From 51f3473fb6f05d1eb4456876962664778215de81 Mon Sep 17 00:00:00 2001 From: Temitayo Aderounmu <91757922+temitayoaderounmu@users.noreply.github.com> Date: Sat, 25 Nov 2023 21:56:49 -0600 Subject: [PATCH] Add files via upload --- dataAnalysis.ipynb | 2875 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 2875 insertions(+) create mode 100644 dataAnalysis.ipynb diff --git a/dataAnalysis.ipynb b/dataAnalysis.ipynb new file mode 100644 index 0000000..9f5a195 --- /dev/null +++ b/dataAnalysis.ipynb @@ -0,0 +1,2875 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": "IPython.OutputArea.prototype._should_scroll = function(lines) {\n return false;\n}\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%%javascript\n", + "IPython.OutputArea.prototype._should_scroll = function(lines) {\n", + " return false;\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": {}, + "outputs": [], + "source": [ + "# import necessary libraries\n", + "import pandas as pd\n", + "import numpy as np\n", + "import math\n", + "import seaborn as sns\n", + "import datetime\n", + "import matplotlib.pylab as plt\n", + "import plotly.graph_objects as go\n", + "from pathlib import Path\n", + "from matplotlib import pyplot\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.ensemble import RandomForestRegressor\n", + "from matplotlib.ticker import NullFormatter\n", + "import matplotlib.ticker as ticker\n", + "from sklearn.gaussian_process import GaussianProcessRegressor\n", + "from sklearn.gaussian_process.kernels import WhiteKernel, DotProduct, RBF\n", + "from sklearn.metrics import mean_squared_error\n", + "from sklearn.neighbors import KNeighborsRegressor\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['auth', 'scrape', 'admin', 'local']\n" + ] + } + ], + "source": [ + "from pymongo import MongoClient\n", + "import pymongo\n", + "# MongoDB Atlas connection string\n", + "# Replace '' with your actual connection string\n", + "connection_string = ''\n", + "try:\n", + " # Connect to MongoDB Atlas\n", + " client = MongoClient(connection_string)\n", + "# return a friendly error if a URI error is thrown \n", + "except pymongo.errors.ConfigurationError:\n", + " print(\"An Invalid URI host error was received. Is your Atlas host name correct in your connection string (found the .env)?\")\n", + "\n", + "#print(client.list_database_names())\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 125, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['scraped_raw', 'scrape_raw', 'scraped_processed']\n" + ] + } + ], + "source": [ + "database_name = 'scrape'\n", + "db = client[database_name]\n", + "#print(db.list_collection_names())\n" + ] + }, + { + "cell_type": "code", + "execution_count": 126, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data has been successfully exported to output_data.csv\n" + ] + } + ], + "source": [ + "collection_name = 'scraped_raw'\n", + "collection = db[collection_name]\n", + "\n", + "# Fetch data from MongoDB and convert it to a DataFrame\n", + "cursor = collection.find()\n", + "data = list(cursor)\n", + "cars = pd.DataFrame(data)\n", + "\n", + "# Convert DataFrame to CSV\n", + "csv_filename = 'output_data.csv'\n", + "cars.to_csv(csv_filename, index=False)\n", + "\n", + "# Close the MongoDB connection\n", + "client.close()\n", + "\n", + "print(f'Data has been successfully exported to {csv_filename}')\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Specify the database and collection\n", + "# Replace '' and '' with your actual database and collection names\n", + "database_name = 'scrape'\n", + "collection_name = 'scraped_processsed'\n", + "db = client[database_name]\n", + "collection = db[collection_name]\n", + "\n", + "# Fetch data from MongoDB and convert it to a DataFrame\n", + "cursor = collection.find()\n", + "data = list(cursor)\n", + "cars = pd.DataFrame(data)\n", + "\n", + "# Convert DataFrame to CSV\n", + "csv_filename = 'output_data.csv'\n", + "cars.to_csv(csv_filename, index=False)\n", + "\n", + "# Close the MongoDB connection\n", + "client.close()\n", + "\n", + "print(f'Data has been successfully exported to {csv_filename}')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [], + "source": [ + "cars = pd.read_csv('output_data.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "#cars = pd.read_csv('data.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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2https://abilene.craigslist.org/ctd/d/georgetow...craigslist12023-11-132014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF...$29,999WWW.GETADIESEL.COM227k mihttps://abilene.craigslist.org/ctd/d/georgetow...['https://images.craigslist.org/00z0z_fBJpyxit...
3https://abilene.craigslist.org/ctd/d/georgetow...craigslist12023-11-131-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR...$42,900WWW.GETADIESEL.COM143k mihttps://abilene.craigslist.org/ctd/d/georgetow...['https://images.craigslist.org/00J0J_cBZBKQMO...
4https://abilene.craigslist.org/ctd/d/georgetow...craigslist12023-11-132017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ...$42,897WWW.GETADIESEL.COM180k mihttps://abilene.craigslist.org/ctd/d/georgetow...['https://images.craigslist.org/00v0v_3LJpHDnn...
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" + ], + "text/plain": [ + " _id source \\\n", + "0 https://abilene.craigslist.org/cto/d/clyde-201... craigslist \n", + "1 https://abilene.craigslist.org/cto/d/abilene-2... craigslist \n", + "2 https://abilene.craigslist.org/ctd/d/georgetow... craigslist \n", + "3 https://abilene.craigslist.org/ctd/d/georgetow... craigslist \n", + "4 https://abilene.craigslist.org/ctd/d/georgetow... craigslist \n", + "\n", + " scraper-version scrape-date \\\n", + "0 1 2023-11-13 \n", + "1 1 2023-11-13 \n", + "2 1 2023-11-13 \n", + "3 1 2023-11-13 \n", + "4 1 2023-11-13 \n", + "\n", + " title price \\\n", + "0 2015 GMC Terrian SLT Leather Seats SUV $8,495 \n", + "1 2012 Ford Edge SUV $5,900 \n", + "2 2014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF... $29,999 \n", + "3 1-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR... $42,900 \n", + "4 2017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ... $42,897 \n", + "\n", + " location odometer \\\n", + "0 Clyde 165k mi \n", + "1 Abilene 127k mi \n", + "2 WWW.GETADIESEL.COM 227k mi \n", + "3 WWW.GETADIESEL.COM 143k mi \n", + "4 WWW.GETADIESEL.COM 180k mi \n", + "\n", + " link \\\n", + "0 https://abilene.craigslist.org/cto/d/clyde-201... \n", + "1 https://abilene.craigslist.org/cto/d/abilene-2... \n", + "2 https://abilene.craigslist.org/ctd/d/georgetow... \n", + "3 https://abilene.craigslist.org/ctd/d/georgetow... \n", + "4 https://abilene.craigslist.org/ctd/d/georgetow... \n", + "\n", + " images \n", + "0 ['https://images.craigslist.org/00q0q_fqrDYmbI... \n", + "1 ['https://images.craigslist.org/00u0u_djFxYThj... \n", + "2 ['https://images.craigslist.org/00z0z_fBJpyxit... \n", + "3 ['https://images.craigslist.org/00J0J_cBZBKQMO... \n", + "4 ['https://images.craigslist.org/00v0v_3LJpHDnn... " + ] + }, + "execution_count": 128, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 129, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "176" + ] + }, + "execution_count": 129, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data Cleaning" + ] + }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [], + "source": [ + "# drop unnecessary variables: id, url, region_url, VIN, image_url, description, lat, and long\n", + "cars = cars.drop(columns = ['_id', 'link'])" + ] + }, + { + "cell_type": "code", + "execution_count": 131, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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1craigslist12023-11-132012 Ford Edge SUV$5,900Abilene127k mi['https://images.craigslist.org/00u0u_djFxYThj...
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3craigslist12023-11-131-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR...$42,900WWW.GETADIESEL.COM143k mi['https://images.craigslist.org/00J0J_cBZBKQMO...
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" + ], + "text/plain": [ + " source scraper-version scrape-date \\\n", + "0 craigslist 1 2023-11-13 \n", + "1 craigslist 1 2023-11-13 \n", + "2 craigslist 1 2023-11-13 \n", + "3 craigslist 1 2023-11-13 \n", + "4 craigslist 1 2023-11-13 \n", + "\n", + " title price \\\n", + "0 2015 GMC Terrian SLT Leather Seats SUV $8,495 \n", + "1 2012 Ford Edge SUV $5,900 \n", + "2 2014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF... $29,999 \n", + "3 1-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR... $42,900 \n", + "4 2017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ... $42,897 \n", + "\n", + " location odometer \\\n", + "0 Clyde 165k mi \n", + "1 Abilene 127k mi \n", + "2 WWW.GETADIESEL.COM 227k mi \n", + "3 WWW.GETADIESEL.COM 143k mi \n", + "4 WWW.GETADIESEL.COM 180k mi \n", + "\n", + " images \n", + "0 ['https://images.craigslist.org/00q0q_fqrDYmbI... \n", + "1 ['https://images.craigslist.org/00u0u_djFxYThj... \n", + "2 ['https://images.craigslist.org/00z0z_fBJpyxit... \n", + "3 ['https://images.craigslist.org/00J0J_cBZBKQMO... \n", + "4 ['https://images.craigslist.org/00v0v_3LJpHDnn... " + ] + }, + "execution_count": 131, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "source 0\n", + "scraper-version 0\n", + "scrape-date 0\n", + "title 0\n", + "price 0\n", + "location 0\n", + "odometer 0\n", + "images 0\n", + "dtype: int64" + ] + }, + "execution_count": 132, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# look at the number of NA values by column\n", + "cars.isna().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [], + "source": [ + "#cars = cars.drop(columns = ['images/23','images/22','images/21','images/20','images/19','images/18','images/17','images/16','images/15','images/14','images/13','images/12','images/11','images/10','images/9','images/8', 'images/7','images/6','images/5','images/4','images/3','images/2','images/1'])" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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0craigslist12023-11-132015 GMC Terrian SLT Leather Seats SUV$8,495Clyde165k mi['https://images.craigslist.org/00q0q_fqrDYmbI...
