJ4bLltL2SVerD4WC6OW3ops2FeWwYdhzcpDptKBS\n0b5u3be+zfID7eQkV7Hr41L/mCFWw9wbsvB5RVKyo2mu6aSxoh1NhJLh44zk7+gKYotQcqCJ7DlJ\n7P+igoMbKvF5fWROjWfUrCHs/LCYon3SjqapsoPzLkkJGYSzwJQpU5gyZQq5ubmUlJQgl8uZOnWq\nX7xOpVIxderUoPNGjx7N6NGj+eSTTwLcQWazmWXLllFTU0NbWxvZ2dn+jKPeUhTvdrd77cLn8/Hw\nww8jCMEZawMhZBBC/KCJ/fV9+Do6aHzkz9T/7nc0/vWvxNx2W9BxysRENJMmYT9wwD8Wec016Bdd\nSsTChdj278eee4SGP/+ZiAsuIO5Xv8TssGN+7nkAWt8MFg4bDH3dPG0mO+W5Zra+XYi1zYUgwORF\nqUxenBpgOPznHzVzaGNPFlTR3kaGjozGVBVYi1B+yHRK9xni27Nz5042bNjgf11dXe2XozgZ/cUB\nIiMjGTv2xCLTKpUqoH2nQqH41sYAQgYhxA+c9jWf4Dh61N/v2Ge10vbll2jOOw/7wYOA1D858rrr\niL51OZbVb+IoKMDX2Un7unUISiURCy+k8a+P4a6rA6Bl5UpkmjBaTtEIdDNpaSpWs4P60p4gsVwp\no2B3vb//sSjCwfWVjFswlLTxsRz+utofZ1AoZcgVwS6r1kYraq0Cp62nZ4MhThvqnHYGaPmgCMex\nFuQRKqKuzUQ1JDzomO4U0m4KCwtpbW0lJyeH2tpaUlJSmDFjBgqFgpycHPLz84mKimL27NlMmzaN\nI0eO+FVPMzIyGDZsGOXl5ezbtw+FQsGMGTNITEykpaWF7du3Y7Vag3SP5s+ff0qfM2QQQvygkesj\n8PTRg/c2NpK2bSudW7fSuW07ndu3UX71MqKuv56Y226j9OJL/HUFnZs2Effgb/3GoJvO7TuQhYXh\nazv1DmRZU2JQKNQ0VXbQUmdFoZRx/rUjKNzTEHCczyvSVNFOQ1k7IybH02lxoNYoOO/iFGQKGQfW\nVQQcn5BuICxcxb7Py3E7vEREh+F2np6GPiF6aH6nAHvXzstnddP03CGGPDIzqJCsb3qnUqlk48aN\n5OXlAVBSUkJ7ezsJCQmsXbvWf1xFRQV33nkn1113HTt27CA8PJyFCxdSV1fH66+/7g8UFxQUsGLF\nClauXBkgl7Fo0SLkcjlJSUkkJCSc0mcNGYSzwZ7/wtEPwTAU5v0WjMFCawPG55MCo6ewTfwhE3PH\nHVK3sy96fPz6pUsQFArUaWnU3HW3P3ZgfvoZRI8nqMjMtncfMp0OXy8RMnXmCCKvuVrKSjpJWuHJ\neOvvBxA6wRCnYeHy0aSMM6LWKBBFAlJLoxK1rH85D3dXWml4lJolD09DJheoyG1m1KxEagosiD6R\npKwoNr6aLxmCGDULbx3NsR31lB8+t7qliaKIs7gVb5uTsJHRyCNO3ozmdOMo6NOAxiPiONqMdlxg\nVfiCBQt48803/amec+fO5euvvw445siRI5hMgW69pqYmcnNz+fTTT/2pqLW1tWRkZARkDblcLvbs\n2ROknVRdXc2yZctO6TN2EzII3zX7X4V190s/V++Bqj3wi0MgH1yJOQCbHoVdz4FMDuf/Cmbfc3rv\n9QdA9f/eRtTNN6EanoY9NxdBqcRraaX1o48RRV9QINldVR00hyopCcNf/0rDH/+I12JBM3EisT//\nOcq4ODTjx2PdvRt3ZRWW4zRCOSkdkventdHOjo9KSJ8cR0WumcaKdtImxOJ2eYlO0IGA5CrqotPi\npORAE7mbqv09DwyxGq68fxJv/2mP33B0NDvJ31ZHQ9m3E9/7PtPydgH2rviLoJYTe8e4ft01ZxKZ\nRoHXEVgzoIgNbmyUmprKL3/5SyorK4mLi8NoNLJ3796AFpl6vR69Xh84v0xGcXFxQF1CU1MTqamp\nQdcwGo1BY33nOxVCBuG75thnga/ba6BiBxSshdJNEJ8NF/8VIocFHrf7BTi4CsIM0q7CbYetf+95\n/+s/QfJ0SJl55j/D9wh3XR1Njz9Byhuv426op+1Dqc13+9q1/fY80M2ahcJopOX110EUUaakEHn1\nMtQjRhCxYD6WDz6g+fkXKL1wIYYrryTh9w/R+OdHT7korRtbm4vcTTXs/LDEP5aYbuD8a0ewv49L\nCMBc3RHQAKfNZCdve11A3ACgtclOXGoEVXnHb6f4Q8PdaPUbAwDR6aX53QISfjEJn81N22dlOKs7\nUKcaiFw8HEGtoP2rSuxHzcijwjBcOhxVog5bThMd22tBgIi5w9CONeKq7qBtfQXeNifaCXFEzB92\n3DllQ7R4LU7/fcgi1agSg+UqQJKxGD16tP/1pZdeyocffojH40GlUnHxxRcTGRlJRUUF7e3tCILA\nvHnz6OzsDJorKyuL+vp6f/3CqFGjmDRpEiaTyR83MBqNTJ8+/bT8e0PIIHz3RKdBaa9tpEwBh9+E\n3Pek1y1l0FYNt2/uOSbvY/jyNz2v37oWJt8aPHfN/v93BqEb685dtH26NmCsc9M3xP/+IcxPPY3P\n4SB83lzkMTHE3XcvUT+6Ecs772J5913Kll5G+Pz5xN13L42P/sVf29D67rvIo6NPmzEAyQ1UkRvo\nMqgvbcPSYGX0rCHkba2ls+vhE5cSQWR88INHLheIS9UH1C4MGx1NdKIOe4cbU9Xx5Zh/SLgag9Nn\nvY12rHvqsR9rwVlkAcDW7EB0eVEmhdPxjfTw9JjsmBusRF8/kpZ3e+SjW946huKn4zGvzMPXZVTb\nN1Yi0yqOO6c7zxJwD75WJ55OB4rwk4vLjRo1invuuYfGxkYSExP9gnQ///nPqa2tJTIyEoPBgNls\nDggqp6en+//U1taiUCj8RWaLFi1i2rRp2Gw2kpKSgmIZp0LIIHzXzLkPqnZD4xGQq+GCP8Du5wOP\nqcsBWwtoo6XXxV8Fvu9xgLIffZKUWWfmnn8AhI0bh1ynw9va6h+TRxqI/tGPiLz+eqpXrKBj/QY6\n1m9AlZbGkH/9k5ZVq/wP/85vvkHQhAUUugE4S0pAoQDPtw/WRsSosLd7iErUMfeGLA5uCOw3JQhQ\nuKeBwt0NyOQCY+YMYdjIaFLHGXE5POxfV4G9XcpGUmsVyBUyYoeFE6ZV4LC6McRpydtai88rnlOh\nJNuhYFlpAHtBC87iwIe0o7AFb2dgkxhfuwtbTmPgySJY9zf6jcFg5+ym/esaoi/PGMjHQKvVMnz4\n8IAxhUJBSkqK/7XRaOSuu+6iqKgIrVbLiBE9ccWkpKSgOWNiYoiJiRnQ9QdDyCB810QkwJ3bwVQI\nuljpoV+2WXId+Y8ZArnvQv4nEJkM+uBfCMZeA5po2PWMtMuYfQ8MnfSdfYzvC4JGQ8SCBXjbWolZ\ncQdNT/xNCgIrlRh/+UsAbDt3YuvVWtNVVoZl1etBD39fR2dADwSA8FkzUaem0tynz+1gGDk1gam9\nHh6TLk2httDid/sMH2/kwLoeI5G3rY5x84bRUNZGzoYqIuO1DBsZhd6oobmukx0f9Lib5t80ktxv\navySFacY//5eoZsQjzPfEjSuStDhtTjxNPWk1yrjdSjjdbjKe3ZNglKGKkWPbV+gUVCn6rHua4Re\nvScGOmc32gmnX2Zcp9MxceLE0z7vYAgZhLNFbFbPz5c+Ae/UgOkYhCfAqCXw5QPSe1W7JKMwcgkU\nfA6KMJj7a4gbJf2ZeVf/8/8/QTdzJu2ff077558jMxgY9tKLOIuKafv4Y2p/dheWKVOIWHhh0HmC\nRhOUWRSx8EIir7mapn/+E6+lFd2MGTSvfA13dTWaaVOx79kbNM9AsHZID36Xw8Om149RdshMeJSa\n7HlJpE+MC0o/RYTSnEb2r6vE55EeWg0CXP7LiUGpp7nf1ODoPDeb4mjHxdLyYTE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MAAAg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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c6ee7dccc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(scaled_df_peugeot405.cluster,scaled_df_peugeot405.mileage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 945,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c68bfc7da0>"
      ]
     },
     "execution_count": 945,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qleNilsKkGtNTtwiSEQLQ6tBBFM7O6M+do2DtWhQ6J7wmT0LdvDnGvDzyV30p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\n5ZuHR9Z+AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c6ee7a0710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(scaled_df_peugeot405.cluster,scaled_df_peugeot405.year)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Find Outliers Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implement By ZScore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 946,
   "metadata": {},
   "outputs": [],
   "source": [
    "def detect_outlier_zscore(data):\n",
    "    outliers = pd.DataFrame([], columns=['ID','sqdist','cluster'])\n",
    "    threshold = 3\n",
    "    mean = np.mean(data.sqdist)\n",
    "    std = np.std(data.sqdist)\n",
    "    \n",
    "    for y in data.itertuples():\n",
    "        z_score= (y.sqdist - mean)/std\n",
    "        if np.abs(z_score) > threshold:\n",
    "            outliers = outliers.append({'ID':y.ID,'sqdist':y.sqdist,'cluster':y.cluster},ignore_index=True)\n",
    "    return outliers    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implement By Quantile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 947,
   "metadata": {},
   "outputs": [],
   "source": [
    "def detect_outlier_quantile(data, percent):\n",
    "    quantile = data.sqdist.quantile(percent)\n",
    "    outliers = pd.DataFrame([], columns=['ID','sqdist','cluster'])\n",
    "    for y in data.itertuples():\n",
    "        if y.sqdist > quantile:\n",
    "            outliers = outliers.append({'ID':y.ID,'sqdist':y.sqdist,'cluster':y.cluster},ignore_index=True)\n",
    "    return outliers    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 948,
   "metadata": {},
   "outputs": [],
   "source": [
    "def outliers(df,numCluster):\n",
    "    clusters = []\n",
    "    outliers_quantile = pd.DataFrame([], columns=['ID','sqdist','cluster'])\n",
    "    outliers_zscore = pd.DataFrame([], columns=['ID','sqdist','cluster'])\n",
    "    for i in range (numCluster):    \n",
    "        clusters.append(df.loc[df.cluster == i])\n",
    "        outliers_quantile = outliers_quantile.append(detect_outlier_quantile(clusters[i],0.75), ignore_index=True)\n",
    "        outliers_zscore = outliers_zscore.append(detect_outlier_zscore(clusters[i]), ignore_index=True)\n",
    "    return outliers_zscore, outliers_quantile\n",
    "\n",
    "outliers_zscore_405, outliers_quantile_405 = outliers(scaled_df_peugeot405,number_cluster_405)\n",
    "outliers_zscore_206, outliers_quantile_206 = outliers(scaled_df_peugeot206,number_cluster_206)\n",
