Praktikum Data Mining. Preprocessing dan Visualisasi.

06211740000015_06211740000075_Praktikum Datmin 1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"train-data.csv\")\n",
    "data_orig = data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Name</th>\n",
       "      <th>Location</th>\n",
       "      <th>Year</th>\n",
       "      <th>Kilometers_Driven</th>\n",
       "      <th>Fuel_Type</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Owner_Type</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Seats</th>\n",
       "      <th>New_Price</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Maruti Wagon R LXI CNG</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2010</td>\n",
       "      <td>72000</td>\n",
       "      <td>CNG</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>26.6 km/kg</td>\n",
       "      <td>998 CC</td>\n",
       "      <td>58.16 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Hyundai Creta 1.6 CRDi SX Option</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2015</td>\n",
       "      <td>41000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>19.67 kmpl</td>\n",
       "      <td>1582 CC</td>\n",
       "      <td>126.2 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Honda Jazz V</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2011</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>18.2 kmpl</td>\n",
       "      <td>1199 CC</td>\n",
       "      <td>88.7 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.61 Lakh</td>\n",
       "      <td>4.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Maruti Ertiga VDI</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2012</td>\n",
       "      <td>87000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>20.77 kmpl</td>\n",
       "      <td>1248 CC</td>\n",
       "      <td>88.76 bhp</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>Audi A4 New 2.0 TDI Multitronic</td>\n",
       "      <td>Coimbatore</td>\n",
       "      <td>2013</td>\n",
       "      <td>40670</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>Second</td>\n",
       "      <td>15.2 kmpl</td>\n",
       "      <td>1968 CC</td>\n",
       "      <td>140.8 bhp</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.74</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                              Name    Location  Year  \\\n",
       "0           0            Maruti Wagon R LXI CNG      Mumbai  2010   \n",
       "1           1  Hyundai Creta 1.6 CRDi SX Option        Pune  2015   \n",
       "2           2                      Honda Jazz V     Chennai  2011   \n",
       "3           3                 Maruti Ertiga VDI     Chennai  2012   \n",
       "4           4   Audi A4 New 2.0 TDI Multitronic  Coimbatore  2013   \n",
       "\n",
       "   Kilometers_Driven Fuel_Type Transmission Owner_Type     Mileage   Engine  \\\n",
       "0              72000       CNG       Manual      First  26.6 km/kg   998 CC   \n",
       "1              41000    Diesel       Manual      First  19.67 kmpl  1582 CC   \n",
       "2              46000    Petrol       Manual      First   18.2 kmpl  1199 CC   \n",
       "3              87000    Diesel       Manual      First  20.77 kmpl  1248 CC   \n",
       "4              40670    Diesel    Automatic     Second   15.2 kmpl  1968 CC   \n",
       "\n",
       "       Power  Seats  New_Price  Price  \n",
       "0  58.16 bhp    5.0        NaN   1.75  \n",
       "1  126.2 bhp    5.0        NaN  12.50  \n",
       "2   88.7 bhp    5.0  8.61 Lakh   4.50  \n",
       "3  88.76 bhp    7.0        NaN   6.00  \n",
       "4  140.8 bhp    5.0        NaN  17.74  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6019 entries, 0 to 6018\n",
      "Data columns (total 14 columns):\n",
      "Unnamed: 0           6019 non-null int64\n",
      "Name                 6019 non-null object\n",
      "Location             6019 non-null object\n",
      "Year                 6019 non-null int64\n",
      "Kilometers_Driven    6019 non-null int64\n",
      "Fuel_Type            6019 non-null object\n",
      "Transmission         6019 non-null object\n",
      "Owner_Type           6019 non-null object\n",
      "Mileage              6017 non-null object\n",
      "Engine               5983 non-null object\n",
      "Power                5983 non-null object\n",
      "Seats                5977 non-null float64\n",
      "New_Price            824 non-null object\n",
      "Price                6019 non-null float64\n",
      "dtypes: float64(2), int64(3), object(9)\n",
      "memory usage: 658.5+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PREPROCESSING"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Variabel Mileage, Engine, dan Power ada satuannya.\n",
    "2. New_Price terlalu banyak missing values (824 nonmissing dari 6019).\n",
    "\n",
    "Solusi:\n",
    "1. Diambil angkanya saja\n",
    "2. Didrop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mileage</th>\n",
       "      <th>Mileage_Unit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>km/kg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>19.67</td>\n",
       "      <td>kmpl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>18.2</td>\n",
       "      <td>kmpl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>20.77</td>\n",
       "      <td>kmpl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>15.2</td>\n",
       "      <td>kmpl</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  Mileage Mileage_Unit\n",
       "0    26.6        km/kg\n",
       "1   19.67         kmpl\n",
       "2    18.2         kmpl\n",
       "3   20.77         kmpl\n",
       "4    15.2         kmpl"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['Mileage', 'Mileage_Unit']] = data['Mileage'].str.split(\" \", expand=True)\n",
    "data[['Mileage', 'Mileage_Unit']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.drop('Mileage_Unit', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Engine'] = data['Mileage'].str.split(\" \", expand=True)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Power'] = data['Power'].str.split(\" \", expand=True)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Mileage'] = pd.to_numeric(data['Mileage'], errors = 'coerce')\n",
    "data['Engine'] = pd.to_numeric(data['Engine'], errors = 'coerce')\n",
    "data['Power'] = pd.to_numeric(data['Power'], errors = 'coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6019 entries, 0 to 6018\n",
      "Data columns (total 14 columns):\n",
      "Unnamed: 0           6019 non-null int64\n",
      "Name                 6019 non-null object\n",
      "Location             6019 non-null object\n",