1craigslist12023-11-132012 Ford Edge SUV$5,900Abilene127k mi['https://images.craigslist.org/00u0u_djFxYThj...
2craigslist12023-11-132014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF...$29,999WWW.GETADIESEL.COM227k mi['https://images.craigslist.org/00z0z_fBJpyxit...
3craigslist12023-11-131-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR...$42,900WWW.GETADIESEL.COM143k mi['https://images.craigslist.org/00J0J_cBZBKQMO...
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" + ], + "text/plain": [ + " source scraper-version scrape-date \\\n", + "0 craigslist 1 2023-11-13 \n", + "1 craigslist 1 2023-11-13 \n", + "2 craigslist 1 2023-11-13 \n", + "3 craigslist 1 2023-11-13 \n", + "4 craigslist 1 2023-11-13 \n", + "\n", + " title price \\\n", + "0 2015 GMC Terrian SLT Leather Seats SUV $8,495 \n", + "1 2012 Ford Edge SUV $5,900 \n", + "2 2014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF... $29,999 \n", + "3 1-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR... $42,900 \n", + "4 2017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ... $42,897 \n", + "\n", + " location odometer \\\n", + "0 Clyde 165k mi \n", + "1 Abilene 127k mi \n", + "2 WWW.GETADIESEL.COM 227k mi \n", + "3 WWW.GETADIESEL.COM 143k mi \n", + "4 WWW.GETADIESEL.COM 180k mi \n", + "\n", + " images \n", + "0 ['https://images.craigslist.org/00q0q_fqrDYmbI... \n", + "1 ['https://images.craigslist.org/00u0u_djFxYThj... \n", + "2 ['https://images.craigslist.org/00z0z_fBJpyxit... \n", + "3 ['https://images.craigslist.org/00J0J_cBZBKQMO... \n", + "4 ['https://images.craigslist.org/00v0v_3LJpHDnn... " + ] + }, + "execution_count": 133, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "176" + ] + }, + "execution_count": 134, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 135, + "metadata": {}, + "outputs": [], + "source": [ + "# drop NA values\n", + "cars = cars.dropna()" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "176" + ] + }, + "execution_count": 136, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 137, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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0craigslist12023-11-132015 GMC Terrian SLT Leather Seats SUV$8,495Clyde165k mi['https://images.craigslist.org/00q0q_fqrDYmbI...
1craigslist12023-11-132012 Ford Edge SUV$5,900Abilene127k mi['https://images.craigslist.org/00u0u_djFxYThj...
2craigslist12023-11-132014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF...$29,999WWW.GETADIESEL.COM227k mi['https://images.craigslist.org/00z0z_fBJpyxit...
3craigslist12023-11-131-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR...$42,900WWW.GETADIESEL.COM143k mi['https://images.craigslist.org/00J0J_cBZBKQMO...
4craigslist12023-11-132017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ...$42,897WWW.GETADIESEL.COM180k mi['https://images.craigslist.org/00v0v_3LJpHDnn...
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" + ], + "text/plain": [ + " source scraper-version scrape-date \\\n", + "0 craigslist 1 2023-11-13 \n", + "1 craigslist 1 2023-11-13 \n", + "2 craigslist 1 2023-11-13 \n", + "3 craigslist 1 2023-11-13 \n", + "4 craigslist 1 2023-11-13 \n", + "\n", + " title price \\\n", + "0 2015 GMC Terrian SLT Leather Seats SUV $8,495 \n", + "1 2012 Ford Edge SUV $5,900 \n", + "2 2014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF... $29,999 \n", + "3 1-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR... $42,900 \n", + "4 2017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ... $42,897 \n", + "\n", + " location odometer \\\n", + "0 Clyde 165k mi \n", + "1 Abilene 127k mi \n", + "2 WWW.GETADIESEL.COM 227k mi \n", + "3 WWW.GETADIESEL.COM 143k mi \n", + "4 WWW.GETADIESEL.COM 180k mi \n", + "\n", + " images \n", + "0 ['https://images.craigslist.org/00q0q_fqrDYmbI... \n", + "1 ['https://images.craigslist.org/00u0u_djFxYThj... \n", + "2 ['https://images.craigslist.org/00z0z_fBJpyxit... \n", + "3 ['https://images.craigslist.org/00J0J_cBZBKQMO... \n", + "4 ['https://images.craigslist.org/00v0v_3LJpHDnn... " + ] + }, + "execution_count": 137, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "# convert year and odometer to integer values\n", + "#cars['odometer'] = cars['odometer'].str.replace('K', '').str.replace(' miles', '').astype(int) * 1000\n", + "#cars['odometer'] = cars['odometer'].str.replace('K miles', '').str.replace(' miles ยท Dealership', '').astype(float).astype(int) * 1000\n", + "import re\n", + "cars['odometer'] = cars['odometer'].apply(lambda x: int(re.search(r'\\d+', str(x)).group(0)) if re.search(r'\\d+', str(x)) else None)\n", + "cars['year'] = cars['title'].str.extract(r'(\\d{4})')\n", + "# Fill NaN values in the 'year' column with a placeholder (you can choose a value that makes sense)\n", + "cars['year'].fillna(-1, inplace=True)\n", + "cars = cars.astype({'year':'int', 'odometer':'int'})" + ] + }, + { + "cell_type": "code", + "execution_count": 139, + "metadata": {}, + "outputs": [], + "source": [ + "# create an age variable to get a better understanding of how old a car is\n", + "cars['age'] = datetime.date.today().year - cars['year']" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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sourcescraper-versionscrape-datetitlepricelocationodometerimagesyearage
0craigslist12023-11-132015 GMC Terrian SLT Leather Seats SUV$8,495Clyde165['https://images.craigslist.org/00q0q_fqrDYmbI...20158
1craigslist12023-11-132012 Ford Edge SUV$5,900Abilene127['https://images.craigslist.org/00u0u_djFxYThj...201211
2craigslist12023-11-132014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF...$29,999WWW.GETADIESEL.COM227['https://images.craigslist.org/00z0z_fBJpyxit...20149
3craigslist12023-11-131-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR...$42,900WWW.GETADIESEL.COM143['https://images.craigslist.org/00J0J_cBZBKQMO...20194
4craigslist12023-11-132017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ...$42,897WWW.GETADIESEL.COM180['https://images.craigslist.org/00v0v_3LJpHDnn...20176