    "outliers_zscore_pride, outliers_quantile_pride = outliers(scaled_df_pride,number_cluster_pride)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 949,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        ID  sqdist  cluster\n",
      "0    211.0   51.01      0.0\n",
      "1    321.0   37.54      0.0\n",
      "2    468.0   38.64      0.0\n",
      "3    625.0   42.69      0.0\n",
      "4    690.0   40.39      0.0\n",
      "5    747.0   53.31      0.0\n",
      "6   1285.0   39.92      0.0\n",
      "7   1330.0   40.39      0.0\n",
      "8   1604.0   50.56      0.0\n",
      "9   3559.0   40.66      0.0\n",
      "10  5230.0  104.30      0.0\n",
      "11  5760.0   38.25      0.0\n",
      "12  6436.0   43.30      0.0\n",
      "13  6504.0   81.36      0.0\n",
      "14  6543.0   41.61      0.0\n",
      "15  7215.0   63.91      0.0\n",
      "16  7319.0   49.58      0.0\n",
      "17  7888.0   40.36      0.0\n",
      "18  7928.0   40.63      0.0\n",
      "19   247.0  102.00      1.0\n",
      "20   258.0   62.04      1.0\n",
      "21  2367.0   95.77      1.0\n",
      "22  2491.0   67.99      1.0\n",
      "23  3244.0   95.77      1.0\n",
      "24  4209.0   60.47      1.0\n",
      "25  4228.0   64.56      1.0\n",
      "26  5030.0   65.65      1.0\n",
      "27  6556.0   95.77      1.0\n",
      "28  6964.0   60.74      1.0\n",
      "29  8219.0   65.47      1.0\n",
      "..     ...     ...      ...\n",
      "52  1189.0   82.25      4.0\n",
      "53  1357.0   85.32      4.0\n",
      "54  2232.0   73.06      4.0\n",
      "55  3399.0   74.87      4.0\n",
      "56  4095.0   61.07      4.0\n",
      "57  4837.0   61.65      4.0\n",
      "58  4918.0   78.45      4.0\n",
      "59  7129.0   57.62      4.0\n",
      "60  1316.0   50.37      5.0\n",
      "61  1449.0   50.29      5.0\n",
      "62  1526.0  117.97      5.0\n",
      "63  1744.0   48.10      5.0\n",
      "64  1871.0   68.13      5.0\n",
      "65  2157.0   80.04      5.0\n",
      "66  2497.0   71.22      5.0\n",
      "67  2533.0   51.53      5.0\n",
      "68  3531.0   47.17      5.0\n",
      "69  3657.0  105.56      5.0\n",
      "70  4770.0   47.17      5.0\n",
      "71  6539.0   52.46      5.0\n",
      "72  7787.0   96.78      5.0\n",
      "73  1197.0   84.78      6.0\n",
      "74  5247.0   82.70      6.0\n",
      "75  5613.0   91.90      6.0\n",
      "76  5909.0   90.78      6.0\n",
      "77  7324.0   79.43      6.0\n",
      "78  7484.0   85.97      6.0\n",
      "79  8271.0  194.39      6.0\n",
      "80  8523.0  205.83      6.0\n",
      "81  8645.0   86.70      6.0\n",
      "\n",
      "[82 rows x 3 columns]\n"
     ]
    }
   ],
   "source": [
    "print(outliers_zscore_206)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 950,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          ID  sqdist  cluster\n",
      "0       15.0   24.72      0.0\n",
      "1       36.0   24.74      0.0\n",
      "2       37.0   26.38      0.0\n",
      "3      105.0   23.61      0.0\n",
      "4      134.0   25.01      0.0\n",
      "5      144.0   26.76      0.0\n",
      "6      148.0   24.61      0.0\n",
      "7      211.0   51.01      0.0\n",
      "8      270.0   24.98      0.0\n",
      "9      311.0   25.80      0.0\n",
      "10     321.0   37.54      0.0\n",
      "11     340.0   23.66      0.0\n",
      "12     350.0   24.89      0.0\n",
      "13     351.0   23.62      0.0\n",
      "14     358.0   31.51      0.0\n",
      "15     359.0   26.27      0.0\n",
      "16     375.0   26.93      0.0\n",
      "17     397.0   27.60      0.0\n",
      "18     408.0   23.84      0.0\n",
      "19     410.0   24.20      0.0\n",