      "Year                 6019 non-null int64\n",
      "Kilometers_Driven    6019 non-null int64\n",
      "Fuel_Type            6019 non-null object\n",
      "Transmission         6019 non-null object\n",
      "Owner_Type           6019 non-null object\n",
      "Mileage              6017 non-null float64\n",
      "Engine               6017 non-null float64\n",
      "Power                5876 non-null float64\n",
      "Seats                5977 non-null float64\n",
      "New_Price            824 non-null object\n",
      "Price                6019 non-null float64\n",
      "dtypes: float64(5), int64(3), object(6)\n",
      "memory usage: 658.5+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.drop('New_Price', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6019 entries, 0 to 6018\n",
      "Data columns (total 13 columns):\n",
      "Unnamed: 0           6019 non-null int64\n",
      "Name                 6019 non-null object\n",
      "Location             6019 non-null object\n",
      "Year                 6019 non-null int64\n",
      "Kilometers_Driven    6019 non-null int64\n",
      "Fuel_Type            6019 non-null object\n",
      "Transmission         6019 non-null object\n",
      "Owner_Type           6019 non-null object\n",
      "Mileage              6017 non-null float64\n",
      "Engine               6017 non-null float64\n",
      "Power                5876 non-null float64\n",
      "Seats                5977 non-null float64\n",
      "Price                6019 non-null float64\n",
      "dtypes: float64(5), int64(3), object(5)\n",
      "memory usage: 611.4+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.drop('Unnamed: 0', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6019 entries, 0 to 6018\n",
      "Data columns (total 12 columns):\n",
      "Name                 6019 non-null object\n",
      "Location             6019 non-null object\n",
      "Year                 6019 non-null int64\n",
      "Kilometers_Driven    6019 non-null int64\n",
      "Fuel_Type            6019 non-null object\n",
      "Transmission         6019 non-null object\n",
      "Owner_Type           6019 non-null object\n",
      "Mileage              6017 non-null float64\n",
      "Engine               6017 non-null float64\n",
      "Power                5876 non-null float64\n",
      "Seats                5977 non-null float64\n",
      "Price                6019 non-null float64\n",
      "dtypes: float64(5), int64(2), object(5)\n",
      "memory usage: 564.4+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Variabel Name diambil mereknya saja, tidak usah tipe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0              Maruti Wagon R LXI CNG\n",
       "1    Hyundai Creta 1.6 CRDi SX Option\n",
       "2                        Honda Jazz V\n",
       "3                   Maruti Ertiga VDI\n",
       "4     Audi A4 New 2.0 TDI Multitronic\n",
       "Name: Name, dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Name'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Make'] = data['Name'].str.split(\" \", expand=True)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Make'] = data['Make'].str.upper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.drop('Name', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Location               0\n",
       "Year                   0\n",
       "Kilometers_Driven      0\n",
       "Fuel_Type              0\n",
       "Transmission           0\n",
       "Owner_Type             0\n",
       "Mileage                2\n",
       "Engine                 2\n",
       "Power                143\n",
       "Seats                 42\n",
       "Price                  0\n",
       "Make                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mileage</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Seats</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Make</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>MARUTI</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>HYUNDAI</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>HONDA</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AUDI</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NISSAN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>VOLKSWAGEN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TATA</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>LAND</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>MITSUBISHI</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>RENAULT</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>MERCEDES-BENZ</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>BMW</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>MAHINDRA</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>FORD</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>PORSCHE</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DATSUN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>JAGUAR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>VOLVO</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>SKODA</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>MINI</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>FIAT</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>JEEP</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>SMART</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AMBASSADOR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ISUZU</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>FORCE</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>BENTLEY</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>LAMBORGHINI</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Mileage  Engine  Power  Seats\n",
       "Make                                        \n",
       "MARUTI             0.0     0.0   36.0   14.0\n",
       "HYUNDAI            0.0     0.0   49.0    7.0\n",
       "HONDA              0.0     0.0    7.0    7.0\n",
       "AUDI               0.0     0.0    1.0    0.0\n",
       "NISSAN             0.0     0.0    2.0    0.0\n",
       "TOYOTA             1.0     1.0   16.0    1.0\n",
       "VOLKSWAGEN         0.0     0.0    1.0    0.0\n",
       "TATA               0.0     0.0    3.0    0.0\n",
       "LAND               0.0     0.0    3.0    3.0\n",
       "MITSUBISHI         0.0     0.0    0.0    0.0\n",
       "RENAULT            0.0     0.0    0.0    0.0\n",
       "MERCEDES-BENZ      0.0     0.0    2.0    0.0\n",
       "BMW                0.0     0.0    5.0    5.0\n",
       "MAHINDRA           1.0     1.0    3.0    0.0\n",
       "FORD               0.0     0.0    5.0    2.0\n",
       "PORSCHE            0.0     0.0    2.0    0.0\n",