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" + ], + "text/plain": [ + " source scraper-version scrape-date \\\n", + "0 craigslist 1 2023-11-13 \n", + "1 craigslist 1 2023-11-13 \n", + "2 craigslist 1 2023-11-13 \n", + "3 craigslist 1 2023-11-13 \n", + "4 craigslist 1 2023-11-13 \n", + "\n", + " title price \\\n", + "0 2015 GMC Terrian SLT Leather Seats SUV $8,495 \n", + "1 2012 Ford Edge SUV $5,900 \n", + "2 2014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF... $29,999 \n", + "3 1-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR... $42,900 \n", + "4 2017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ... $42,897 \n", + "\n", + " location odometer \\\n", + "0 Clyde 165 \n", + "1 Abilene 127 \n", + "2 WWW.GETADIESEL.COM 227 \n", + "3 WWW.GETADIESEL.COM 143 \n", + "4 WWW.GETADIESEL.COM 180 \n", + "\n", + " images year age \n", + "0 ['https://images.craigslist.org/00q0q_fqrDYmbI... 2015 8 \n", + "1 ['https://images.craigslist.org/00u0u_djFxYThj... 2012 11 \n", + "2 ['https://images.craigslist.org/00z0z_fBJpyxit... 2014 9 \n", + "3 ['https://images.craigslist.org/00J0J_cBZBKQMO... 2019 4 \n", + "4 ['https://images.craigslist.org/00v0v_3LJpHDnn... 2017 6 " + ] + }, + "execution_count": 140, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data Exploration" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[Text(0.5, 1.0, 'Distribution of Car Ages')]" + ] + }, + "execution_count": 141, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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sourcescraper-versionscrape-datetitlepricelocationodometerimagesyearage
20craigslist12023-11-13Hyundai n line night edition$1Abilene43['https://images.craigslist.org/00d0d_kxEDyPhc...-12024
110craigslist12023-11-17VW Beetle$11,000De Leon123['https://images.craigslist.org/00y0y_beMk0BoY...-12024
171craigslist12023-11-17Semi truck$17,500Amarillo735['https://images.craigslist.org/00y0y_lf5lgq6v...-12024
\n", + "
" + ], + "text/plain": [ + " source scraper-version scrape-date title \\\n", + "20 craigslist 1 2023-11-13 Hyundai n line night edition \n", + "110 craigslist 1 2023-11-17 VW Beetle \n", + "171 craigslist 1 2023-11-17 Semi truck \n", + "\n", + " price location odometer \\\n", + "20 $1 Abilene 43 \n", + "110 $11,000 De Leon 123 \n", + "171 $17,500 Amarillo 735 \n", + "\n", + " images year age \n", + "20 ['https://images.craigslist.org/00d0d_kxEDyPhc... -1 2024 \n", + "110 ['https://images.craigslist.org/00y0y_beMk0BoY... -1 2024 \n", + "171 ['https://images.craigslist.org/00y0y_lf5lgq6v... -1 2024 " + ] + }, + "execution_count": 142, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars[cars['year'] < 1990]" + ] + }, + { + "cell_type": "code", + "execution_count": 143, + "metadata": {}, + "outputs": [], + "source": [ + "cars = cars[cars.year >= 2005]" + ] + }, + { + "cell_type": "code", + "execution_count": 144, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "173" + ] + }, + "execution_count": 144, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 145, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Text(0.5, 1.0, 'Distribution of Car Ages')]" + ] + }, + "execution_count": 145, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# looking again at the distribution of ages\n", + "sns.histplot(data = cars, x = 'age', binwidth = 1).set(title = 'Distribution of Car Ages')" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "173" + ] + }, + "execution_count": 146, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[Text(0.5, 1.0, 'Distribution of Car Odometer')]" + ] + }, + "execution_count": 147, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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sourcescraper-versionscrape-datetitlepricelocationodometerimagesyearage
14craigslist12023-11-132015 *Peterbilt* *579* *w/sleeper*$42,900Peterbilt 579 w/sleeper627['https://images.craigslist.org/00u0u_iI62XuOK...20158
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" + ], + "text/plain": [ + " source scraper-version scrape-date \\\n", + "14 craigslist 1 2023-11-13 \n", + "\n", + " title price location \\\n", + "14 2015 *Peterbilt* *579* *w/sleeper* $42,900 Peterbilt 579 w/sleeper \n", + "\n", + " odometer images year age \n", + "14 627 ['https://images.craigslist.org/00u0u_iI62XuOK... 2015 8 " + ] + }, + "execution_count": 148, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars[cars['odometer'] > 300]" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "metadata": {}, + "outputs": [], + "source": [ + "cars = cars[cars.odometer <= 300]\n", + "# Clean up the 'price' column by replacing non-numeric values with NaN\n", + "cars['price'] = pd.to_numeric(cars['price'].replace('[\\$,]', '', regex=True), errors='coerce')\n", + "\n", + "# Fill NaN values in the 'price' column with a placeholder (you can choose a value that makes sense)\n", + "cars['price'].fillna(-1, inplace=True)\n", + "\n", + "# Convert 'price' column to integers\n", + "cars['price'] = cars['price'].astype(int)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 150, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "172" + ] + }, + "execution_count": 150, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 151, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[Text(0.5, 1.0, 'Distribution of Car Odometer')]" + ] + }, + "execution_count": 151, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.histplot(data = cars, x = 'odometer').set(title = 'Distribution of Car Odometer')" + ] + }, + { + "cell_type": "code", + "execution_count": 152, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[Text(0.5, 1.0, 'Correlation of Vehicle Odometer and List Price')]" + ] + }, + "execution_count": 152, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: [source, scraper-version, scrape-date, title, price, location, odometer, images, year, age]\n", + "Index: []" + ] + }, + "execution_count": 153, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars[cars['price'] > 100000]" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "metadata": {}, + "outputs": [], + "source": [ + "cars = cars[cars.price <= 100000]" + ] + }, + { + "cell_type": "code", + "execution_count": 156, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "172" + ] + }, + "execution_count": 156, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 157, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[Text(0.5, 1.0, 'Correlation of Vehicle Odometer and List Price')]" + ] + }, + "execution_count": 157, + "metadata": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# look at the odometer vs price now\n", + "sns.scatterplot(data = cars, x = 'odometer', y = 'price').set(title = 'Correlation of Vehicle Odometer and List Price')" + ] + }, + { + "cell_type": "code", + "execution_count": 158, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[Text(0.5, 1.0, 'Distribution of List Price')]" + ] + }, + "execution_count": 158, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "
" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: [source, scraper-version, scrape-date, title, price, location, odometer, images, year, age]\n", + "Index: []" + ] + }, + "execution_count": 159, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars[cars['price'] < 1000]" + ] + }, + { + "cell_type": "code", + "execution_count": 160, + "metadata": {}, + "outputs": [], + "source": [ + "cars = cars[cars.price >= 1000]" + ] + }, + { + "cell_type": "code", + "execution_count": 161, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Text(0.5, 1.0, 'Distribution of List Price')]" + ] + }, + "execution_count": 161, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.histplot(data = cars, x = 'price').set(title = 'Distribution of List Price')" + ] + }, + { + "cell_type": "code", + "execution_count": 162, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "172" + ] + }, + "execution_count": 162, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 174, + "metadata": {}, + "outputs": [], + "source": [ + "#Dictionary of car makes\n", + "kbb_make = {\n", + " 'acura',\n", + " 'alfa-romeo',\n", + " 'aston-martin',\n", + " 'audi',\n", + " 'bentley',\n", + " 'bmw',\n", + " 'buick',\n", + " 'cadillac',\n", + " 'chevrolet',\n", + " 'chrysler',\n", + " 'dodge',\n", + " 'ferrari',\n", + " 'fiat',\n", + " 'ford',\n", + " 'genesis',\n", + " 'gmc',\n", + " 'honda',\n", + " 'hyundai',\n", + " 'infiniti',\n", + " 'jaguar',\n", + " 'jeep',\n", + " 'kia',\n", + " 'lamborghini',\n", + " 'land rover',\n", + " 'lexus',\n", + " 'lincoln',\n", + " 'lucid',\n", + " 'maserati',\n", + " 'mazda',\n", + " 'mclaren',\n", + " 'mercedes-benz',\n", + " 'mini',\n", + " 'mitsubishi',\n", + " 'nissan',\n", + " 'polestar',\n", + " 'porsche',\n", + " 'ram',\n", + " 'rivian',\n", + " 'rolls-royce',\n", + " 'subaru',\n", + " 'tesla',\n", + " 'toyota',\n", + " 'volkswagen',\n", + " 'volvo',\n", + "}\n", + "\n", + "# Dictionary to store car models for each make\n", + "kbb_models = {\n", + " 'acura': ['ILX', 'MDX', 'NSX','RDX','TLX'],\n", + " 'alfa-romeo': ['Giulia', 'Stelvio'],\n", + " 'aston-martin': ['DB11', 'DBS', 'DBX','Vantage'],\n", + " 'audi': ['A3', 'A4','A4 allroad','A5', 'A6','A6 allroad',\n", + " 'A7','A8','e-tron','e-tron GT','e-tron S',\n", + " 'e-tron S Sportback','e-tron Sportback','Q3',\n", + " 'Q4 e-tron','Q4 Sportback e-tron','Q5', \n", + " 'Q5 Sportback','Q7','Q8','R8','RS 3','RS 5',\n", + " 'RS 6','RS 7', 'RS e-tron GT','RS Q8','S3',\n", + " 'S4','S5','S6','S7','S8','SQ5','SQ5 Sportback',\n", + " 'SQ7','SQ8','TT'],\n", + " 'bentley': ['Bentayga','Continental GT','Flying Spur'],\n", + " 'bmw': ['2 Series','3 Series','4 Series', '5 Series',\n", + " '6 Series','7 Series','8 Series','i4','iX','M3',\n", + " 'M4','M5','M8','X1','X2','X3','X3 M','X4','X4 M','X5',\n", + " 'X5 M','X6','X6 M','X7','Z4'],\n", + " 'buick': ['Enclave','Encore','Encore GX','Envision'],\n", + " 'cadillac': ['CT4','CT5','Escalade','Escalade ESV','XT4','XT5','XT6'],\n", + " 'chevrolet': ['Blazer','Bolt EUV','Bolt EV','Camaro','Colorado Crew Cab',\n", + " 'Colorado Extended Cab','Corvette','Equinox','Express 2500 Cargo',\n", + " 'Express 2500 Passenger','Express 3500 Cargo','Express 3500 Passenger',\n", + " 'Malibu','Silverado 1500 Crew Cab','Silverado 1500 Double Cab',\n", + " 'Silverado 1500 Regular Cab','Silverado 1500 Limited Crew Cab',\n", + " 'Silverado 1500 Limited Double Cab','Silverado 1500 Limited Regular Cab',\n", + " 'Silverado 2500 HD Crew Cab','Silverado 2500 HD Double Cab',\n", + " 'Silverado 2500 HD Regular Cab','Silverado 3500 HD Crew Cab',\n", + " 'Silverado 3500 HD Double Cab','Silverado 3500 HD Regular Cab',\n", + " 'Spark','Suburban','Tahoe','Trailblazer','Traverse','Trax',\n", + " 'Avalanche','Cruze','Impala','Lumina','Malibu Maxx','Monte Carlo','SS','Uplander','Venture'],\n", + " 'chrysler': ['300','Pacifica','Pacifica Hybrid','Voyager'],\n", + " 'dodge': ['Charger', 'Challenger', 'Durango'],\n", + " 'ferrari': ['296 GTB','812 Competizione','812 Competizione A','812 GTS',\n", + " 'F8', 'Portofino', 'SF90', 'Roma'],\n", + " 'fiat': ['500X'],\n", + " 'ford': ['Bronco', 'Bronco Sport','E-Transit 350 Cargo Van','EcoSport', 'Edge', \n", + " 'Escape','Escape Plug-in Hybrid', 'Expedition','Expedition MAX', \n", + " 'Explorer', 'F150 Lightning', 'F150 Regular Cab','F150 Super Cab',\n", + " 'F150 SuperCrew Cab', 'F250 Super Duty Crew Cab','F250 Super Duty Regular Cab',\n", + " 'F250 Super Duty Super Cab', 'F350 Super Duty Crew Cab','F350 Super Duty Regular Cab',\n", + " 'F350 Super Duty Super Cab', 'F450 Super Duty Crew Cab','F450 Super Duty Regular Cab', \n", + " 'Maverick', 'Mustang','Mustang MACH-E', 'Ranger SuperCab','Ranger SuperCrew', \n", + " 'Transit 150 Cargo Van', 'Transit 150 Crew Van', 'Transit 150 Passenger Van', \n", + " 'Transit 250 Cargo Van', 'Transit 250 Crew Van', 'Transit 350 HD Cargo Van', 'Transit 350 HD Crew Van',\n", + " 'Transit 350 Cargo Van', 'Transit 350 Crew Van', 'Transit 350 Passenger Van', \n", + " 'Transit Connect Cargo Van', 'Transit Connect Passenger Wagon','C-Max Hybrid','C-Max Energi',\n", + " 'Fiesta','Flex','Focus','Fusion','Mustang Mach-E','Taurus','Thunderbird'],\n", + " 'genesis': ['G70', 'G80','G90', 'GV70','GV80'],\n", + " 'gmc': ['Acadia','Canyon Crew Cab','Canyon Extended Cab','HUMMER EV Pickup','Savana 2500 Cargo','Savana 2500 Passenger', \n", + " 'Savana 3500 Cargo','Savana 3500 Passenger','Sierra 1500 Crew Cab', 'Sierra 1500 Double Cab','Sierra 1500 Regular Cab',\n", + " 'Sierra 1500 Limited Crew Cab', 'Sierra 1500 Limited Double Cab', 'Sierra 1500 Limited Regular Cab', \n", + " 'Sierra 2500 HD Crew Cab','Sierra 2500 HD Double Cab','Sierra 2500 HD Regular Cab', 'Sierra 3500 HD Crew Cab',\n", + " 'Sierra 3500 HD Double Cab','Sierra 3500 HD Regular Cab', 'Yukon', 'Yukon XL', 'Terrain','C1500 Pickup','C2500 Pickup',\n", + " 'C3500 Pickup','Envoy','Envoy XL','Envoy XUV','Jimmy','R/V 3500 Series','S15 Jimmy','Safari','Savana 1500 Cargo',\n", + " 'Savana 1500 Passenger','Savana 2500 Cargo','Savana 2500 Passenger','Savana 3500 Cargo',\n", + " 'Savana 3500 Passenger','Sierra 1500 Classic Crew Cab','Sierra 1500 Classic Double Cab',\n", + " 'Sierra 1500 Classic Regular Cab','Sierra 1500 HD Classic Crew Cab','Sierra 1500 HD Classic Double Cab',\n", + " 'Sierra 1500 HD Classic Regular Cab','Sierra 2500 Classic Crew Cab','Sierra 2500 Classic Double Cab',\n", + " 'Sierra 2500 Classic Regular Cab','Sierra 3500 Classic Crew Cab','Sierra 3500 Classic Double Cab',\n", + " 'Sierra 3500 Classic Regular Cab','Sonoma','Suburban 1500','Suburban 2500','Syclone','Typhoon',\n", + " 'Vandura 1500','Vandura 2500','Vandura 3500','Yukon XL 1500','Yukon XL 2500'],\n", + " 'honda': ['Accord', 'Accord Hybrid', 'Civic', 'CR-V', 'CR-V Hybrid', 'HR-V', 'Insight', 'Odyssey', 'Passport', 'Pilot',\n", + " 'Fit','Element','Prelude','S2000','Crosstour','Ridgeline'],\n", + " 'hyundai': ['Accent', 'Elantra', 'Elantra N' , 'IONIQ5', 'Ioniq Hybrid','Ioniq Plug-in Hybrid','Kona', 'Kona Electric', 'Kona N',\n", + " 'Palisade', 'Santa Fe', 'Santa Fe Hybrid', 'Santa Fe Plug-in Hybrid','Sonata', 'Sonata Hybrid', 'Tucson', 'Tucson Hybrid', \n", + " 'Tucson Plug-in Hybrid', 'Venue', 'Veloster', 'Santa Cruz','Azera','Equus','Genesis Coupe','Genesis G70','Genesis G80',\n", + " 'Genesis G90','Santa Fe Sport','Santa Fe XL','Veracruz'],\n", + " 'infiniti': ['Q50', 'Q60','QX50','QX55','QX60','QX80','EX35','EX37','FX35','FX37','FX45','FX50',\n", + " 'G25','G35','G37','I30','I35','JX35',\n", + " 'M35','M35h','M37','M45','M56','Q40',\n", + " 'Q45','QX4','QX56','QX60 Hybrid',\n", + " 'QX70',],\n", + " 'jaguar': ['XF', 'E-PACE','F-PACE','F-TYPE', 'I-PACE','S-Type','X-Type','XE','XE SV Project 8','XJ','XJR',\n", + " 'XJR-S','XJS','XK','XK-Series'],\n", + " 'jeep': ['Cherokee', 'Compass', 'Gladiator', 'Grand Cherokee', 'Grand Cherokee 4xe', 'Grand Cherokee L', 'Grand Wagoneer','Renegade', \n", + " 'Wagoneer','Wrangler','Wrangler Unlimited', 'Wrangler Unlimited 4xe','CJ-5','CJ-7','CJ-8 Scrambler','Commander','Comanche','Dispatcher',\n", + " 'FC-150','FC-170','FC-170 DRW','Gladiator (JT)','Grand Cherokee SRT',\n", + " 'Grand Cherokee SRT8','Grand Cherokee Trackhawk','Grand Wagoneer (SJ)',\n", + " 'J-100','J-2500','J-2600','J-2700','J-2800','J-3500','J-3600',\n", + " 'J-3700','J-3800','J10','J20','Jeepster','Jeepster Commando','Liberty',\n", + " 'Patriot','Scrambler','Wagoneer (SJ)','Wagoneer (XJ)','Willys','Wrangler (JK)',\n", + " 'Wrangler (LJ)','Wrangler (TJ)','Wrangler (YJ)'],\n", + " 'kia': ['Cadenza', 'Forte', 'K5', 'K900', 'Niro', 'Rio', 'Seltos', 'Sorento', 'Soul', 'Sportage', 'Stinger', \n", + " 'Telluride','Amanti','Borrego','Forte5','K900','Optima','Optima Hybrid','Rondo','Sedona',\n", + " 'Sephia','Sorento Sport','Soul EV','Spectra','Sportage Hybrid','Telluride Nightfall Edition'],\n", + " 'lamborghini': ['Aventador', 'Huracan', 'Urus','Gallardo','Centenario','Diablo','Gallardo Spyder','Huracan Evo','Huracan Evo Spyder',\n", + " 'Huracan Performante','Huracan Performante Spyder','Huracan Spyder',\n", + " 'Murcielago','Murcielago Roadster','Reventon','Urus Graphite Capsule'],\n", + " 'land rover': ['LR2','LR4','Defender', 'Discovery', 'Discovery Sport', 'Range Rover', 'Range Rover Evoque', 'Range Rover Sport', 'Range Rover Velar',\n", + " 'Discovery Series II','Discovery Series II SD','Discovery Sport SD',\n", + " 'Discovery Series II SE7','Discovery Series II XD','Freelander',\n", + " 'Freelander SE','Freelander SE3','LR2 HSE','LR3','LR3 HSE','LR3 SE',\n", + " 'LR4 HSE','LR4 HSE LUX','LR4 V8','LR4 V8 HSE LUX','Range Rover 4.0 SE',\n", + " 'Range Rover 4.6 HSE','Range Rover HSE','Range Rover Velar R-Dynamic',\n", + " 'Range Rover Velar S','Range Rover Velar SE','Range Rover Velar SVAutobiography Dynamic',\n", + " 'Range Rover Westminster','Range Rover Westminster Edition','Range Rover 4.6 HSE',\n", + " 'Range Rover Autobiography','Range Rover Autobiography Black','Range Rover Autobiography Black LWB',\n", + " 'Range Rover Autobiography L','Range Rover Autobiography LWB',\n", + " 'Range Rover HSE','Range Rover HSE LUX','Range Rover Long Wheelbase','Range Rover SE',\n", + " 'Range Rover Sport','Range Rover Sport 5.0L V8 Supercharged','Range Rover Sport GT Limited Edition',\n", + " 'Range Rover Sport HSE','Range Rover Sport HST','Range Rover Sport Limited Edition','Range Rover Sport SC',\n", + " 'Range Rover Sport SE','Range Rover Sport Supercharged','Range Rover Sport SVR',\n", + " 'Range Rover Velar','Range Rover Velar First Edition','Range Rover Velar P250 S','Range Rover Velar P250 SE',\n", + " 'Range Rover Velar P250 R-Dynamic S','Range Rover Velar P250 R-Dynamic SE','Range Rover Velar P250 R-Dynamic HSE',\n", + " 'Range Rover Velar P340 S','Range Rover Velar P340 SE','Range Rover Velar P340 R-Dynamic S',\n", + " 'Range Rover Velar P340 R-Dynamic SE','Range Rover Velar P380 R-Dynamic HSE','Range Rover 4.0 SE',\n", + " 'Range Rover Autobiography','Range Rover Autobiography Black',\n", + " 'Range Rover Autobiography Black LWB','Range Rover Autobiography L',\n", + " 'Range Rover Autobiography LWB','Range Rover HSE','Range Rover HSE LUX',\n", + " 'Range Rover Long Wheelbase','Range Rover SE'],\n", + " 'lexus': ['ES', 'GS', 'GX', 'IS', 'LS', 'LX', 'NX', 'RC', 'RX', 'UX','CT','ES 250','ES 300','ES 300h','ES 330','ES 350','GS 200t','GS 300',\n", + " 'GS 350','GS 400','GS 430','GS 450h','GS 460','GS F','GX 460','GX 470','HS 250h','IS 200t','IS 250',\n", + " 'IS 300','IS 350','IS 350C','LC 500','LC 500h','LFA','LS 400',\n", + " 'LS 430','LS 460','LS 500','LS 500h','LS 600h','LX 450','LX 470',\n", + " 'LX 570','NX 200t','NX 300','NX 300h','RC 200t','RC 300','RC 350',\n", + " 'RC F','RX 300','RX 330','RX 350','RX 350L','RX 400h','RX 450h',\n", + " 'RX 450hL','SC 300','SC 400','SC 430','UX 200','UX 250h',\n", + " 'GS 300','GS 350','GS 450h','GS F','IS 200t','IS 300',\n", + " 'LC 500','LC 500h','LS 500','LS 500h','LX 570','NX 200t',\n", + " 'NX 300','RC 300','RC 350','RC F','RX 350','RX 450h',\n", + " 'ES 250','ES 300','ES 300h','ES 330','ES 350','GS 200t',\n", + " 'GS 300','GS 350','GS 400','GS 430','GS 450h','GS F','GX 460',\n", + " 'GX 470','HS 250h','IS 200t','IS 250','IS 300','IS 350',\n", + " 'IS 350C','LC 500','LC 500h','LFA','LS 400','LS 430',\n", + " 'LS 460','LS 500','LS 500h','LS 600h','LX 450','LX 470',\n", + " 'LX 570','NX 200t','NX 300','NX 300h','RC 200t','RC 300',\n", + " 'RC 350','RC F','RX 300','RX 330','RX 350','RX 350L',\n", + " 'RX 400h','RX 450h','RX 450hL','SC 300','SC 400','SC 430',\n", + " 'UX 200','UX 250h'],\n", + " 'lincoln': ['Aviator', 'Continental', 'Corsair', 'MKS','MKZ','MKT','MKX', 'Nautilus', 'Navigator', 'Navigator L','Blackwood','Capri','Continental Mark III','Continental Mark IV',\n", + " 'Continental Mark V','Continental Mark VI','Corsair','LS','Mark LT',\n", + " 'Mark VI','Mark VII','Mark VIII','MKS','MKT','MKX','MKZ',\n", + " 'Nautilus','Navigator','Navigator L','Town Car','Versailles',\n", + " 'Zephyr'],\n", + " 'lucid': ['Air','Air Dream Edition','Air Grand Touring','Air Pure','Air Touring'],\n", + " 'maserati': ['Ghibli', 'GranTurismo','Levante','MC20', 'Quattroporte','430','GranSport','GranTurismo MC','Levante GTS','Levante S',\n", + " 'Quattroporte GTS','Quattroporte S','Quattroporte Trofeo'],\n", + " 'mazda': ['CX-30', 'CX-5', 'CX-9', 'Mazda3', 'Mazda6', 'MX-5 Miata','323','626','929','B-Series Pickup','CX-3','CX-7','CX-9',\n", + " 