      "20     424.0   24.35      0.0\n",
      "21     452.0   25.21      0.0\n",
      "22     465.0   23.75      0.0\n",
      "23     468.0   38.64      0.0\n",
      "24     514.0   27.30      0.0\n",
      "25     518.0   27.80      0.0\n",
      "26     523.0   31.49      0.0\n",
      "27     527.0   24.45      0.0\n",
      "28     533.0   24.43      0.0\n",
      "29     575.0   24.75      0.0\n",
      "...      ...     ...      ...\n",
      "2155  7521.0   46.87      6.0\n",
      "2156  7575.0   72.28      6.0\n",
      "2157  7598.0   47.92      6.0\n",
      "2158  7601.0   59.31      6.0\n",
      "2159  7665.0   59.60      6.0\n",
      "2160  7688.0   50.34      6.0\n",
      "2161  7700.0   58.97      6.0\n",
      "2162  7739.0   46.33      6.0\n",
      "2163  7754.0   75.43      6.0\n",
      "2164  7755.0   47.09      6.0\n",
      "2165  7807.0   57.41      6.0\n",
      "2166  7816.0   48.44      6.0\n",
      "2167  7819.0   64.03      6.0\n",
      "2168  7890.0   53.37      6.0\n",
      "2169  7922.0   49.65      6.0\n",
      "2170  7976.0   53.75      6.0\n",
      "2171  8008.0   57.87      6.0\n",
      "2172  8165.0   47.57      6.0\n",
      "2173  8205.0   48.39      6.0\n",
      "2174  8271.0  194.39      6.0\n",
      "2175  8310.0   72.44      6.0\n",
      "2176  8392.0   56.26      6.0\n",
      "2177  8413.0   49.61      6.0\n",
      "2178  8427.0   61.18      6.0\n",
      "2179  8475.0   52.25      6.0\n",
      "2180  8523.0  205.83      6.0\n",
      "2181  8542.0   46.76      6.0\n",
      "2182  8554.0   56.69      6.0\n",
      "2183  8645.0   86.70      6.0\n",
      "2184  8670.0   53.13      6.0\n",
      "\n",
      "[2185 rows x 3 columns]\n"
     ]
    }
   ],
   "source": [
    "print(outliers_quantile_206)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 951,
   "metadata": {},
   "outputs": [],
   "source": [
    "def checkTrue(x, outliers, clusterNum):\n",
    "    for i in range (clusterNum):\n",
    "        if len(outliers.loc[outliers.ID==x]) != 0:\n",
    "            return True\n",
    "    return False\n",
    "df_peugeot405['Label'] = df_peugeot405['ID'].apply(lambda x: 1 if checkTrue(x, outliers_quantile_405, number_cluster_405) else 0)\n",
    "scaled_df_peugeot405['Label'] = scaled_df_peugeot405['ID'].apply(lambda x: 1 if checkTrue(x, outliers_quantile_405, number_cluster_405) else 0)\n",
    "df_peugeot206['Label'] = df_peugeot206['ID'].apply(lambda x: 1 if checkTrue(x, outliers_zscore_206, number_cluster_206) else 0)\n",
    "scaled_df_peugeot206['Label'] = scaled_df_peugeot206['ID'].apply(lambda x: 1 if checkTrue(x, outliers_zscore_206, number_cluster_206) else 0)\n",
    "df_pride['Label'] = df_pride['ID'].apply(lambda x: 1 if checkTrue(x, outliers_quantile_pride, number_cluster_pride) else 0)\n",
    "scaled_df_pride['Label'] = scaled_df_pride['ID'].apply(lambda x: 1 if checkTrue(x, outliers_quantile_pride, number_cluster_pride) else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 952,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        ID  Label\n",
      "0        0      0\n",
      "1        1      0\n",
      "2        2      0\n",
      "3        3      0\n",
      "4        4      0\n",
      "5        5      0\n",
      "6        6      0\n",
      "7        7      0\n",
      "8        8      0\n",
      "9        9      0\n",
      "10      10      0\n",
      "11      11      0\n",
      "12      12      0\n",
      "13      13      0\n",
      "14      14      0\n",
      "15      15      0\n",
      "16      16      0\n",
      "17      17      0\n",