       "DATSUN             0.0     0.0    0.0    0.0\n",
       "JAGUAR             0.0     0.0    0.0    0.0\n",
       "VOLVO              0.0     0.0    0.0    0.0\n",
       "CHEVROLET          0.0     0.0    1.0    0.0\n",
       "SKODA              0.0     0.0    1.0    0.0\n",
       "MINI               0.0     0.0    0.0    0.0\n",
       "FIAT               0.0     0.0    5.0    3.0\n",
       "JEEP               0.0     0.0    0.0    0.0\n",
       "SMART              0.0     0.0    1.0    0.0\n",
       "AMBASSADOR         0.0     0.0    0.0    0.0\n",
       "ISUZU              0.0     0.0    0.0    0.0\n",
       "FORCE              0.0     0.0    0.0    0.0\n",
       "BENTLEY            0.0     0.0    0.0    0.0\n",
       "LAMBORGHINI        0.0     0.0    0.0    0.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['Make', 'Mileage', 'Engine', 'Power', 'Seats']].set_index('Make').isna().sum(level=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\asus\\Anaconda3\\lib\\site-packages\\numpy\\lib\\histograms.py:824: RuntimeWarning: invalid value encountered in greater_equal\n",
      "  keep = (tmp_a >= first_edge)\n",
      "C:\\Users\\asus\\Anaconda3\\lib\\site-packages\\numpy\\lib\\histograms.py:825: RuntimeWarning: invalid value encountered in less_equal\n",
      "  keep &= (tmp_a <= last_edge)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data['Mileage'], bins=20, color=\"peachpuff\")\n",
    "plt.title(\"Histogram Mileage\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data['Engine'], bins=20, color=\"darksalmon\")\n",
    "plt.title(\"Histogram Mesin Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data['Power'], bins=20, color=\"rosybrown\")\n",
    "plt.title(\"Histogram Tenaga Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mileage dan Engine distribusinya tidak skewed, imputasi menggunakan mean.\n",
    "\n",
    "Power distribusinya skewed, imputasi menggunakan median.\n",
    "\n",
    "Imputasi dilakukan menggunakan mean/median tiap merek."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Mileage'] = data[['Make','Mileage']].groupby('Make').transform(lambda x: x.fillna(x.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Engine'] = data[['Make', 'Engine']].groupby('Make').transform(lambda x: x.fillna(x.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Power'] = data[['Make', 'Power']].groupby('Make').transform(lambda x: x.fillna(x.median()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.,  7.,  8.,  4.,  6.,  2., nan, 10.,  9.,  0.])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Seats'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Seats'] = data['Seats'].replace(0, np.nan)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tidak mungkin mobil punya 0 tempat duduk."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0     5014\n",
       "7.0      674\n",
       "8.0      134\n",
       "4.0       99\n",
       "6.0       31\n",
       "2.0       16\n",
       "10.0       5\n",
       "9.0        3\n",
       "Name: Seats, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Seats'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Seats'] = data['Seats'].fillna(data['Seats'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0     5057\n",
       "7.0      674\n",
       "8.0      134\n",
       "4.0       99\n",
       "6.0       31\n",
       "2.0       16\n",
       "10.0       5\n",
       "9.0        3\n",
       "Name: Seats, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Seats'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Seats'] = data['Seats'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6019 entries, 0 to 6018\n",
      "Data columns (total 12 columns):\n",
      "Location             6019 non-null object\n",
      "Year                 6019 non-null int64\n",
      "Kilometers_Driven    6019 non-null int64\n",
      "Fuel_Type            6019 non-null object\n",
      "Transmission         6019 non-null object\n",
      "Owner_Type           6019 non-null object\n",
      "Mileage              6019 non-null float64\n",
      "Engine               6019 non-null float64\n",
      "Power                6018 non-null float64\n",
      "Seats                6019 non-null int32\n",
      "Price                6019 non-null float64\n",
      "Make                 6019 non-null object\n",
      "dtypes: float64(4), int32(1), int64(2), object(5)\n",
      "memory usage: 540.9+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[915]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['Power'].isnull()].index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "93.7"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Power'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\asus\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "data['Power'][915] = 93.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "93.7"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Power'][915]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Location</th>\n",
       "      <th>Year</th>\n",
       "      <th>Kilometers_Driven</th>\n",
       "      <th>Fuel_Type</th>\n",
       "      <th>Transmission</th>\n",
       "      <th>Owner_Type</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Seats</th>\n",
       "      <th>Price</th>\n",
       "      <th>Make</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2010</td>\n",
       "      <td>72000</td>\n",
       "      <td>CNG</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>26.60</td>\n",
       "      <td>26.60</td>\n",
       "      <td>58.16</td>\n",
       "      <td>5</td>\n",
       "      <td>1.75</td>\n",
       "      <td>MARUTI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Pune</td>\n",
       "      <td>2015</td>\n",
       "      <td>41000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>19.67</td>\n",
       "      <td>19.67</td>\n",
       "      <td>126.20</td>\n",
       "      <td>5</td>\n",
       "      <td>12.50</td>\n",
       "      <td>HYUNDAI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2011</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>18.20</td>\n",
       "      <td>18.20</td>\n",
       "      <td>88.70</td>\n",
       "      <td>5</td>\n",
       "      <td>4.50</td>\n",
       "      <td>HONDA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2012</td>\n",
       "      <td>87000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First</td>\n",
       "      <td>20.77</td>\n",
       "      <td>20.77</td>\n",
       "      <td>88.76</td>\n",
       "      <td>7</td>\n",
       "      <td>6.00</td>\n",
       "      <td>MARUTI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Coimbatore</td>\n",
       "      <td>2013</td>\n",