'GLC','Mazda2','Mazda3 Sport','Mazda5','Mazda6 Sport',\n", + " 'MAZDASPEED MX-5','MAZDASPEED Protege','MAZDASPEED3',\n", + " 'MAZDASPEED6','Millenia','MPV','MX-3','MX-5 Miata RF','MX-6',\n", + " 'Navajo','Protege','Protege5','RX-7','RX-8','Tribute'],\n", + " 'mclaren': ['570S', '600LT', '720S', '765LT','GT',\n", + " '570S Spider','600LT Spider','620R','675LT','675LT Spider',\n", + " '720S Spider','765LT Spider','GT','GT Coupe','GT Spider',\n", + " 'MP4-12C','MP4-12C Spider','P1'],\n", + " 'mclaren': ['570S', '600LT', '720S', '765LT','GT'],\n", + " 'mercedes-benz': ['A-Class', 'C-Class', 'E-Class', 'G-Class', 'GLA', 'GLC', 'GLE', 'GLS', 'S-Class','190-Class','260-Class','300-Class','350-Class','380-Class','400-Class','420-Class',\n", + " '450-Class','500-Class','560-Class','600-Class','AMG GT','B-Class','C-Class Coupe',\n", + " 'C-Class Wagon','CL-Class','CLA','CLA-Class','CLK-Class','CLS','CLS-Class',\n", + " 'E-Class Coupe','E-Class Wagon','G-Class','GL-Class','GLA-Class','GLB','GLB-Class',\n", + " 'GLC Coupe','GLC-Class','GLE Coupe','GLE-Class','GLK-Class','GLS-Class',\n", + " 'M-Class','Maybach S-Class','Metris','R-Class','S-Class Coupe',\n", + " 'S-Class Maybach','SL-Class','SLC-Class','SLK-Class','SLR McLaren','SLS AMG',\n", + " 'Sprinter'],\n", + " 'mini': ['Clubman', 'Convertible', 'Countryman', 'Hardtop','Cooper','Cooper Clubman','Cooper Countryman','Cooper Paceman',\n", + " 'Hardtop 2 Door','Hardtop 4 Door','John Cooper Works',\n", + " 'John Cooper Works Clubman','John Cooper Works Convertible',\n", + " 'John Cooper Works Countryman','John Cooper Works Hardtop',\n", + " 'John Cooper Works Hardtop 2 Door','John Cooper Works Hardtop 4 Door',\n", + " 'John Cooper Works Paceman'],\n", + " 'mitsubishi': ['Outlander', 'Eclipse Cross', 'Pajero','3000GT','Diamante','Eclipse','Eclipse Spyder','Endeavor','Expo',\n", + " 'Galant','Lancer','Mighty Max','Mirage','Montero','Montero Sport',\n", + " 'Outlander PHEV','Outlander Sport','Raider','Sigma','Van'],\n", + " 'nissan': ['370Z', 'Altima', 'Armada', 'Frontier', 'Kicks', 'LEAF', 'Maxima', 'Murano', 'NV Cargo', 'NV Passenger', 'NV200', 'Pathfinder', 'Rogue', 'Rogue Sport', 'Titan', 'Versa',\n", + " '200SX','240SX','300ZX','350Z','370Z Coupe','370Z NISMO','370Z Roadster',\n", + " 'Altima Hybrid','Armada','Cube','Frontier King Cab','Frontier Crew Cab',\n", + " 'GT-R','Kicks','LEAF','Maxima','Murano','Murano CrossCabriolet','NV Cargo','NV Passenger','NV200',\n", + " 'Pathfinder','Quest','Rogue','Rogue Select','Rogue Sport',\n", + " 'Sentra','Titan King Cab','Titan Crew Cab','Titan XD',\n", + " 'Versa','Versa Note','Versa Sedan','Xterra','Altima','Armada',\n", + " 'Cube','Frontier','GT-R','JUKE','Kicks','LEAF','Maxima',\n", + " 'Murano','Murano CrossCabriolet','NV Cargo','NV Passenger',\n", + " 'NV200','Pathfinder','Quest','Rogue','Rogue Select','Rogue Sport',\n", + " 'Sentra','Titan'],\n", + " 'polestar': ['2', '1', '3'],\n", + " 'porsche': ['911', 'Cayenne', 'Macan', 'Panamera', 'Taycan','718 Cayman','911 Carrera','911 Carrera 4','911 Carrera 4 Cabriolet',\n", + " '911 Carrera 4 GTS','911 Carrera 4S','911 Carrera 4S Cabriolet',\n", + " '911 Carrera Cabriolet','911 Carrera GTS','911 Carrera S',\n", + " '911 Carrera S Cabriolet','911 Targa','911 Targa 4',\n", + " '911 Targa 4 GTS','911 Targa 4S','911 Turbo','911 Turbo Cabriolet',\n", + " '911 Turbo S','911 Turbo S Cabriolet','918 Spyder','Boxster',\n", + " 'Carrera GT','Cayenne','Cayenne Coupe','Cayenne E-Hybrid','Cayenne GTS',\n", + " 'Cayenne S','Cayenne S E-Hybrid','Cayenne Turbo','Cayenne Turbo S E-Hybrid',\n", + " 'Cayman','Macan','Panamera','Panamera 4','Panamera 4 E-Hybrid',\n", + " 'Panamera 4 Executive','Panamera 4S','Panamera 4S E-Hybrid',\n", + " 'Panamera Executive','Panamera GTS','Panamera S','Panamera Turbo',\n", + " 'Panamera Turbo Executive','Panamera Turbo S E-Hybrid'],\n", + " 'ram': ['1500', '2500', '3500','1500 Classic','1500 Classic Crew Cab','1500 Classic Quad Cab',\n", + " '1500 Classic Regular Cab','2500','3500','3500 Chassis Cab',\n", + " '4500 Chassis Cab','5500 Chassis Cab','C/V','Dakota',\n", + " 'ProMaster Cargo Van','ProMaster Chassis Cab','ProMaster City Cargo',\n", + " 'ProMaster City Wagon','ProMaster Cutaway','ProMaster Window Van'],\n", + " 'rivian': ['R1T', 'R1S'],\n", + " 'rolls-royce': ['Cullinan', 'Dawn', 'Ghost', 'Phantom', 'Wraith','Cullinan Black Badge','Dawn','Dawn Black Badge','Ghost',\n", + " 'Ghost Black Badge','Phantom','Phantom Drophead Coupe',\n", + " 'Phantom Drophead Coupe Waterspeed Collection','Phantom Coupe',\n", + " 'Phantom Coupe Aviator Collection','Phantom Coupe Waterspeed Collection',\n", + " 'Phantom Coupe Tiger Edition','Wraith','Wraith Black Badge'],\n", + " 'subaru': ['Ascent', 'BRZ', 'Crosstrek', 'Forester', 'Impreza', 'Legacy', 'Outback', 'WRX',\n", + " 'Ascent','Baja','BRAT','BRZ','Crosstrek','Crosstrek Hybrid',\n", + " 'Forester','Impreza','Impreza Outback Sport','Impreza WRX',\n", + " 'Legacy','Outback','SVX','Tribeca','WRX','XT','XT6'],\n", + " 'tesla': ['Model 3', 'Model S', 'Model X', 'Model Y'],\n", + " 'toyota': ['4Runner', 'Avalon', 'C-HR', 'Camry', 'Corolla', 'Highlander', 'Land Cruiser', 'Prius', 'RAV4', \n", + " 'Sequoia', 'Sienna', 'Tacoma', 'Tundra', 'Venza', 'Yaris', 'Corolla Hatchback',\n", + " 'Corolla Hybrid','Corolla iM','FJ Cruiser','GR86','Highlander',\n", + " 'Highlander Hybrid','Land Cruiser','Matrix','Mirai','MR2',\n", + " 'MR2 Spyder','Paseo','Previa','Prius','Prius c','Prius Plug-in',\n", + " 'Prius Prime','Prius Prime Advanced','Prius Prime Premium',\n", + " 'Prius v','RAV4','RAV4 Prime','Sequoia','Sienna',\n", + " 'Supra','T100','Tacoma','Tercel','Tundra','Venza',\n", + " 'Yaris','Yaris iA','4Runner','Avalon','Avalon Hybrid',\n", + " 'C-HR','Camry','Camry Hybrid','Camry Solara','Celica',\n", + " 'Corolla','Corolla Hatchback','Corolla Hybrid','Corolla iM',\n", + " 'FJ Cruiser','GR86','Highlander','Highlander Hybrid',\n", + " 'Land Cruiser','Matrix','Mirai','MR2','MR2 Spyder',\n", + " 'Paseo','Previa','Prius','Prius c','Prius Plug-in',\n", + " 'Prius Prime','Prius Prime Advanced','Prius Prime Premium',\n", + " 'Prius v','RAV4','RAV4 Prime','Sequoia','Sienna',\n", + " 'Supra','T100','Tacoma','Tercel','Tundra','Venza',\n", + " 'Yaris','Yaris iA'],\n", + " 'volkswagen': ['Arteon', 'Atlas', 'Golf', 'Jetta', 'Passat', 'Tiguan',\n", + " 'Atlas','Atlas Cross Sport','Beetle','Cabrio',\n", + " 'CC','e-Golf','EuroVan','Fox','GLI','Golf','Golf Alltrack',\n", + " 'Golf GTI','Golf R','Golf SportWagen','ID.4','Jetta','Jetta GLI',\n", + " 'Karmann Ghia','Microbus','Passat','Quantum','R32','Rabbit',\n", + " 'Routan','Tiguan','Touareg','Touareg 2'],\n", + " 'volvo': ['S60', 'S90', 'V60', 'V90', 'XC40', 'XC60', 'XC90','240','740','760','780','850','940','960','C30',\n", + " 'C40 Recharge','C70','S40','S60 Cross Country','S60 Recharge',\n", + " 'S70','S80','S90 Recharge','V40','V50','V60','V60 Cross Country',\n", + " 'V60 Recharge','V70','V90','V90 Cross Country','V90 Recharge',\n", + " 'XC40','XC40 Recharge','XC60','XC60 Recharge','XC70',\n", + " 'XC90','XC90 Recharge'],\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 199, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " manufacturer model\n", + "0 gmc Terrain\n", + "1 ford Edge\n", + "2 ford F350\n", + "3 chevrolet 3500HD\n", + "4 ford F250\n", + ".. ... ...