      "18      18      0\n",
      "19      19      0\n",
      "20      20      0\n",
      "21      21      0\n",
      "22      22      0\n",
      "23      23      0\n",
      "24      24      0\n",
      "25      25      0\n",
      "26      26      0\n",
      "27      27      0\n",
      "28      28      0\n",
      "29      29      0\n",
      "...    ...    ...\n",
      "8715  8715      0\n",
      "8716  8716      0\n",
      "8717  8717      0\n",
      "8718  8718      0\n",
      "8719  8719      0\n",
      "8720  8720      0\n",
      "8721  8721      0\n",
      "8722  8722      0\n",
      "8723  8723      0\n",
      "8724  8724      0\n",
      "8725  8725      0\n",
      "8726  8726      0\n",
      "8727  8727      0\n",
      "8728  8728      0\n",
      "8729  8729      0\n",
      "8730  8730      0\n",
      "8731  8731      0\n",
      "8732  8732      0\n",
      "8733  8733      0\n",
      "8734  8734      0\n",
      "8735  8735      0\n",
      "8736  8736      0\n",
      "8737  8737      0\n",
      "8738  8738      0\n",
      "8739  8739      0\n",
      "8740  8740      0\n",
      "8741  8741      0\n",
      "8742  8742      0\n",
      "8743  8743      0\n",
      "8744  8744      0\n",
      "\n",
      "[8745 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "print(scaled_df_peugeot206.loc[:,['ID','Label']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Decomposition PCA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 405"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 953,
   "metadata": {},
   "outputs": [],
   "source": [
    "pca = PCA(n_components=2)\n",
    "principalComponents = pca.fit_transform(scaled_df_peugeot405.loc[:,column_names])\n",
    "principalDf_405 = pd.DataFrame(data = principalComponents\n",
    "             , columns = ['principal component 1', 'principal component 2'])\n",
    "finalDf_405 = pd.concat([principalDf_405, scaled_df_peugeot405['Label']], axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 206"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 954,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "principalComponents = pca.fit_transform(scaled_df_peugeot206.loc[:,column_names])\n",
    "principalDf_206 = pd.DataFrame(data = principalComponents\n",
    "             , columns = ['principal component 1', 'principal component 2'])\n",
    "finalDf_206 = pd.concat([principalDf_206, scaled_df_peugeot206['Label']], axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pride"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 955,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "principalComponents = pca.fit_transform(scaled_df_pride.loc[:,column_names])\n",
    "principalDf_pride = pd.DataFrame(data = principalComponents\n",
    "             , columns = ['principal component 1', 'principal component 2'])\n",
    "finalDf_pride = pd.concat([principalDf_pride, scaled_df_pride['Label']], axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 956,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ep/uDDwht326czkaM8J7SNVe2bIGNG8HtPa8U7L8/jBqV9WXy8v3F47Btm/HG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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c6fa6e9908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def visualize_pca(df):\n",
    "    fig = plt.figure(figsize = (8,8))\n",
    "    ax = fig.add_subplot(1,1,1) \n",
    "    ax.set_xlabel('Principal Component 1', fontsize = 15)\n",
    "    ax.set_ylabel('Principal Component 2', fontsize = 15)\n",
    "    ax.set_title('2 component PCA', fontsize = 20)\n",
    "    targets = [0, 1]\n",