       "      <td>40670</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>Second</td>\n",
       "      <td>15.20</td>\n",
       "      <td>15.20</td>\n",
       "      <td>140.80</td>\n",
       "      <td>5</td>\n",
       "      <td>17.74</td>\n",
       "      <td>AUDI</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Location  Year  Kilometers_Driven Fuel_Type Transmission Owner_Type  \\\n",
       "0      Mumbai  2010              72000       CNG       Manual      First   \n",
       "1        Pune  2015              41000    Diesel       Manual      First   \n",
       "2     Chennai  2011              46000    Petrol       Manual      First   \n",
       "3     Chennai  2012              87000    Diesel       Manual      First   \n",
       "4  Coimbatore  2013              40670    Diesel    Automatic     Second   \n",
       "\n",
       "   Mileage  Engine   Power  Seats  Price     Make  \n",
       "0    26.60   26.60   58.16      5   1.75   MARUTI  \n",
       "1    19.67   19.67  126.20      5  12.50  HYUNDAI  \n",
       "2    18.20   18.20   88.70      5   4.50    HONDA  \n",
       "3    20.77   20.77   88.76      7   6.00   MARUTI  \n",
       "4    15.20   15.20  140.80      5  17.74     AUDI  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6019 entries, 0 to 6018\n",
      "Data columns (total 12 columns):\n",
      "Location             6019 non-null object\n",
      "Year                 6019 non-null int64\n",
      "Kilometers_Driven    6019 non-null int64\n",
      "Fuel_Type            6019 non-null object\n",
      "Transmission         6019 non-null object\n",
      "Owner_Type           6019 non-null object\n",
      "Mileage              6019 non-null float64\n",
      "Engine               6019 non-null float64\n",
      "Power                6019 non-null float64\n",
      "Seats                6019 non-null int32\n",
      "Price                6019 non-null float64\n",
      "Make                 6019 non-null object\n",
      "dtypes: float64(4), int32(1), int64(2), object(5)\n",
      "memory usage: 540.9+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Kilometers Driven ada outlier yang terlalu parah. Diindikasikan noise salah input berupa terlalu banyak angka 0 satu buah."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([2328], dtype='int64')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['Kilometers_Driven']>6000000].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\asus\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "data['Kilometers_Driven'][2328] = 650000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# VISUALISASI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(data['Price'], bins=50, color=\"c\")\n",
    "plt.title(\"Density Plot Harga Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='Make', x='Price', data=data, order=data.groupby('Make').median()['Price'].sort_values(ascending=False).index)\n",
    "plt.title(\"Boxplot Harga untuk Masing-Masing Merek Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "count = data['Make'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Npw45ArjezFYCrk/7ANsCK6XPvrjSCoIgCNpIVWXxjqRZgCmSDpD0KWCx/lwwBfdtBvwawMzeNbNXgB2B2hzJWcBOaXtH4GxzbgcWlLRkf64dBEEQ9I+q6T4OAebGEwh+Dx9VTOjnNVcApgO/kbQ27mF1MLC4mT0HYGbPSaopozFANuPttFT2XD+vP2BWWnLt0jpTnru/DZIEQRC0h6pBeXelzTeAzw/CNdcDDjSzOyT9lF6TUxEqEqmukrQvbqZi2WWXHaCIQRAEQZayoLzLmx03sx36cc1pwDQzuyPtX4Qri+clLZlGFUsCL2TqL5M5f2ng2QJZTgdOBxg3blydMgmCIAj6T9nI4kO4Ceh84A6Ke/ktYWb/lPS0pFXM7O/AFsDD6TMB+EH6+/t0yuXAAZImAhsBr9bMVUEQBEF7KFMWSwBbAuOB3YGrgPPNbPIAr3sgcG5aSOkx3LQ1C3ChpH2Ap4CdU90/AJ8ApgJvMXAzWBAEQdAiZRHc7wFXA1dLmgNXGjdJOtbMTu7vRc3sPmBcwaEtCuoasdBSEARBRymd4E5KYjtcUYwFTgIuGVqxgiAIgm6ibIL7LGBN4I/AMWb2UFukCoIgCLqKspHFnsCbwMrAQVLP/LZwC9H8jU4MgiAIRg5lcxZVI7yDIAiCEUwogyAIgqCUUBZBEARBKaEsgiAIglJCWQRBEASlhLIIgiAISgllEQRBEJQSyiIIgiAoJZRFEARBUEooiyAIgqCUUBZBEARBKaEsgiAIglJCWQRBEASlhLIIgiAISgllEQRBEJQSyiIIgiAoJZRFEARBUEooiyAIgqCUUBZBEARBKaEsgiAIglJCWQRBEASlhLIIgiAISumYspA0StK9kq5M+8tLukPSFEkXSJo9lc+R9qem42M7JXMQBMHMSidHFgcDj2T2fwicaGYrAS8D+6TyfYCXzewDwImpXhAEQdBGZu3ERSUtDWwHHAccKknA5sDuqcpZwNHAacCOaRvgIuAUSTIza6fM/WWdZTYqrXPf03e0QZIgCIL+06mRxU+AbwLvp/1FgFfMbEbanwaMSdtjgKcB0vFXU/0gCIKgTbRdWUj6JPCCmd2dLS6oahWOZdvdV9IkSZOmT58+CJIGQRAENToxstgU2EHSE8BE3Pz0E2BBSTWz2NLAs2l7GrAMQDq+APBSvlEzO93MxpnZuNGjRw/tHQRBEMxktF1ZmNm3zGxpMxsL7AbcYGafA24EPpuqTQB+n7YvT/uk4zcMl/mKIAiCkUI3xVkcjk92T8XnJH6dyn8NLJLKDwWO6JB8QRAEMy0d8YaqYWY3ATel7ceADQvqvAPs3FbBgiAIgj5008giCIIg6FJCWQRBEASlhLIIgiAISgllEQRBEJQSyiIIgiAoJZRFEARBUEooiyAIgqCUUBZBEARBKaEsgiAIglI6GsEd9GWTsZuV1vnrEze3QZIgCIK+hLIYpmy54palda77x3VtkCQIgpmBMEMFQRAEpcTIYiZhp5W3a3r8skevapMkQRAMR2JkEQRBEJQSyiIIgiAoJZRFEARBUEooiyAIgqCUmOAO6thztZ1K65zzyGVtkCQIgm4hlEUwIL68evmKtz9/+HdtkCQIgqEkzFBBEARBKaEsgiAIglJCWQRBEASlhLIIgiAISokJ7qBtfH3N3Urr/OihiW2QJAiCVomRRRAEQVBK25WFpGUk3SjpEUmTJR2cyheWdJ2kKenvQqlckk6SNFXSA5LWa7fMQRAEMzudGFnMAA4zs9WAjYH9Ja0OHAFcb2YrAdenfYBtgZXSZ1/gtPaLHARBMHPTdmVhZs+Z2T1p+3XgEWAMsCNwVqp2FlALI94RONuc24EFJS3ZZrGDIAhmajo6ZyFpLLAucAewuJk9B65QgMVStTHA05nTpqWyIAiCoE10TFlImhe4GDjEzF5rVrWgzAra21fSJEmTpk+fPlhiBkEQBHRIWUiaDVcU55rZJan4+Zp5Kf19IZVPA5bJnL408Gy+TTM73czGmdm40aNHD53wQRAEMyGd8IYS8GvgETP7cebQ5cCEtD0B+H2mfK/kFbUx8GrNXBUEQRC0h04E5W0K7Ak8KOm+VHYk8APgQkn7AE8BtXSmfwA+AUwF3gI+315xg05w9JqfK6/z0LltkCQIAuiAsjCzWymehwDYoqC+AfsPqVBBEARBUyLdRzDsOWHNPUrrHPbQb9sgSRCMXCLdRxAEQVBKKIsgCIKglFAWQRAEQSmhLIIgCIJSYoI7mKn4+Rp7ltb58uRz2iBJEAwvYmQRBEEQlBLKIgiCICgllEUQBEFQSsxZBEETfrtGecDfHpMj4C8Y+cTIIgiCICgllEUQBEFQSiiLIAiCoJRQFkEQBEEpMcEdBIPEpWvtXlrnUw+c1wZJgmDwiZFFEARBUEooiyAIgqCUUBZBEARBKaEsgiAIglJigjsIOsB1G+5WWmfLOye2QZIgqEaMLIIgCIJSQlkEQRAEpYSyCIIgCEqJOYsg6HL+8rFdSutseuOFbZAkmJmJkUUQBEFQSowsgmAEce/2O5fWWfeK3wEwefxnS+uucf5FPduP7rdraf2Vf3FBaZ1geDJslIWkbYCfAqOAX5nZDzosUhAEDfjH18sXjVrxR75o1BPHfKm07tijfjlgmYKBMSyUhaRRwKnAlsA04C5Jl5vZw52VLAiCdvLUCQeX1ln2sJ8C8Mzp3ymtO2bf/xmwTDMLw2XOYkNgqpk9ZmbvAhOBHTssUxAEwUzDsBhZAGOApzP704CNOiRLEAQjjOfO+9/SOkvu/q2e7ecvP6Vp3cV3OKBne/r1Z5e2PXqLvQB46c4rSusuvOH2ALw6+ZbSugus8REA3njygdK68y63VtPjMrPSRjqNpJ2Brc3si2l/T2BDMzswU2dfYN+0uwrw94KmFgX+VfGyQ1W3W+QYbnW7RY5uqNstcnRD3W6RoxvqDkbby5nZ6MLaZtb1H+BDwDWZ/W8B3+pHO5M6Xbdb5BhudbtFjm6o2y1ydEPdbpGjG+oOddvDZc7iLmAlSctLmh3YDbi8wzIFQRDMNAyLOQszmyHpAOAa3HX2DDOb3GGxgiAIZhqGhbIAMLM/AH8YYDOnd0HdbpFjuNXtFjm6oW63yNENdbtFjm6oO6RtD4sJ7iAIgqCzDJc5iyAIgqCDhLLoAJIW77QMwxFJy0j6Rqfl6AYkLddpGYKZi1AWg0gzJSBpAUlfkPQn4J42ijWskbSopK9Iuhm4CRiQopU0rCL/JX1I0mclLZb215J0HnBrg/oHFJW3G0mzS1pV0irJg3Gg7W0k6X5Jb0i6TdLqgyHncEXS91usP+DOxYids5B0BdDw5sxsh0G6zgLAZ4DdgdXMbEzm2FzADunYesB8wE7AzWb2fkFb5wPHmtkjBcfOMbM90/ayzWQys6cKzp8V2BZYNRU9AlxtZjMq3uemwO5mtn+m7EXgduCvwF+AO83srSrtlVxrPuBT+P9tZeBSYFczW7ri+SsC44HdzGzN3LF7zGy9iu1ca2ZbVay7WbPjZnZzrv4E4GA8gBT8+zjJzM7O1Dke+CRwH/AB4Ergq8D3gV+Y2TsFcrRyfyfT/Bk5qEo7uTZHAd/DA2SfwTukS+KTqd/N/94kXWhmu6TtH5rZ4ZljPf9/SZPw+Kqb8Wfqi2a2dYksNza5PzOzLVqVI+0/mGvX8OC2G4EfZb8XSQs3k9HMXiq5hwWB/c3suFx55e851Z8K/CrJV+mZzzNsvKH6wY+qVpT0OsU/KuE/qvlz9RsqgUydc4HNgGuBU4Ab8PxWNzUR5ePAJpL+z8xOzR1bI7N9VZJXmTIDRgOL4e7FWXmXwn/IzwH3pvM+CZwg6WNm9myRMJLWSfe4C/A4cEmuyvLAxsAmwJHA+pIeIykPM7sw01b2f1yTu3YP+f/xC8CdwHeAW83MJH2qSMZM+0sCuyZ51wL+F1cYA6E4krWYIvOYAWsDS5P5TiTtBRwCHIqPMoX/jo6XREZhbAesa2bvSFoIeBZYy8ymtHwnxUyqWrGFZ+SHeGTwimb2ajp3QeAE4Hjga7nzV8psbwkcntnP/v9nMbPr0vbvJH2Lcr5eULYx8E38N9YfOcCfnTwLAxOAk4FsGt27qX9WaxiwAriJFfhvYCngMuA8XOnuCZxfcO6o9JsoardICa0LHAvcLenAfOelEq1E8A2nD3DmELV7Lp6n6tf4j2oU8HhBvfuBB/Af7DKp7LGStu8FlsDjSa4EFs0cu6fJeWOB04ApwIFF/wvgkILyg4CzcmUrA9/Fe7q3AgcCT1b838wDHABMBd4bwP/4a8AdwEO4Elqx0f8OfzBvAB4F/gdXFHXfR6b+W/gLOv+5N/8/Bh4DPt3oU3IPHwb+iI+8ts8dux0Y2+B7vD2zf3fu+H0V/nczgNcKPq8Drw3FM5G7/hT8xZ4vnxWYUlB+T9F2wbH8d9Fnv4Jc/wX8CbgF2La/clS4zr39/L/dCBwNbA2ciL87zgeWaFD/3+l/8HjBp+F7BlgfeCU9Ww8ADwIPVJFxJI8smmfFKkHSPPhoYXcz2y5zaE3gZfxl+jcze09SXY/LzNaWtCre0/2TpBeA+SQtYWb/bHBZS8e2lnQoMEnSV8zsjxT0ICStBHwbT6p4AnCQmf2noN2NzWzvgoudJCmfQ+tv+AO1vZlNTdfJ9wZr118KH1VsAmyQiu/GRwS3NTjng/Sawh62guBKMzsROFHSCvjo4DJgKUmHA5ea2aOZ6qema+1uZpPSNZrZVh8HylcIchbAe5GNeoX5kRaStsB7iAZ833p7w1nmN7Mn6ho0e0JSdoS1oqRspoKx2X0rNqU+aGbrFt1MgaxDYao1KzCxmgfWFl1rbknr4uaqudK20meuTL2bge0z+3/O7Bd+FwCStsa/j3eA48zsxgZyV5WjjD7zwC2YjBc2s6PT9jWSngc2MLN/Nzj14arfc0aWzfE1gX6FPzd131MzRrKymDvzhddhZnWTzGki7hP4C34b4GLg57nzKisBM/sb3kv/rqRx+IvvTknTzGyTZsKb2Y8lXQ/8VtIngJ5JQklr4kpiDeD/gH3M7L0mzb3d5Fh+juEzeDqVGyVdjaeDL/wf4tl/78F7QkeYp48vJM3t/B5YFh91CfigpKeAHc3stfw5ZvYYcBxwXFIy4/He+oqZakvhL/8fJweDC4HZmtzvu2b2jybHszxpZl+oUlHSdvh38irwbTP7S5Pqzb6P7LH8ZPwJVWRpgZqpVsAvgS82qpgxQ+VNn7MCs5tZ7V3yiKTdzey83PnjKU7u+U/gxwXbtX2/UEFnpwxJd+EmpONJnRdJPXb+3Dugkhz5NjIsBOxBxhSdqGwyzpmV/om/w+ZJsjad2yhD0kQ8e/fuZvZgv9pIQ5MRR/px30WDXqGZbZ6puyX+ItoaHw5eAJxsZmMrXGeDdO5ngR4lIOkAM6vLYyxJwGZm9ueCY/fmewuS5sRfEl8xs1lS2Xu4KewqoE5JWG5iMs0jFNlvBfyfma1Yd6B3ZDUe2Bw4C+/VX5up8yE8yeMm+PzFE/hDeRuepOzfmbonAe8C36z1PCXNAvwAmMv6ZhCuPLGck3kZfN5iPDB3kvfIXJ3TzOwrDc7/jJldnNmv+z6aXPt9XHneT0FvPdtLl/QWbqqrawZYwczmKbnWMvjk/fEFx440s0JPGUkbmNldDY5VvtdUfz58sn0//P98WEa2y/DRd81evwGwILCTmT1d3GLp9X5iZoek7YPN7KeZY2cWKRNJN9F8gnvzBsfKZMmPTgx4EffWO73B6L527lh8PuTjuEPDyan8Cbyn3+h9tUKunb3N7MwG11jOzJ7MlX3JzAa03OBIVhatPui3AHub2eOp7LH8F1TSRh8l0Kq3QjpnlqIhfDq2pJk9l7b3prn54Kzcub9pdl0z+3yJXAvjvfddmz1g6UHYHvfyWdrM5swcexifnM17w8yKm05Wy5S19OJqIMsq+Av1mBbOecrMls3sr2VmD6TtOXLKb2Mzuz2z/1/N2s52DlTixph/0NM5i+LfwXi8h3ipmRV1APLnrY6PFMcDr5rZuAb1Kv1e02T1IcBe+CTsiWb2YkG9rfCRr4DJwLVW8LKR9Olm1zOzS/Ly5WXtz7NWILrI22QAACAASURBVMce+PvwnFz5l4A38yOlfrSfNxmf1UypVGzzQ/hv4WYze0HSWsARwEfMbJlc3ZaVbZ6RbIZqhfXxB+pPqRc+kZxHURZJH8MnfrNuj6dYc0+nKuzhOqcQA84BaNSjSLLVfadlyqAMM3tJ0gUUeAclk1xt3mJTfDh+GznzHW7+qXPZS7bsvF12gWYvkdoLJCPDIrhZMOsWfH4riqLWVG7/TNxLCfyesi+kn2X3i0aKSbZl8N/WnzN165RBg3OLXIhXsBIX4qSMxqfPDGA5YFx+nkR93TrrvGuypo+krA7DR25n4F5arxZcu+bJc0V2FNqE7XPb2dV/snMR2e+m4UOSkyX/G6q5uN5nZq/njh2Gey/muQC3NvQoC0m34abGGwqueb31dcmtbDJOZvDPpboGPAycVzRvIen/8P/XfcDhkrJu1UWm0+y9TcDnLmpUmt8dycrim1Urmtm9uDfM4fJ4gvHA7JL+iPfgehJuJdv0Kbgb2jHQ4/Z4RjI91ZIdriWpzg6f6pvl3HETGxSUCf9RjCEpC0m3mtmH03ZP/EXiTvq+1GpyjwIWMrN/pf3Zgb2Br+V69ZVd+CT9C3fH/Ss+MvuBpUnxAuZU8RySgDlyZZUnliWthntDXUOvW/AGwJFyt+AiO3kj8j3fZi+ohi+solFA7vjjuWsps28Zs2B/XIj/iv//JgKfNbMpkh7PK4pE3q0za8PvcetMPAlMB36Dz3Ptk+3YmFnNxn8OrhxPkXQd/ptpGM+T7cikEWWjjs0sSZnNktmuCdCoY7d9QdnC+LO5T+5lP6pAgWBmr0nKz4Eti9/fH/B1dbIjhHxcxf30mow3BDbM/d8Ogp4R4OV4vNLd6d4+Cnxb0o5W7wjySVpzq25Z2eYZycrix+rrfdEwcCaL+cTkXyQdhLvG7kbf7IzfwG2v92fK7pMHDZ1Mb2bcyl4pmWtn7fbCexmH466W2aCcrE07G38BBT8ESbsBvwDelDQFd9E7B5/T+Vyu+tl4L/hifJL/dtyMsJbVe3H1+NJXID9pmD+WpfLEMq7IDrZMTAf4/APey/pMrjwfUNVziPro8Pzvp9GxVkcBeVPQLHgsy9dxhVfjSPz3dxpwXhrdlTEdj+tYHB8JTimQ3W/AbPkK7dU4PtPOfI0qpTmfi9U757Uf8Eu559X51tgbiUZyJhag9yUK9YqtSJZCxZNGXhfSd2nm2STNY2Zv5urOR8a5JPE87hp9EnCHpPGZTkleln0ayZfjZHxeso/3nKSP453Tj+Xqv117h5nZy5L+3kRRQP+UbR9G8pxFkV24Fjgzj5l9KVe/UoSzpL+Z2aoUkD3WX7t7kmNvfFh8B/C/+d5xq/ZbSQ/hCm6q3JPjNtye36fHm+reb2ZrZ/afB5ZtMBQ+qdm9WD8igFO7rcw3/d3MVql6rJX5ArmnW80bbNe0TdrfxcwWz9R9m/pRQNN5L/kE/554B+Q+3NX24YJ6NRfi3fDgsaOodyHO1q9lFRiPR34viC9LfGeu3nLAK9YbPPcx/AX/BHCqNfFuawW5J9vZeIejmXl3wHMPLciUf26+DmyBv7CfSGVjcRfTmyzjTJB7/j6Fm3S+b2Y/H8Bz3+y98kh29J/KXqGv59Vm2X3LuT2rxQn0IkbsyKKBXfhJ4F5J2d4bah7h/FFLE8uJPj2PHNljv2tVZkn745PD1wPbNLFtL5h+pLOk7ZptVngPLM+7NfOQmd2TzBJ1iiIjR1UXvi/jwT0X4sPgZqaZVuzHe1KAClKOUP378ItWnC9IZKOy89HO+f3Ko4Bk1vgCHnx4K+463NCd1+pdiHen3oU4W/9VfF7hDLk78a7ATyQtY30nPi/ER0OvyqP1f4dHvq+Dz8n0uNK22jHImOJ2w4MNL6JvZHOtXjbWYwX1jSvpeelJ2sPMfpu2N7WMa7IaeB42Qu780KfzY2Y/kvQG8GdJ8yaZ3sRNq6c1asvMLpV0J3Cm3MV93ib3V3R+7aU+i3JOFOn8OSl+T7fkVm1NPDsljWl0rE+9kTqyaEZB7/lM/KX1k1y9g4D1zWxCpiyv0XsOAR82s4UydbfF89msTu+E1Q8z8xp5ud7H7dTTKbBpm9laqV5L3k2SptHXBHRodj9jb26pByKfWN4ZfxnNwCcDLzazlwvurUjmhfHJtbz9OHteXcoRS+6GDe6t5xAetZ73CsmnrciaJw+3As+eBnL9yAq8kaqMApLMM4CfAHV5vCw3gT9YKOdSKemBzG/qR8D7ZvbNNOK5r3YsHZ9Q32Ifmc9K9T6P3/8H8Tmvibi3TuGLRhW9yFodTafyohf1wniuqj3MrFHg6Lz4u7FuDiMdv9rMtiko/wbwPevrBVj1/r6DpyI5IDeyOQl3Qz+2WTuZ6zV0q25yTh8vwIb1RqqyUPPAmTdy8wPNhoB9TBktfPlfxHve36S3FzoOjyv4lWUmzTNtt+xSWQVJR5W026rXUNE1xuAviUPxl+45JafUzlsOuNDMNsqUrUyvu+eLuBL6upnV/X8G497SSGpvYBMzqxTdXeUBU28g4a6WiWVJnZNm/v9fSPVaVmwt9GSR9KCZfTBt34NP1l6T9nsUSStIOgef1L62wIS7lOXykEkaDYzOm98krQG8YGbT036PeSdv6mlk+il4VmvxEFOKTGyq6AQyVMgzBn8TjxES8AY+v3pyyXn9cqvOnP90vlNVWG8EK4vKgTPN7IwDsEE+jI80XsqVL4LbtOt+fJJWNY/6Jj8kVcavX9LSeG6hW9P+ofQOf8+zxh5JVWXPz988DFyTf/gz9dfDf6hb4pOQJ+Qf/pLr5XuKtbiXfaw35UhLcS/9oVEPtUHdpg9Y+p43A54ys7tbkGFxM3u+yfGmiq1qZybV/Sney34OT4y5spn9R56U8QrLxGTkzUMF7ZamBilSsPLI4tMs53osT9Mxwcx2T/sDjrPIfCdPWi6DgzJOILhTwNH0OoF8L1u/wCTXo8Rrz2SmbiOHCj+xQCHLJ9VpNLLJ1Ol3ZuZcW5VGFiN5ziLvPdCMRn79AvIZZ2+kea+w5mOtvKJIFV5U41iK86jm1388ntCwxn64x9bcuDtv3sOpsklMjedvfqxchlpJx6Rjj+Dmhm81UiiNkMdp5CfPW0k50rK5r0Ebs5F7HtQ4vXQtZ1C27pV4ypOH0sv2HnxEuYKkX+ZNnLlz+6S5x3uHhSQT34mSCud18CSKdaatBhyCmxCXxDs2tQ7UEnhsQJYP4S6g5+OOF/1xvyw654N5RQFgZtdIytrhV5P0QGpjxbRda7OwE9HkO1lR0um57+Q7uMm51AkE7xDlWRjPGnxBrt1ahlrh7rOfKJI1ybsKntq95iTzCN6xLXJkaMmtWo3T0Qt3gChlxCoLaGlYmU1Klic/P1E17fFrkta2vi62SFobzwBaKHKD7fz+KmZ2ZWb/LTM7IbV/S12jHoW6HwUmMUlL50xi38d7ekXzN/+Le5PV+G888+Xa6fP9pAj7zLGk85vaj3PlV5hPHNbcL78GLC7pNOpTjrRybzToFCyEvzQvypU3Sy+dN2Msb2YPpe3PA9eZ2V6pB/gXfH4iK0dpmvtGFCm2DJel9pB0sZl9pkE9zM0KEwvK7y2ovgQ+chyfZL4Kd4WtSwTZhKKXVbM8XtljqzY4vxmtfCeVnUAslyGhhqSf4zFHP8nUzc4R/buRKVkejX0J3uk7Hf/NrQvcJOnTlskWkGjVrbpZOvpKqepHrLJQC7EF1kKEc9akkIb8/40HlX3ZPDtsjcOAy+UTu9kcOROofzn2NN9gO78/Z+7YFpntRQra/Rr1JrEbUo/8VvrGkbSSobYVP/38+iIGvIQrjD3om6X2TmA9c5/3c4Fz1Zty5Ah8jZAardwb1HcKaubJn5rZVX0OtBaHkA3M2gJPzIeZvZ7Maj2o4lonLSq2ntMy203NdgVzItk2zDKBo+ZRx1cDV0uaA1caN0k61vo6HLTag50i6RMFI9xt8Y5IjYcatAvwb0n/wKOqr8+UV/5OgMWSObfGvNl9yziBNMLM3m5iNSjju8D43G/gMkk34E4S2+au1UpmZvAO5pEMgBGrLGhhWClfjKYRZvX5YkrTHpvZrZI2wkPw94aeHDkbW+MU5Usne6gy26T9rGnidUkr134QtRdlMum8UdBuKyaxyhlqi3pJabLtxdRrzdbN2srzHk4X05c6oZL8v0ifPnVbMfc16xioINGeqqdgeFrSgXgywfXwF2ttBJHvPVdKc08Lii1Xp2i7vqJZw+C6IpKS2A5/OY3FPXXynlut9mC/BlwpaRd6zTvjcLNXzyJDzWRNFoQ18Y5FdmXEVr6TX9I32DC/3xT5PN+e6VrZ8qwpOZv6HCCb+XbFfGchHf+zpDpnmMzxqm7V2+CjkX4zkie485NgzTyeirwNetJsWG/6ZVSQ9jhL7cuX9E3ck6FyznhVd0/cBn9Qj6M3knV9/MdwcG6Eg6Q7gH0bmMR+aWYbZsoqZ6iVtDHu3fUSHkl9Dr5K2izAXmZ2daZuKx5Ojdxha/+HrKtv5XsrQk0S7ak4BcN6eA6sPikY5GtkH4ub1U6tmcrkgW7rm1mfkZV609zvipsvV8Xt9406EpWQZyR+M8k6F70Kvlmamdq5c+PzPk/UTLeZY2fhL+I/AhMz5p1mssybrtksFqamhHan90U/GVfIhVkWmrSzn5n9IrPf0nfSwnXyIzLh/+c/4+7a2Xm9phHrlhJzSrrbzNZvcL3BSJR4P54+pHDoU9ThqmtjBCuLyrEFufOyaTYexkcOD2SO30TzCe7al38q/lLZ35qvbdAv5AnKvklvuo/J+Mu87iGW9GG811VoErOMB4daiOGQpzg5Eg8EPB1fgez29CI83/q6N1b2cJL0HG6LbfTDPiZTt/K9Zc6pmmjvejwoqygFw7etxIlC7rn0Sn6UVVCvttbJzvRNc78G3uO8PO2fSG/Q5SlWsCZLK0jaAe90vISPxE/FU1mMxV1zz8rUfZ/eIMeiGKD5M3W/gjsc1NLSvIE7HPysgkz98iJr0Nb3WzG9aBAcJfqLerMF1B0ily0g1S9SWLX5tbpOgTxZ5zMUP1NW9BzWCTKClUUz/3uzXJCLKqTZ6IcM6+E5X/6Gv/x6RhlFD3oy4eyPmyjOwEcvHwH+ARxmJS6x8mjP7c2sLnpcHsm7P33TRp86kJ6spPvMbJ203Sclgep94T+F9+A3wc0BE/F4k7p5gVZ7UpKWwM19pfemvon2Jlpvor0iOSqnYJD0XTxe5G+pp3w1Puk/A486/1OF+5gFHxmemPavwH+Hf037D+Pmz7mBz5jZTmVtllzvflxBLYB7wK1lZo+lHvn1lmIwWmzzO/h3fEAykZDs6j8F7jCz/8nVb+ixhHsCNfQiqyBLK67QDR0lyMVFqXGalCdxJf5upu78wOKW8jZJ2pnelfeuseQmXdWqkGn3Mtzp4BL8d9zUAy7/PPYLG+I1ebvxgy9XmN3fH1/D+TRguQrnL4a7qF6Ep0g4BlisQd2P0hvfcWP63NCg7rW4N9LJeK/mG7h54kt4fpqic0bhk19n473CiwrqLNvC/2avJp89c3VbXrcY721+Dl9j/K30P98qV6fyOsbAlk2O/bCg7Pd41PQpeKwCNF7f+1FgjoLyOcmtJ40rqFrna9/0PY/CXWHvbOF+nspsT8ody67PfesgPAf3ZrYf7O93kDvv78CcBeVzAY8WlE/ObB8JnJ2256Pi2tBNZLkfdwhYuOiTq/twviyVLwI8kiu7A1gqba+Dx1gchi8Q9qtc3dPxdXJq+1PT8/0r4OcV7mFOYOcGxxbAvbyuwU1gXy26h4F8n33aGGgDw+WDDy2PxQNu8g/h+3gOpAfxRcxrn7rFzHHT0pO4gtgBz9FyDJ58bdNMvcVwG/5fgLWr/rjTX2VfGqnsvtz+ZviaEU/jE8T/BOZu0G72pX5xiQwnF3xOSfc8I1f3PeA13BV4Rtqu7f+nwv0ujPfmbsiXt/C9PgpslyubBV+L4uoG5yyA52a6Dp9gfxnYsKDed3ClNjZTNhafx/hurm72xXsxsF/R/7/C/Tyd2f57s/sehGei9jJdhPoX6/39bLOZzH8rKLsvs3097oRS+Jvvhyz/xj2qHi/4PJar+0iTdvLK4oHM9o9w82/td5d/X9xL6kQU/E4KFT4VOoAFv/fxuNI6tEGdvQf6exnJ3lCVbdO05gJ6Ap7BNeuL/ntJl+KeOrW0FbfjQ9i9LH1bFXgP3EYmXysiS48JK83HPIX3yr9h7gr4uJnl19PuOSWz3dQ2adXTpGNNMohWwRp4OFlr6w1vRXLnNLNLkqfL7/C1sAtjZ6xioj0z+x95Coab0+QvuN2+KAXDv9M80vN4Oumsk8DcVCf7W3lW0kZmdke2QnIseJaB03La7wpMk7SF9XVhRdLmeKBnnlY8llrlYatuemklLir7PG2Oz3NgZu+r3gNv1tzznw2m7ONKLGkzfKJ/O9x9fFNg+UbPtaRN8HfbR3A38U+ZWV2cVeK/UvtFmJnt0+BY742UVRiuqIVFYKy1nEvzW0HQkpndpxSmn9jIzKZLmlPSB/CH7x/W3MOjlnVT9M3AKfoqtItxG+muwHuSfk/zh9sabBdSMH/zWRvg/M1QYWZPpAnna5KtfU/cNn5oyam185/HJ3lPUkFuLvNspqeoPAXDIbhZcjS+1OjjAPJMpPksx83iG+bK7B8OXCDPJZX1epuAf/cDwiqsMd8PDsTji26lr8PBptRnSgVf7+FYfE3qXc3slVS+Me600C5aiYu6QdKFuPJbCI+TIc255IM135e0hKX5M0sOKPJcav3uAEp6Eh8RT8TNnjNS+XrpOvk50SupZ1n8dzvTr2fxezwC8nLcDe+vTbxvKidsk4fgb2K5zKryoLG/Wu96FrPSu8Thk/hQcWn8Afi2Fay/q9by+gjvwY7HUwjMjz94fzCzPrEWasGdUn3TpP+gRUXadtTrx74kPmy/Dl++Eqh/aNLLoNGPvq6Hpc4nl1sMOIC+Xm+nWpP8US20nZ/8NeBfZvb0ANo8BU8Jsgp9HQ7OLekoFbW13EB+f5L2toIliBs5glR1AknPXi1NyoVm9kwqXxefu7wmU3cP/Hk6jN5Ow3q4+eokSzFc8jxdO+Gm7/PwubUHi95Xqf5NNOkEWvLKbHDuCvj80GbAicCvrcLaJSNWWQCo4iIwDc4tTNgmaV98wvnr9O3t/RA4w5Kft9zNcT78pfJ6Kpsf/5G8bWYHV7yH9Qp6Cfk6s+FBN+PxyeJFq7TdoK1KadK7BfXm6sqO/3vkzj808hX08vT0sCyTiE2tJZdrOpKxChHAVVE/0lA3aOfGguKF8ZXhxpvZff1o82Dc621JPJbm/LJ25KkuxuCpzF+QtBYeqf8Rq5ANtaJco3CT5Xhga+AWM/ts5viyVj2nVqvXrgXE1QI7J+MdsXw8VCsdwA3x+a3n0v4E/F33BHB0kSlXvgTxt/FO9PHAb62FXG4jWllkydimdwPyi8A0O69o5blPUh/jcLyZXZGpMwXP4mm5c0fhE30rDeD6O+GjmBcK6s9lZs2isMuuV2eKydJtI43+PDSZc5v2sNTaCoNHNZPTBpgGXgNMQ93itcYBPzazRjbuKm0shz9ru+EePefjLp6P5uodj0dq34d36K7EvXq+D/yi1dFIgRxF8wAr5M076pvVtmlOrRIzYp+Reolsdcu4Zo417QDKU8p/3MxeSvc4ETcBrgOsllWEqf7vcFfgH+GLXr2XPV5pntAGOEM+HD9UcI9N9Wajn+57NPFWaXasoG6dyxtuG38G7+2eidss1+j0/7VD3+U9JO8p/KX/LK4svkcDLxLcnfW3uJLfG5+ELGw7t1/nzTPE9zYf7rJ8Ne7VcwIetNeW/+sgtrUuboJ5r+DYwyRXW9z+/zaw0iBddxqe2G9PYL5U9niDuvcWbQ+SHGPSi3r2tL8YrgyfbXLObOn/thgwV8Hx+zPbp+Ido9p+nRcZ3nnq8QSjr5dYoet4/jOSJ7ib5t/H3V5rdSsnbFPjRGkAWO/ykg9L2svMzs6dvwcepFeVuh6ppV6DpLF4ANQmwH6SlgXuMrOGaZDLGKxeUxsZZb29ol3xQK6LgYsl1Zk/cj2sr+E9rPlrXizWt4dVObmcPCivEWZm32vttoAW01APFmkUPiCTQ6ZnvBuexO/PFPyWcZPsOwBm9rJ8sbEpA7l2hlYcQVpyAqmKpENw089UYI40N/FjfH5t/Uy9nwMnm9nkZD6/Df9tLoybvM/PNT1K0qzmZqQt8A5jjbr3ug2CM8OIVRa0ln+/lYRt2WRox+AZIYs4ELhI0hfo610xF75oSR0qjgz9WDKX9IkMhR5PoDlTm3Phw/25GADWYnK5LqClhwb/Dgx/AA9LZbXfhtHXtbiV5HJF5oR5cJvzIvhIp1VaTUPdEg06PgvjnY9Kc2oFbdbSmNfMPhPx3F2N8kOtqL5ef2OzHT2rsKhSI8zs4PSyrs0DHI93DHahfh5gbUmvJRnmSts1mQbSSdoXz/j6UurMTQU2s/qU4x8xsy+n7c/j1oed5NkJ/ki9sjgfXy/8X/ho7BYAueflq3khNAhrmI/YOYs0N1D74a5Fk/z7yqxC1+I1mq2wd4+ZrSdpCzwgUHi06vVF9dM5d+C+0s/KM7P+CV9DYi08yO2Lqd6RuDIcjUfM3p4+D5inku43arzgD9ByDMSQI+nb+GTgv/CJ6vVSD/wDwFlmtukA2h5nZpVy/efOmw9/2e6D24dPsIL5pRbaW5Fe+3/hut79bHdCrqjWSbqrv/KmSfPz8ODP8uR0LXgADpQ02tkW/z8OyBGkhWvmE5o+ZGZrFtTLLht7FfA7S55cjd4z8nibJfElbN9MZSsD81q9F+CAVxoccttnN3zw9Sb2xj18Diw4fi8eDb1Ai+02tOvSD7snFSNDcTPWJNw7Z6tW5S6RoWbTfBxPwd6ybbMD3+/G+GhtnkzZyrjiyNfdI7O9ae7YAQW/iyl4HMDqFeRYGPif9L86Gne5Hex7/SBu7/7HELTdYyfvwHc4J551dg0K0oUMQvu1tb5r+3XzAEN0Xy+Q4njSp89+pt6N+ET/usArwBKpfFYGYa6MJnMyVd9VI9kMharl3we3HR4E3CXpe5Zbv6KfjG7mTmnFrpSVIkPNbNU0AtgEzz11hDwd9P24l1S/g5ksk1Cv2cipm7CCUaE17nUfik9ug6cyyfaovoCnNqm1sa58qcvdcJPiu/R69fTxCktePZ/GcwF90HKujv2hZP7o35Jup37Bn1bab2gnl/R1M8ubPgYdNYhHksfDFMYjtdC28FHYAaldSZqB3/OxTU8ePL6R22+USXc//P20BJ7mvBbbsQVuFRkozeZkKpmXRrIZqj/591fHH5hZaJDuN/cAz02DADe1kGY70/ZP8WHlc/gE/Mpm9h95ZOgVlllrIXPOrLiy2wz/wS1vA0zDkWl7wHn0u43ccD+fGbepcpSnftgNX7Tpn5YxccnjU/6NR9IWxacMqmOAMgv+WIFZo2Ibk81sjbR9CPBRy9jJ29FR0CDFIzVo+2u4iXJf642oXwF/Lq+2lN23Xaji+h5DdO238PkS4Rl9axmshbsSz9Po3B7aMRTrxAcPpX89fV6jb5K71wrq74ObHA6A3sRfA7h+y66H6YvbDffSGZMpXxcPJqzt74DnnboFX4vgFjxqeUcyQ+1O3EO3f+hHptx0bBZ8DuwMPGnjZZ2+lyTXfgM4N2uauIq+2VEH1X20iQxTip43PAXFlAG2fS+waEH56HbdX7reV/BUHi+mz5PAV3N1vkRyGU7vgd+k99UDwLqDIMNyzT5V2hixZigzm6VqXXkeqSdwj4QBrVSWbbYf56xiZhOTTHPUCs3s3jSZVWNv3H/8m8DdViFUvyo501nedRQbxEjkDrGqpAdIPay0TdovSgXzEdyMuRO+DvREvBdc53HSCSyzMlw/eEUeYPoMHqy2D/SMVgfkVdcCZultlitstNRsK8xmuRX/UtvT02T3kKPe9T0+arn1PSQtbL3rexyMx0xBr1PO8nhH8SQ8WWC/sRaWQG7EiFUWLXKU5VZDGwS26Mc559FrQ7+Nvvb0n9X2zaxPXIgGcXUxmruKjgSbZeV8TpKexnuEE4FjbBDyMXUZQ20nr8JgxSMV0awTNWgdrBL2xJco6IlEN19gahd8jrGmLGZY7/zMJ/F1PV4E/iTp/xggarIEcvr/X93sfAhlUWMHSYXprKFPoF1lrH8upmqw3WdfTVYXkzSg1cWsSVoKSRv0t91uoaiHBT1zALvhJoIaH25SvxbbMZzZysy2yReaJ8K7pqD+ULA/cEkr8UgtUIudyCPc+6otWEHKEjN7O81z1Xg/Pcsv48o6uxzAYIzyTqF3CeQbyC2BTEoN34zKppoRziT8h3o3Ph9wd+7TLqp6LCxvvRP2nweuM7Pt8bU0vjCYAklaXdKx8lxXpw1m251A0vySviXpFElbyTkQdxHeJVf93Mx5eQ+50mSUw4BB/a30BzN7xsw2wt2Tn8BHcsea2YaWsrkOoO1RZjZ/wWc+M2uLGYq0vke+UPXre3wXfw89AVxuKR4sxaE8NghyzGpm15pn2v2nJQ9CM6s8eouRBX3Xt5V0iOXWu20jS0s6Ce/51LZJ+2My9bLuhFvg5iLMc+Bneyv9QtUXjRqOnIP33m4Dvoi7Ns4O7Gj12VGzHiJr5I71Z04qyCHPQPBlPIngg3gyx+E+YstyEL44WtP1PczsyvTczWd9lz+4Cx/xDpTseyGfaDTmLPpJJ+3yWZ/sfORwdn/IVhdTC4tGDVNWMLMPAkj6FSny24oXNWr2WxgJ8zdrNTHTmLUnD9hZeOfnFjy6ejU8XfyIwDyGZU08821tnYybcS+2d3J1Z+AdmVqMyMfSedsDiw9QlGbpTCqZ5EJZdBEtjGiGcnWx6fgiTYvjLoZTwQq4rwAACKFJREFUGBkvxho9o7LkcfN4A0UBsKA8cd8sabvmWCBcoQ53HrTOB12unlHev2ZkmPf6kJTCGbX95IX076K6kjbCFcSn8IwA+1Mf2NcfGQYcezVig/JaoWqgXZtkmYC70a2Sih7B0wKcnalTt1Zw5thXzGxAcwsawKJR3Y56Vw0E+qwcWBSA2VTxmtnnh0rOdtANEfr5wM+RFgjazAsJ6PFCknQcPmf2FD7hfCkwyTIZFTpNKIsuQtJeeEDeobiHk3Az0/F4BtyzU73HgJ3zbrKSjsGXixy0h039XDQq6H4kHWlm3++wDJWV93BE0iR6vZBOJ+eFZL3ZBKbjSUF/AlxpZu+owTLQnSKURRchz/WzW35+QL5uxUQz2zjtrw/8Dvicmd2W7Jun4cnzdjKzIjv0YMi3XCNX0pFIPiAxz3APUFT1tVmCfiLpPjNbJ20/Ypl123OpZ7LLvm6OJxb8ON5B64oJ/5iz6C7mL5pINl+3Yv7M/t3ypVUvlbQ/nioAYBsbYDS3Wlg0aiYgG5C4H74e90ii5fTrQctU8kIyX1rgj8Afk4fYJ3GT+DOSrjez3Ydc0hJiZNFFSLrbzNYvO6beNSdWBy7D1704gPTD7GdAYO0602myaJQN4voCw4lusO8Hw4+MmS1rYiPtz1kW7yFfG+XTHXTn75UllEX3kMkMWXeITGZISY/T2yvJrvJWs/P2286pFhaNmpkYaROvUD6KtAGsUhe0TgrAe9nMHkjpQDYD/gH8zMwKvafaSSiLLiIF5TSkynyBpDEDjXzNtDUHvctRHmtmJw9Gu8OREaosYhQ5xKjiypOSTsU7Z3MAjwLz4vFTm+DrzH9uiEUtJZRFFyFp1Vr4vaQ5sr0JVVz6VdJTZrbsAOXILxp1OXDGYCmh4YKkB+kdwX2A3KjPzNZqu1CDSIwih56UUWEangkB+irkHiuApIfNbPU0X/EMvlrhe8l55YFaLEoniQnu7qJS1tkSBpSGQn0XjTrGKiwaNYL5NB6c+HSufDng2faLM7ikSdWrgaszo8ibJM3Uo8hB5mR8Ncu/4CO4W624h/4OeACfpCfTd4OZmaR+rxY4mISy6C4qZZ0tYaBDxT3xCbmVgYPUu5zriPB7b5ETgSPz5j9Jo9OxhpmKhwsFo8hGSw8H/cDMDk6jg4/iz9bJkq4FTrO0el+itnaM6LuOjPBMCh0nlEV3USnrbBP/eOHR1v0XoIVFo2YCxprZA/lCM5uUYl+GNTGKbA9pJHGjpHvx4Nbv4Wl0fpmpll07Jr+OzK/aIWcZMWfRRUh6AU/gJzxqemLtELCLmS2e6k1o1k43uNmNBCRNNbMPtHpsuJDs6bXo6SFfN3xmRNI8eHbZXfERwiXABWaWN212PaEsuoj+KAF1cBH4kY6k84EbzOyXufJ98IWDdu2MZMFwQdKb+CjifNxBos8L18wuSfVOqj+7T72OR9OHsugikifEfGY2PVe+GPCaZVIaS/oK8C1611x4A/ihmf2sXfKOdFJerEvxJThrebjG4etffMoGb732YIQi6UwazyOamX0h1XsXX+P9Qtx5Iu/G3HFrQSiLLkLS6cDVtd5Gpvxz+BKfX0n7tUXgD7DcIvDAHda7CHwwCEj6GG7bB5hsZjd0Up5gZCBpcUvruktaBNgZN1fNAC4ALra+CyF1lFAWXUTN17rBsclmtkba/ju5ReBT+VzA/Wa28tBLGwRBq2TS/+8OrGZmYwrqjMG90w4FDjez/JK+HSG8obqLZu6xfbyU8ooileUXgQ+CoMOkTtwOuIJYD/d02glfMS9fdz1cUWyJe6ndna/TKcJNsrt4QdKG+UJJG+Ar2NWough8EAQdRNK5ePqOrYBT8FiWl83sJjN7P1PvGEl346OJP+Nr3u9jZg93QOxCwgzVRSRFcSFwJn0nVPfC17m4I9VbHU/BUbgIfKRrCILuQNL9uMXgbJLLbNGiRski8Bi9acyziULfN7O12yVzI0JZdBnJA+erZCZUgVPM7IVMnVNwV7xV6F0EfjJwbpF5KgiCzpFWxdsdn7x+AVgV+GDWm65BElEBS+NZBD7RDlmbEcpimCBpUzP7S9o+GI8EXRL3mjjfzO7rpHxBEJQjaRw+J7EzMM3MNimosw6uXHYBHse9ok5pq6AFhLLoIlIW0F2AMcAfzWyypE/ia/jOlV98J/VGdkufOfHRxkQze7S9kgdB0AqSZgEONrMT0/7K+HM8HngR7wR+3cyaLlvQTkJZdBEpgGcZ4E5gI+BJ4EPAEWZ2Wcm56wJnAGuZ2aghFjUIggGSXU4gzVncAuxjZlNTWd3cRicJ19nuYhz+sn8/RXP/C/hAo0hhSbMB2+A9ki1wL4pj2iVsEAQDIusq/xn8Ob5R0tX05ojrGkJZdBfv1tzpUl77R4sUhaTagjXb4aOQicC+kR8qCIYVPWYdM7sUuDQlHtwJ+BqwuKTTgEvN7NoOydhDmKG6iNwa3AJWTPu1LKBrpXo34gslXVxbljEIgu5D0us0Xk5gLjNr2GFPS7LuDOxqZpsPkYiVCWXRRQzGGtxBEARDQZihuou5mq3BjU94B0EQtJ1I99FdnJfZvi13LFKPB0HQMUJZdBeDsQZ3EATBoBPKoruotAZ3EARBu4k5i+5i6bS8ojLbpP26vPdBEATtIryhuoj+rMEdBEHQDkJZBEEQBKWEGaqLkHR5s+NmtkO7ZAmCIMgSyqK7+BDwNJ499g7CAyoIgi4hzFBdREpRXsv7tBZwFb5WRax8FwRBRwnX2S7CzN4zs6vNbAKwMZ4X6iZJB3ZYtCAIZnLCDNVlSJoDzyY7Hl/c/STgkk7KFARBEGaoLkLSWfja23/EV7x7qMMiBUEQAKEsuoq0WlZtTYrsF1NLUT5/+6UKgiAIZREEQRBUICa4gyAIglJCWQRBEASlhLIIgiAISgllEQRBEJQSyiIIgiAo5f8BkcgJ7nYb7lcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=count.index, y=count, palette=\"rocket\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(\"Bar Chart Merek Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "count2 = data['Fuel_Type'].value_counts()\n",
    "plt.pie(count2)\n",
    "plt.legend(labels=['%s, %1.f' % (l,s) for l, s in zip(count2.index, count2)])\n",
    "plt.tight_layout()\n",
    "plt.title(\"Pie Chart Jenis Bahan Bakar Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "count3 = data['Transmission'].value_counts()\n",
    "plt.pie(count3)\n",
    "plt.legend(labels=['%s, %1.f' % (l,s) for l, s in zip(count3.index, count3)])\n",
    "plt.tight_layout()\n",
    "plt.title(\"Pie Chart Transmisi Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "count3 = data['Location'].value_counts()\n",
    "sns.barplot(x=count3.index, y=count3, palette=\"twilight\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(\"Bar Chart Lokasi Mobil Terjual\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=data['Year'].value_counts().index, y=data['Year'].value_counts(), palette=\"twilight\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(\"Bar Chart Tahun Mobil Terjual\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data['Kilometers_Driven'], bins=20, color=\"teal\")\n",
    "plt.title(\"Histogram Jarak Tempuh Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IiP4MGPq2nwAO6aX9OXq5+sb2m8DJfazrYuDiwZcZERFDIZ/IjYioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKjJg6EuaIOkeSU9LWiTpnNK+h6QFkhaX291LuyR9XdISSU9IOrRlXbNK/8WSZm253YqIiN60c6S/Dvii7QOAKcDZkg4Ezgfusj0JuKvMAxwLTCp/s4FvQvMiAVwEHA4cBlzU/UIRERHDY8DQt73C9o/K9M+Ap4FxwAxgbuk2FzixTM8ArnHjAWC0pH2AY4AFtlfZXg0sAKYP6d5ERES/BjWmL2kicAjwILC37RXQvDAAe5Vu44ClLXdbVtr6au+5jdmSFkpa2NXVNZjyIiJiAG2HvqRdge8C59p+vb+uvbS5n/YNG+yrbE+2PXns2LHtlhcREW1oK/Ql7UAT+NfZ/l5pfqUM21BuV5b2ZcCElruPB5b30x4REcOknat3BFwNPG378pZFtwLdV+DMAm5paT+jXMUzBXitDP/cAUyTtHs5gTuttEVExDAZ1UafI4DTgSclPVbaLgQuAeZLOgt4CTi5LLsdOA5YArwBnAlge5WkrwIPl35fsb1qSPYiIiLaMmDo276P3sfjAab20t/A2X2saw4wZzAFRkTE0MknciMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIok9CMiKpLQj4ioSEI/IqIiCf2IiIoMGPqS5khaKemplrY9JC2QtLjc7l7aJenrkpZIekLSoS33mVX6L5Y0a8vsTkRE9KedI/2/A6b3aDsfuMv2JOCuMg9wLDCp/M0GvgnNiwRwEXA4cBhwUfcLRUREDJ8BQ9/2D4BVPZpnAHPL9FzgxJb2a9x4ABgtaR/gGGCB7VW2VwML2PiFJCIitrBNHdPf2/YKgHK7V2kfByxt6bestPXVvhFJsyUtlLSwq6trE8uLiIjeDPWJXPXS5n7aN260r7I92fbksWPHDmlxERG129TQf6UM21BuV5b2ZcCEln7jgeX9tEdExDDa1NC/Fei+AmcWcEtL+xnlKp4pwGtl+OcOYJqk3csJ3GmlLSIihtGogTpIuh74ODBG0jKaq3AuAeZLOgt4CTi5dL8dOA5YArwBnAlge5WkrwIPl35fsd3z5HBERGxhA4a+7VP6WDS1l74Gzu5jPXOAOYOqLiIihlQ+kRsRUZGEfkRERRL6EREVSehHRFQkoR8RUZGEfkRERRL6EREVGfA6/YgYWS5Tb19lNTzOc69fmRVbkRzpR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUZFSnC4iIrcdlUke2e57dke1ui3KkHxFRkRzpb0M6dRQWEVuPYT/SlzRd0rOSlkg6f7i3HxFRs2ENfUnbA/8TOBY4EDhF0oHDWUNERM2Ge3jnMGCJ7ecAJM0DZgA/3hIby0mn2JIynBZbo+EO/XHA0pb5ZcDhrR0kzQZml9m1kp7djO2NAX66GfffJH86cBh0pK42bHV1tfFYb0lb3ePVYZtc1xZ+nre5xwt4f18Lhjv0e3vmNjgstn0VcNWQbExaaHvyUKxrKKWuwUldg5O6Bqe2uob7RO4yYELL/Hhg+TDXEBFRreEO/YeBSZL2k7QjMBO4dZhriIio1rAO79heJ+mPgTuA7YE5thdtwU0OyTDRFpC6Bid1DU7qGpyq6pJzpUlERDXyNQwRERVJ6EdEVGSbC31JEyTdI+lpSYskndPpmgAk7STpIUmPl7q+3OmaWknaXtKjkm7rdC3dJL0g6UlJj0la2Ol6ukkaLelGSc+Uf2cfGwE1fbg8Tt1/r0s6t9N1AUj6Qvk3/5Sk6yXt1OmaACSdU2pa1OnHStIcSSslPdXStoekBZIWl9vdh2Jb21zoA+uAL9o+AJgCnD1CvurhLeBo2wcBBwPTJU3pcE2tzgGe7nQRvTjK9sEj7DrqK4Hv294fOIgR8LjZfrY8TgcDvw28AdzU4bKQNA74E2Cy7Y/SXMAxs7NVgaSPAv+e5lsCDgKOlzSpgyX9HTC9R9v5wF22JwF3lfnNts2Fvu0Vtn9Upn9G8x9yXGerAjfWltkdyt+IOIsuaTzw+8C3Ol3LSCfpPcCRwNUAtn9pe01nq9rIVOAntl/sdCHFKODdkkYBOzMyPptzAPCA7TdsrwP+CfhUp4qx/QNgVY/mGcDcMj0XOHEotrXNhX4rSROBQ4AHO1tJowyhPAasBBbYHhF1AX8NfAl4u9OF9GDgTkmPlK/nGAk+AHQB/6cMh31L0i6dLqqHmcD1nS4CwPa/AJcBLwErgNds39nZqgB4CjhS0p6SdgaOY8MPjo4Ee9teAc3BLLDXUKx0mw19SbsC3wXOtf16p+sBsL2+vP0eDxxW3mJ2lKTjgZW2H+l0Lb04wvahNN/KerakIztdEM1R66HAN20fAvycIXrbPRTKhx5PAL7T6VoAyjj0DGA/4H3ALpJO62xVYPtp4FJgAfB94HGaoeFt3jYZ+pJ2oAn862x/r9P19FSGA+5l4zG8TjgCOEHSC8A84GhJ13a2pIbt5eV2Jc349GGdrQhovkpkWcu7tBtpXgRGimOBH9l+pdOFFJ8AnrfdZftXwPeA3+1wTQDYvtr2obaPpBlaWdzpmnp4RdI+AOV25VCsdJsLfUmiGW992vblna6nm6SxkkaX6XfT/Gd4prNVge0LbI+3PZFmWOBu2x0/EpO0i6TduqeBaTRvyTvK9svAUkkfLk1T2UJfDb6JTmGEDO0ULwFTJO1c/m9OZQSc+AaQtFe53Rf4N4ysxw2ar6iZVaZnAbcMxUq3xZ9LPAI4HXiyjJ8DXGj79g7WBLAPMLf8kMx2wHzbI+byyBFob+CmJicYBfy97e93tqRf+zxwXRlKeQ44s8P1AFDGpn8P+A+drqWb7Qcl3Qj8iGb45FFGztcefFfSnsCvgLNtr+5UIZKuBz4OjJG0DLgIuASYL+ksmhfPk4dkW/kahoiIemxzwzsREdG3hH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFfn/MbI+vXX46RgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data['Seats'], color=\"darkred\")\n",