\n", + "170 ford F250\n", + "172 toyota Prius\n", + "173 chevrolet Silverado 1500 Crew Cab\n", + "174 ford F350\n", + "175 ford F350\n", + "\n", + "[169 rows x 2 columns]\n" + ] + }, + { + "data": { + "text/plain": [ + "([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19],\n", + " [Text(0, 0, 'gmc'),\n", + " Text(1, 0, 'ford'),\n", + " Text(2, 0, 'chevrolet'),\n", + " Text(3, 0, 'ram'),\n", + " Text(4, 0, 'bmw'),\n", + " Text(5, 0, 'jeep'),\n", + " Text(6, 0, 'nissan'),\n", + " Text(7, 0, 'kia'),\n", + " Text(8, 0, 'cadillac'),\n", + " Text(9, 0, 'dodge'),\n", + " Text(10, 0, 'acura'),\n", + " Text(11, 0, 'volkswagen'),\n", + " Text(12, 0, 'subaru'),\n", + " Text(13, 0, 'honda'),\n", + " Text(14, 0, 'land rover'),\n", + " Text(15, 0, 'hyundai'),\n", + " Text(16, 0, 'buick'),\n", + " Text(17, 0, 'toyota'),\n", + " Text(18, 0, 'infiniti'),\n", + " Text(19, 0, 'lexus')])" + ] + }, + "execution_count": 199, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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nEwAaPXq0OOOZ279/Ln97LSkpiRISEujevXuUmZkp58gKv0mTJpGZmRnt27eP1q1bJ+9wCi1pH8iOHTvIxcWFDh48SK9fv5Z3WD/EbygKKDk5mbZu3Upr1qwhHx8fqlWrlrxDKrSktWmPHDlCnz59oufPn1NUVBTNmTOHS6L9B0xMTGjIkCF069Yt0tPTo+7duxOR4r187Nu3j3x8fCggIIB2794tjrpUtBf2v+rb46KhoUH9+/ennTt38nX6HdIXhqSkJEpNTaX4+HiKjY2l+Ph4mjdvHq1YsYJCQ0Nl9mU/JggCbd++nZo1a0YBAQHUvn17Cg4OlndYciNtCMfGxpKzszMNGTKE/Pz8qG3btnT16lW+j/1EWVlZFBERQcHBwTRgwACqV68eESneM/OPSF/8R40aRZMnTyYTExMyMzOjyMhIcnNz4863H4iNjaWOHTtSQEAADRs2jOzs7CgzM5NKlCjB1/BPkv86XbRoEc2ePZtatGhBOTk5FB4errADJ8qVK0cTJkygSpUqUXh4OO3cuVPeIRU60ufsuXPnKDw8nGbOnEk3b97k5PNPVKZMGXJxcaFSpUrR8ePHiSivX4CfGXkEQaC6devSnDlz6MmTJ7Rw4UI6e/asvMOSi5MnT9LAgQMpNDSUsrKySFlZmXJycujLly9Uvnx5eYdXJOSv+DBmzBjq2rUr9e/fnxwdHWnatGl0584dOUdYuORvE+SfMX7ixAny9fWlTZs2ySOsQk8QBEpMTCRfX1+aO3cuTZkyhapVqybvsH6In+gK6MWLFySRSMja2lrcxnU1v08QBNq/fz+1bNmSypYtS9OmTaOgoCDau3cvzZ8/n+7fvy/vEIsN6TloZGREM2bMoDJlypClpaU4SkVRGscnTpygLl26kKamJp05c4ZmzZpFEydOpNzcXIV7Yf+7bt26RUR5L1iurq507949cWq+opw/f9XatWtpzJgx9OzZMzIyMiIiIk1NTXJ3d6dZs2ZRbGwspaamyjnKwk16LWZkZNCcOXMoPDyc4uPjae3atRQdHU1+fn7yDVBOBEGgQ4cOUe/evWnSpEl05coVOnz4MB04cIAGDx5Mly5d4vvYT/Llyxe6fv061a1bl4j+14aTvvB+/vxZbrEVJklJSbR7927atWsXjRgxgszNzenNmzfk5uYms2A0n5d5Dh06RH5+fjRy5Ei6evUqzZw5k06fPk3NmjWj169fc1vkJ5FepydOnKCsrCzasGEDTZ48mVatWkVBQUG0a9cuGjJkCBEV74SN9He9e/dO3GZra0vjxo0jZWVlioiI4Bk2+eQfGezq6kqbN2+mgwcPkpmZGcXHx8s7vCIr//UlkUhIW1ubhgwZQsHBwXTy5EkaOXIkEeUlbBSxv+RHv9nV1ZVGjhxJ9+/fp0WLFilkwsbKyoo8PT0pJSWFQkNDKTMzk5SVlals2bJUpUoVIsqrmMH9bT8mHRw4c+ZMWrNmDUVHR1NaWhq1a9eOli9fTnPnzuWlCPIRBIFevHhBb968oZIlS9LevXvp8OHDFBYWRmPHjiVfX1/asGGDvMMslA4ePEhdu3YlPz8/ys3NpTNnzlBQUBCNGzeODhw4IO/wZIEpnOPHj0NTUxOnTp0St+Xm5gIAtm/fjpSUFHmFVqjk5uZCIpGge/fu6N69u8xnCxYsQPXq1REUFIT79+/LKcLiQSKRAACysrKQkZEhbr969Srq1asHc3NzZGZmitsPHTqE9+/f//I4f5VVq1Zh+vTpAIAPHz5g1KhRaNSoEUJDQ5GTkwPgf9cr+5+kpCQIggA3NzecP38eADBnzhyUK1cOL1++BMDHLb9NmzbB2NgYpUuXRkJCgsxnKSkp0NDQwKFDh+QUXdGxf/9+BAUFoU+fPnj9+rW4/cCBAyhXrhx8fX3Fe1xxFRkZidTUVPHvjIwMDB8+HBMnTgQA3L9/H/r6+vDz84O+vj5sbW1x4cKFYn9cfoXc3Fw4ODggMDAQ2dnZ4jYASE5OxpIlS8TnhiKLj4+HoaEhAGDHjh1QU1NDREQEgLzzNSYmho/T/8vMzETv3r0xY8YMAMDvv/8OHR0deHp6wsTEBA0bNsSbN28AgK/hn+Do0aOoVq0aqlSpgnPnzonbX79+jUWLFkFfXx9DhgyRY4S/xpkzZ+Dm5oajR4/KbD979izs7Oxga2tboK2iiKT395MnT0JLSwsrV64EADx48ACCIEBdXR3r16+XZ4hFkvRedvjwYUyYMAGdO3fGjh078Pz5c2RmZiIsLAzGxsYYNWqU+B1FeqfI/1ujo6MREhKCESNGyLwnxMbGwsbGBl5eXjhz5ow8wpQLadvh8+fPmDx5Mho1aoTBgwfj1atXsLOz++6xkLbXmOy5df/+fTg7O2Pz5s0AgD179qB8+fLw8PBA9erV0adPH9y6dUteoRYK0nvVq1ev0KZNGwQEBCAqKgqCIGD79u3ifqGhoVBWVubnAWTbqrm5uejevTvMzMxw7tw5eHp6onXr1mjUqBGsra3RsWNHvH37Vn7BfoOTNQro1q1bsLCwQN++fXH16lVxe3Z2NhwdHWUaIopIekE/fPgQANCnTx907doVAGRe5gcMGAANDQ307NkTd+7c+fWBFgPSY71nzx5069YNBgYGCA4OxsaNGwHkJWxMTExgbm6OixcvYvTo0dDV1cWTJ0/kGfZ/4uLFizh+/DhGjhyJpUuXitvfvXuH0aNHo1GjRhg3bhx3KP3A1atXoaqqijJlyiAgIADBwcG4efMmfHx80K1bN3z+/FneIcrNj14o9+3bB1NTU3To0AHHjx8Xt7948QJ16tTBrl27flWIRdaqVatQokQJ1KhRQ0wiS+9rBw4cQMWKFdGlS5di26mZkpKC9u3bywxayM7ORlxcHG7evIm3b9/C2toaffr0AZDXESIIAiwtLXH58mV5hV0kfe8ckkgkGDFiBBo0aIANGzbIXOuhoaGwsrKSSSIqgu8dp9OnT6NDhw6IioqCmpoafvvtN/Gzo0ePonfv3rh9+/avDLNQOn/+PL5+/Yq4uDikpKTg9evXMDc3R1BQECQSCdauXQtBEFC7dm0xYcP+nbt372LUqFEoV64cxo4dK/PZmzdvsGTJEpQpUwYLFy6UU4T/Hem1+vjxYxw4cAAmJibw8vLCiRMnZPZLSEiAuro6rKyssHv3bnmEKlfr169HZGSk+HdmZiYWLFiACRMmAAAePXqEmjVrol+/fhg8eDBUVFRkOu3YX7N9+3aUK1cOvXr1QmBgIKpWrQp3d3e8f/8eL1++RFhYGBo0aICBAwfKO1S5GTlyJLS0tNC7d2/Y2dmhSZMmmDVrlvh5bGwsbG1t0aZNG5k+puIsf5vj8+fPmDJlCmxtbdGzZ09oamqiffv28PT0RI8ePeDr64tu3bohJCSE3+chm7T6+PEjAGDv3r14+/Ytzp49i2rVqiE8PBwAEBQUhEqVKsHDw0OhB0pLB8fl5ORgwYIFMDAwQMmSJcW+o/zHVJqwkfarKbKjR49iz549APIGN+jr60NbWxseHh5iu2Lbtm0wNTUtVO1bTtYogMWLF2Po0KEYMmSIOENh3bp1MDAwQJcuXbBs2TJs2bIFLVq0gKmpKWf7AWzZsgU1a9bE3bt3MXHiRGhra4vJG2lnSHh4OPT09NC2bVs8e/ZMnuEWabt374aqqiqmTZuGdevWoWvXrtDU1ERycjIA4MaNG7C0tEStWrWgp6eHpKQkOUf8823btg3q6urQ0tKCiooK2rZtK/P5hw8fMG7cOBgYGGDy5MlyirJw+vDhA758+QIgb7ZIy5YtMWPGDIwcORKVKlVC586dYWVlJT6gFU3+ztsdO3ZgxYoVmDZtmjhqZO/evbCyskLjxo2xZMkSbNu2DR06dICxsTG/SPxA/hezjIwMbNiwAaVLl8bIkSML7BsfH49atWrh999//5Uh/lLScyk5OVmcmfv161cAwK5du2BlZSUOaNi7dy9cXFxgbm6Oe/fuySXeokh6zp05cwYzZszAzJkzceDAAQB5s1JdXV1hYWGBHj16YObMmfD29oa6ujouXbokz7B/ufzXZlRUlDjL8sWLF9DT04MgCJg/f764T1ZWFpydneHh4VFsE6p/1b59+6CmpoaDBw+K22JjY9G0aVOx/ZuQkABnZ2c4OTnxIKV/4NuBE9K/nz9/jtGjR0NfXx8zZ86U2Sc9PR3btm0rts/jrVu3QhAEPH/+HPHx8WjUqBG6desmk7A5deoUmjVrBm9vbzx69EiO0f5679+/h729Pezt7WU63FJSUpCUlISMjAzY29ujb9++yM3NxY0bN6CiogJBELB161Y5Rl603Lt3D/Xq1RNnKuXm5kJFRQVjxowR93n9+jXGjh2LRo0a4cWLF/IK9ZfKf89avnw5dHV1ceHCBQB571xKSkpo0KCBzLvpxo0b0adPH4WYeSRtNxw/fhybN29GTk4OPn/+jEmTJsHS0hJVqlSBn58fRo8ejUGDBiEwMBC+vr64du2anCOXv507d2Lv3r0AgODgYDg7O0MikeDTp08AgJCQEHh5eYnvE2PHjoW1tTX69++vEOfW92zYsAFWVlZiMuHy5cvQ0tKCrq4uBg0ahPT0dACyg8vHjRsHQRCwZcsWucRcGHz8+BG+vr7Q0NBAXFwcgLz+o/xVIYC8ZLSjo2OhquDDyZpiburUqdDU1ISbmxt0dHRQu3ZtcaTDrl270KNHD2hoaKBx48bo1KmTeEMsri8FfyR/OS5fX1/MmzdP/MzW1hYNGjRAWlqa2DE8atQoLFiwQLwxsr9O+pB9+/YtnJycxGP9/v17