    "    colors = ['r', 'g', 'b']\n",
    "    for target, color in zip(targets,colors):\n",
    "        indicesToKeep = df['Label'] == target\n",
    "        ax.scatter(df.loc[indicesToKeep, 'principal component 1']\n",
    "                   , df.loc[indicesToKeep, 'principal component 2']\n",
    "                   , c = color\n",
    "                   , s = 50)\n",
    "    ax.legend(targets)\n",
    "    ax.grid()\n",
    "visualize_pca(finalDf_206)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 957,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       principal component 1  principal component 2\n",
      "0                  -2.283665               0.647830\n",
      "1                  -1.235477              -0.562741\n",
      "2                   1.530166              -0.536385\n",
      "3                   0.415739               0.174223\n",
      "4                  -0.461496              -1.487962\n",
      "5                   0.640407              -0.950877\n",
      "6                  -3.761366               0.864070\n",
      "7                  -2.063414              -0.906780\n",
      "8                  -0.454126              -0.137708\n",
      "9                  -1.244759              -0.359991\n",
      "10                 -0.928619              -1.702021\n",
      "11                  2.620555               0.136029\n",
      "12                 -0.056468               0.051962\n",
      "13                 -1.249505               0.799334\n",
      "14                 -0.610679              -1.558961\n",
      "15                  1.817010              -0.038233\n",
      "16                  0.397116               0.268805\n",
      "17                 -2.104090              -2.275918\n",
      "18                 -1.168929               1.387945\n",
      "19                 -1.607540              -1.725479\n",
      "20                  1.295415              -0.649163\n",
      "21                  1.767009               0.010767\n",
      "22                 -1.424437               2.147888\n",
      "23                 -0.677381              -1.219596\n",
      "24                  0.973011               0.046411\n",
      "25                  2.015961              -0.305776\n",
      "26                  0.387776               0.160637\n",
      "27                  2.063685               0.079672\n",
      "28                  0.094901               0.466912\n",
      "29                 -1.153654               0.087944\n",
      "...                      ...                    ...\n",
      "10165               0.477557               0.172594\n",
      "10166              -3.259312              -0.441795\n",
      "10167               1.028292              -0.775369\n",
      "10168               0.880051              -0.381168\n",
      "10169               0.810333               0.570107\n",
      "10170               1.097233              -0.102264\n",
      "10171               0.807005              -0.572326\n",
      "10172               0.466084              -1.041367\n",
      "10173               0.955154              -0.698969\n",
      "10174              -1.309941              -0.100434\n",
      "10175               0.042227              -1.248314\n",
      "10176               0.511975              -0.193981\n",
      "10177               1.957764               0.122494\n",
      "10178              -0.922025               1.101228\n",
      "10179              -1.595428              -2.030128\n",
      "10180               0.692710              -0.937132\n",