    "plt.title(\"Histogram Tempat Duduk Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='Transmission', y='Price', data=data)\n",
    "plt.title(\"Boxplot Harga untuk Masing-Masing Transmisi Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='Location', x='Price', data=data, order=data.groupby('Location').median()['Price'].sort_values(ascending=False).index)\n",
    "plt.title(\"Boxplot Harga untuk Masing-Masing Lokasi Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y='Price', x='Owner_Type', data=data)\n",
    "plt.title(\"Boxplot Harga untuk Masing-Masing Tipe Kepemilikan\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x='Year', y='Price', data=data, color=\"cadetblue\")\n",
    "plt.title(\"Scatterplot Tahun Terhadap Harga Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x='Power', y='Price', data=data, color=\"cadetblue\")\n",
    "plt.xlabel(\"Power\")\n",
    "plt.ylabel(\"Price\")\n",
    "plt.title(\"Scatterplot Tenaga Terhadap Harga Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Kilometers_Driven</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>Engine</th>\n",
       "      <th>Power</th>\n",
       "      <th>Seats</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Year</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.436792</td>\n",
       "      <td>0.321511</td>\n",
       "      <td>0.321511</td>\n",
       "      <td>0.025751</td>\n",
       "      <td>0.014829</td>\n",
       "      <td>0.305327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Kilometers_Driven</td>\n",
       "      <td>-0.436792</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.142167</td>\n",
       "      <td>-0.142167</td>\n",
       "      <td>0.007004</td>\n",
       "      <td>0.206710</td>\n",
       "      <td>-0.152001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Mileage</td>\n",
       "      <td>0.321511</td>\n",
       "      <td>-0.142167</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.494072</td>\n",
       "      <td>-0.302310</td>\n",
       "      <td>-0.306634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Engine</td>\n",
       "      <td>0.321511</td>\n",
       "      <td>-0.142167</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.494072</td>\n",
       "      <td>-0.302310</td>\n",
       "      <td>-0.306634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Power</td>\n",
       "      <td>0.025751</td>\n",
       "      <td>0.007004</td>\n",
       "      <td>-0.494072</td>\n",
       "      <td>-0.494072</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.098438</td>\n",
       "      <td>0.772910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Seats</td>\n",
       "      <td>0.014829</td>\n",
       "      <td>0.206710</td>\n",
       "      <td>-0.302310</td>\n",
       "      <td>-0.302310</td>\n",
       "      <td>0.098438</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.053787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Price</td>\n",
       "      <td>0.305327</td>\n",
       "      <td>-0.152001</td>\n",
       "      <td>-0.306634</td>\n",
       "      <td>-0.306634</td>\n",
       "      <td>0.772910</td>\n",
       "      <td>0.053787</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Year  Kilometers_Driven   Mileage    Engine     Power  \\\n",
       "Year               1.000000          -0.436792  0.321511  0.321511  0.025751   \n",
       "Kilometers_Driven -0.436792           1.000000 -0.142167 -0.142167  0.007004   \n",
       "Mileage            0.321511          -0.142167  1.000000  1.000000 -0.494072   \n",
       "Engine             0.321511          -0.142167  1.000000  1.000000 -0.494072   \n",
       "Power              0.025751           0.007004 -0.494072 -0.494072  1.000000   \n",
       "Seats              0.014829           0.206710 -0.302310 -0.302310  0.098438   \n",
       "Price              0.305327          -0.152001 -0.306634 -0.306634  0.772910   \n",
       "\n",
       "                      Seats     Price  \n",
       "Year               0.014829  0.305327  \n",
       "Kilometers_Driven  0.206710 -0.152001  \n",
       "Mileage           -0.302310 -0.306634  \n",
       "Engine            -0.302310 -0.306634  \n",
       "Power              0.098438  0.772910  \n",
       "Seats              1.000000  0.053787  \n",
       "Price              0.053787  1.000000  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr = data.corr()\n",
    "corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x='Mileage', y='Price', data=data, color=\"cadetblue\")\n",
    "plt.xlabel(\"Mileage\")\n",
    "plt.ylabel(\"Price\")\n",
    "plt.title(\"Scatterplot Mileage Terhadap Harga Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x='Engine', y='Price', data=data, color=\"cadetblue\")\n",
    "plt.xlabel(\"Engine\")\n",
    "plt.ylabel(\"Price\")\n",
    "plt.title(\"Scatterplot Mesin Terhadap Harga Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x='Seats', y='Price', data=data, color=\"cadetblue\")\n",
    "plt.xlabel(\"Seats\")\n",
    "plt.ylabel(\"Price\")\n",
    "plt.title(\"Scatterplot Tempat Duduk Terhadap Harga Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x='Kilometers_Driven', y='Price', data=data, color=\"cadetblue\")\n",
    "plt.xlabel(\"Kilometer_Driven\")\n",
    "plt.ylabel(\"Price\")\n",
    "plt.title(\"Scatterplot Kilometer Driven Terhadap Harga Mobil\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,ax = plt.subplots(figsize=(10,10))\n",
    "sns.heatmap(corr, annot=True, linewidths=.05, fmt= '.1f', ax=ax)\n",
    "bottom, top = ax.get_ylim()\n",
    "ax.set_ylim(bottom + 0.5, top - 0.5)\n",
    "plt.title(\"Korelasi AntarKolom pada Data Harga Mobil Bekas\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}

nama file : NRP1_NRP2_Judul.ipynb
kalau (dot)ipynb tidak ditulis, nnt tidak bisa terbaca syntax nya.
Terima kasih dan semangat :)