      "10181              -2.324239              -0.305441\n",
      "10182               2.095685               0.084813\n",
      "10183               1.696466              -0.157208\n",
      "10184               1.655478              -0.032308\n",
      "10185               0.035016               0.822088\n",
      "10186               2.705791               0.106408\n",
      "10187              -2.451616              -0.366445\n",
      "10188              -1.224812              -0.018595\n",
      "10189              -1.870448               0.949132\n",
      "10190               2.541783               0.173131\n",
      "10191              -1.197085               0.378619\n",
      "10192               1.839075              -0.016839\n",
      "10193              -0.002345               0.389415\n",
      "10194               1.278784               0.586116\n",
      "\n",
      "[10195 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "print(finalDf_405.loc[:,['principal component 1', 'principal component 2']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 958,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict(df):\n",
    "    trainX, testX, trainy, testy = train_test_split(df.loc[:,['principal component 1', 'principal component 2']], df.loc[:,['Label']], test_size=0.4, random_state=2)\n",
    "    model = KNeighborsClassifier(n_neighbors=3)\n",
    "    model.fit(trainX, trainy)\n",
    "    probs = model.predict_proba(testX)\n",
    "    probs = probs[:, 1]\n",
    "    auc = roc_auc_score(testy, probs)\n",
    "    print('AUC: %.3f' % auc)\n",
    "    fpr, tpr, thresholds = roc_curve(testy, probs)\n",
    "    pyplot.plot([0, 1], [0, 1], linestyle='--')\n",
    "    pyplot.plot(fpr, tpr, marker='.')\n",
    "    pyplot.show()\n",
    "    return trainX, testX, trainy, testy, model, probs, auc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 405"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 959,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC: 0.969\n"
     ]
    },
    {
     "data": {
      "image/png": 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PvizkJ6N6cNuILBoneO8fKBHxBg+Ge9XvHunct+8rYcaKLfxgWDe6pjTjo8kj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\ni4jEIIW7iEgMUriLiMQghbuISAz6/2W+CpO/Hk77AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c6ee7a01d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trainX_405, testX_405, trainy_405, testy_405, model_405, probs_405, auc_405 = predict(finalDf_405)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 206"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 960,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC: 0.873\n"
     ]
    },
    {
     "data": {
      "image/png": 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37EreXL+HwpwU7r1yrAZ9icgxBRPug4BtAc+LgYnHWH8T8EpbnzCz2cBsgKys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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c68c2a0c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trainX_206, testX_206, trainy_206, testy_206, model_206, probs_206, auc_206 = predict(finalDf_206)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pride"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 961,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC: 0.893\n"
     ]
    },
    {
     "data": {
      "image/png": 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+RKKNd8NdI/dDUu8PcOFjC9lRUctdU0dw8Zh+xKnRl0jU8XC464DqwVi7tYKs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\niUIKdxGRKKRwFxGJQv8PQcZv1Ph9CaYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c686d13630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trainX_pride, testX_pride, trainy_pride, testy_pride, model_pride, probs_pride, auc_pride = predict(finalDf_pride)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Precision and Recall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 962,
   "metadata": {},
   "outputs": [],
   "source": [
    "def precision_recall(model, testX, testy, probs):\n",
    "    yhat = model.predict(testX)\n",
    "    precision, recall, thresholds = precision_recall_curve(testy, probs)\n",
    "\n",
    "    f1 = f1_score(testy, yhat)\n",
    "    au = auc(recall, precision)\n",
    "    ap = average_precision_score(testy, probs)\n",
    "    print('f1=%.3f au=%.3f ap=%.3f' % (f1, au, ap))\n",
    "\n",
    "    step_kwargs = ({'step': 'post'}\n",
    "                   if 'step' in signature(plt.fill_between).parameters\n",
    "                   else {})\n",
    "    plt.step(recall, precision, color='b', alpha=0.2,\n",
    "             where='post')\n",
    "    pyplot.fill_between(recall, precision, alpha=0.2, color='b', **step_kwargs)\n",
    "    pyplot.plot([0, 1], [0.5, 0.5], linestyle='--')\n",
    "    pyplot.xlabel('Recall')\n",
    "    pyplot.ylabel('Precision')\n",
    "    pyplot.plot(recall, precision, marker='.')\n",
    "    pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 405"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 963,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f1=0.919 au=0.963 ap=0.939\n"
     ]
    },
    {
     "data": {
      "image/png": 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/vo6bWrfwp7bHus2/5OTkpSG/2vgAax/b9xXcDXV1fOGkZgCu3/AX7nly+z7zD2po4NNv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\n4FAwM7MCh4KZmRU4FMzMrOD/A91bDiWxTxdPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c68c30bfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "precision_recall(model_405,testX_405,testy_405,probs_405)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 206"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 964,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f1=0.720 au=0.758 ap=0.651\n"
     ]
    },
    {
     "data": {
      "image/png": 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WBGgHVBlY3N0nA5MB8vLydnvT0rBhu/tKEZHQ8hNf8YrzPIW5QH8z621mOcA4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\n4NKW+Oa/pwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c687376668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "precision_recall(model_206,testX_206,testy_206,probs_206)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pride"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 965,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f1=0.756 au=0.841 ap=0.773\n"
     ]
    },
    {
     "data": {
      "image/png": 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UREQkTqEgIiJxCgUREYmzTLsswMxWAF9u59vzgZV1WE4m0D43DtrnxmFH9nkX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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c68c2016d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "precision_recall(model_pride,testX_pride,testy_pride,probs_pride)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 966,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_peugeot405.to_excel(writer, sheet_name ='peugeot 405')\n",
    "df_peugeot206.to_excel(writer, sheet_name ='peugeot 206')\n",
    "df_pride.to_excel(writer, sheet_name ='pride')  \n",
    "        \n",
    "writer.save() "
   ]
  }
 ],
 "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": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}