VK5c+bslH06fPo3nz5//0jh/hYyMDHTq1AmrV6/GzZs3MX36dBgaGooj0aXev3+PKVOmIC0tTT6BFkJnzpyBhYUFFi5ciFevXuH9+/cICgoSy9usXr0aDRs2hCAI8PDwUMj7mtSIESOgo6OD1q1bw9bWFhUqVMD+/fsB5M1sMzExQYkSJdCxY0eZGVyKfMy+JX1GZGZmyhyXzMxMREVFoWTJkjIv9lLSF4/iJv8xSEtLg5OTE1q3bi0zY2bhwoWoVauWOBtyzJgxmDBhAp9X/8D27duhpaUFR0dHdOzYEWpqaoiKigKQN5ozLCwMHTt2hLm5Odzd3Qu8hBR3+V/eU1JSYGtrCwsLC/F8vHr1KjQ1NeHi4oIVK1Zg48aNaNmyJUxMTMRBSoqasHn06BH69euHxYsXy2yfN28eNDQ0xL/HjBmDoKAghZ6p+k/lPz+XLl2KQYMGwdHREbGxsXj58iXevHmD0NBQGBoayoxUz6+43Tffv3+PcePGySRQExIS0LhxY3Tr1g179uyBRCLBuHHjMHz4cLx7906O0crP/fv34eLigpYtWyI6Olrms6tXr8Lc3FwsoXfv3j34+vpi3LhxuH79ujzCLZJu3boFS0tL5OTk4NatW6hRo4bMe5h0IMqrV68U4r3f09NTLHGWm5uL7OxshIWFISwsDEDe4C8NDQ3MnDkTPj4+qFatmlg6M7/i3KkubS/ExMRAQ0MDw4YNEwcxSEuiOTg4YPjw4Qrbtvgjbdq0gZqaGjp37gxNTU1cuXJF5vO+ffuiQ4cOYmLUzc0N27dvF49lcT63fuTixYvi4JlXr14hOzsbSUlJWLBgARo3boyAgABxNn3+9sK0adMU8nmQ/7q7dOkS+vTpg1q1ahWYoSutbFOuXLlCN8iNkzXF3KBBg3Ds2DEAeaOzHBwcUKtWLZkbYnp6Ot6+fSue0Io8s+bYsWMwMzNDmzZtZC7We/fuoUmTJqhcuTJatWqFNm3aoFSpUgp54/unVq9eXWDkeUZGBho2bIhz587h4cOHqF69Ovr27St+HhcXV+DhXZwcO3YMDg4O6Natm9iZ+fHjRyxevBgNGzZE7969Zfbnxp4siUQCX19ftGnTBtbW1rh27RoiIiJgY2MjrlNz5coVzJ07Fzdu3JBztPKzZs0aVKlSRbyn7du3D4IgYOfOneI+CQkJsLKyQkBAgFhfWREbwj8ivfb27duHjh07olWrVujWrZs4WzU7OxurVq1CyZIlMX78eHmG+svt2bMHERERiI6ORqtWreDq6ip2kD958gSVKlWCgYEBmjZtivLly+PixYvyDbgIkF570vPu9OnT0NbWxvLlywHkddCVLl0agiDIDCwB8pKH0oE3iiL/s3HKlClwc3ODhYUFlJWVYW1tLc7ITU5Ohp2dHQwNDWFnZ4cePXoo9CAlIG+9tw4dOqBhw4bi+4L0WKSlpUFfXx86Ojpo27YtypYtW6zbZL/CyJEjoa2tjXHjxiE4OBiampoYMGAAcnNz8fDhQ4wZMwbGxsYYN26cvEP9TyUlJaFGjRqwtrbGyZMnZa7h/fv3o127dqhUqRJMTEygoaFR6DpQfgWJRCK+k1+8eBFOTk5wcHCQGSF96NAhCIKAEydOIDMzE+PHj4eDgwOysrLkFXaRID3fpAMwT5w4AT09PVy5cgX6+vriTCUgrzykj4+Pwrzzf/jwQRwQkn+G28uXL/H7778jLS0NRkZGYtvj4sWLqFChAmrVqiW2URTlffXcuXOoUKECoqOjxXNJKisrC5MnT4atrS38/f3F9wVFOTZ/hb6+vkwJr/yWLFmCOnXqoFmzZmjYsCHq1atXYG1GRXX58mUYGBhgx44dAPLabDNmzICtrS369esnJmzCw8Nx5MgROUYqX9/OkLly5Qp69eqFWrVqiWvgPXz4EL169YKVlVWhLM/NyZpi6vz580hMTISnp6dMA/fDhw9wdHSErq7ud0ddKvoD5Pz58zA2NoaSkpI4zTf/MZk7dy6GDx+OAQMG8BTWvyErKwsBAQGwtLTElClTxO0vXryAvb09li5ditq1a8tMm3748CF69uyJnTt3FsvzUiKRYOvWrdDX14eWlpbYiAPyrtPFixfD0tIS7u7ucoyycJGeB58/fxZr2wJ5JTK8vb1Rrlw5zJ8/HzVr1kTXrl25Uff/wsLCMHToUADA5s2bUa5cOXH2Uf6RqjExMbCxsUGPHj1k1rBheXbu3Al1dXUMGzYMkZGRMDQ0RNOmTcUX+OzsbKxevRqCIGDq1Klyjva/ER8fLzZmpddjly5dsGTJEgB55S9atGgBV1dXsZRlWloaBg4ciLFjxypMZ8e/ERkZibVr14ov/l++fMGCBQswevRoAHnrO+jo6KBPnz6YMGECBEEQZ9goovz398WLF6Ns2bI4fPgwHj16hNWrV6NFixawsrISz8eMjAykp6fLvMQp8iClS5cuoWnTplBWVpaZ0SGRSJCTk4OLFy9i4MCBGDZsGLd7/6XExETo6emJ5+K5c+cgCAI2bNgg7vP06VMMGDAAXl5exbLtK3XmzBk4OTmhVKlSOHnyJADIzNi6c+cOdu/ejWXLlilsyUzp//9bt26Fj48PbGxsULp0adSvX1+mJJqXlxcEQYCpqSnKlSsnzgJhf+zkyZOwtrYW/3Z2doYgCPDx8ZHZb/To0bC1tS2W1R2+RyKRID09HT179oSqqqp4fUqT+Lt374aRkZE4yPDYsWPo0qULwsPDi/X71s2bNwtsW7lyJRwdHZGRkSEen/zH4MuXLxg9ejRatWqlMOfPX5GVlYV3796JJR4rV66M+Pj4Am2xiIgIjBgxAsOHDxc/U9SBNflduHAB3bp1g6mpqbg+WU5ODmbOnAk7Ozu0aNECAwYMgCAICttuS0lJQcOGDXHq1CmZ7VeuXIGHhwdq1KghDlB69OhRob0+OVlTDIWEhKB8+fKoXbs2BEHA6tWrZUZZfvjwAa1atYKqqqrCNoB/JDs7GxcuXIChoSFsbGzEF4dvR6kW5xeo/0p6ejpGjBiBRo0aYdKkSeL2yZMnQxAEdOjQQWb/0NBQGBsbi9M9i4v8587Hjx8RExODKlWqoGPHjjL7ffz4EbNmzYK9vT2ePn36q8MstHbv3o3WrVujZcuWMqUzAGDFihVwdnZG/fr1IQgCYmJi5BRl4eLn5wdfX18cOXIE6urqWLZsmfjZ9OnTZUp3xcXFoW7duujTpw+PzMzn5s2baNCggZiUePr0KWrVqgV1dXUYGBjIJGzWr19fLJMSz58/h56eHnr16iXT+Le3t8ecOXPEv6Vr4Lm6uoqdRsX5Bf5nkUgkkEgkaNKkCUxMTLBt2zaxDXL//n2cOnUKmZmZsLe3F8uzXL9+HWpqahAEQea6VgT5ZwZmZ2cjOzsbXl5eCAoKktkvPj4eFhYWsLa2/u6sEEVtz128eFHsbLt58yacnJzQuHFjbNu27bv7cwfJvxcfH4/mzZsDyEts538ef/jwQVxj6fnz5+J5WZzPzzNnzsDe3h7VqlXD48ePARR831J0p0+fhoqKClatWoXU1FRcvnwZtra2BdawWbduHaKjo3H37l05Rlu03LhxA7q6uli3bh0A4ODBg7C3t4e1tTUuXbqEhIQEhISEQF1dvVCOuP4v5O8sv3LlCtq0aYOKFSvi7Nmz4vb4+HgYGBggMjISz549Q4cOHTBo0CDxXlUcnxWbNm2Ctra2zEBBABg8eDAMDQ3Fv/O3da9evYrc3Fx8+fIFr169+mWxFlZ/9B7g7OwMLS0txMfHyzwDMjIyZPZT1IE132sHnD9/Hr6+vjA2NhYTNrm5uYiMjIS3tzdatWqlMPctqfzH6eTJk3BycoKNjY3M/QvI6+tQUlKCqqqqOMOmsOJkTTFz6NAhWFtbIyEhAUlJSWjbti20tbVx6NAhmRvc+/fvMWjQoGL5QP0rpJ0iAPDgwQNcvXoV9+/fF7clJydDT08PdnZ24kMj//Erzi9P/wXpAzo9PR3Dhg1Do0aNMGHCBPHzoKAgKCsrY+rUqZg0aRICAwOhrq5eLMvlvHv3DtnZ2WKD7+PHj9i2bRtq1aqFLl26yOz78eNHcRE5lvfSqqmpiX79+qFPnz5QVlZG//79ZRpzV65cwcKFC1GnTh2FS0b/qCF88OBBmJqaomTJkuKMGiDv/OrYsSOGDRsm8yzYu3cv7t+//5/HW5ScOXMG48ePR25uLp48eYLatWsjICAADx8+hL6+Puzt7RWiPFBycjKsra3Rp08fcXauk5MT1q9fL7Pfhg0b0KJFCzg6Oircy8I/JR3VlZ2djQ4dOsDMzAybN2+WSZreuHED5ubmYhLs0aNH8Pb2xsKFC4tlgvBHYmJiIAiCTJIQyKtx3rJlywJrqkgXWG3cuDGfj8grT9ikSRO0bdsWv//+OwAgNTUVrVu3RuvWrcUXf6B4drz9Ct97Hq9duxYNGjRAQkICypUrJ1P6JSYmBr169cKzZ8/EbcXlXUP6O54+fYqXL1/KDMI6e/YsHBwcULduXTFho6gdct8jLYucvwPzzp07sLa2hpGREbZu3SrH6Iq2d+/eoXPnzvD29gaQd97FxcXByckJ6urqMDY2RrNmzRSyBN+YMWNgZ2eHli1bolSpUlBXVxdLoj158gTdunVDrVq1UK1aNVhYWIjnZ3G5Z31P/rVCpPbv349atWrJtIFzc3ORkZGB3r17IzY29leHWSjlfx7GxsZizpw5WL16NY4ePSpub9euHbS1tREbG4vnz5+jffv28PLyAlC8z6s/I/3tZ8+excaNG8XkMpBXTvTbhI1U/ootiuTIkSPieXX48GF06tQJ5ubmYol3ALh27Ro6duyIkSNHiutMFVacrClG1qxZg+Dg4ALrgrRu3RrVqlXDwYMHv9sAVqQXsQ8fPgD4341v+/bt0NHRQe3atVGqVCn4+vqKF7g0YePg4MAjvf6l/A/Zly9fYujQobCxsZGZYTN16lTY2dmhcePG8PX1LZaLI+/duxdOTk6wtbWFs7OzODo9IyMD27Ztg46ODrp16ybnKAuX/OfOkSNHxMUtgbzjqaqqin79+hVYxF3RGin5G8Lx8fFYtmwZNm7ciGvXruHr16/o1asX6tevj/DwcHz8+BEXL15Eu3btYGFhwVPLv0N63uUvEyftDPfx8YGHhwc+f/6MnJwcsXSGpaVlgZrVxVFKSgosLCzg7++P1NRUeHh4IDExscB+S5cuRY8ePcQOOPZjq1atgru7u5iEyc7OhrOzM8zMzLBlyxbxvEpKSoIgCOIiq2PHjoW9vX2BuszF3dOnTzF9+nRxgWOp8PBwGBgYYNeuXTJJrg0bNqBz587o2rUr/Pz8CozWVEQRERFwdHREly5dxITNlStX0Lp1azg7O8uM2mf/3J49e8QZM1lZWbCxsYEgCAgPDxf3+fz5Mzp06IAePXoUu04p6e/ZvXs3GjVqBAMDA5ibm2PlypXiPmfOnEGLFi1gZGSEBw8eyCvUQkV63FauXAljY2NxDQLp++jZs2dRpkwZWFhYYNOmTXKLs6jIX0Y5v+PHj0NJSQm7du2S2Z6amopXr17h7du3vyrEQmP16tUoW7Yszpw5g/T0dJw/fx5du3ZFmTJlxBLJv//+O06ePIndu3eL7w6KkGS9cuUKypQpg7i4OAB5CZwOHTrA2dkZa9asAZCXzJk4cSKqVq1a6DuCf7WQkBBoaWnB3t4eurq6qFevnkx5fFdXV2hpacHQ0BCmpqbc//b/tm/fjrJly8LIyAjlypUTS+8BeSXRfH19YWpqis2bN8s5UvmSSCQwNDTEiBEjxG1HjhxB586dYWpqiqNHj+LTp08YP348vLy8isS7EydripHOnTtDEAQ4OTkV6DBycnJCzZo1sWfPHoXtkOvbty/8/f3FxsTx48dRtmxZLFmyBDdu3MDWrVvh4OCAdu3aiY2R5ORkaGpqwtnZWZ6hF1nSxvHr16+RlZUlvmy8evUKw4cPh5WVlUzC5vXr15BIJMWywzM2NhZly5bFpEmTEB0djY4dO6JSpUo4d+4cgLyEzfbt26Gurl6gXrKikp4/586dw8aNG+Hh4SHTqAPyEjYqKioYOHBggYSNIsg/SxDIW7y4Zs2acHJygp2dHerVq4eEhAQ8efIEPXv2RO3ataGmpgZzc3OZRLSiPhe+R3o8ExIS4OnpKbPA6pcvX2Bvb4/FixeL2wYMGIATJ07g0aNHvzxWeUlJSYGVlRV8fX2hpqYGfX19tGrVCq1bt0bz5s3RqlUr9OvXT2aUOPux8PBwmJqaIiAg4IcJG2nyYdCgQRAEASYmJihfvnyxnIH6R6SJ6Y8fP2L+/PkFSju2a9cOdevWxfr16/Hw4UO8e/cOLi4umDlzJubNm4fKlSsr1LWa37ezPVatWgU7OzuZhE1qaipsbGzQpUsXcYAT++vyH+PU1FSUKVMG/v7+4szLHTt2oGHDhmjRogVOnTqFzZs3o23btjAxMRHfT4pbwiYuLg5ly5bFggULcPz4cYwePRqCIMg8R8+dOwcLCwtYWloiJyen2B2Dv+J7vzklJQUlS5bE7NmzZbafPn0aTZs2Rbdu3RT2fvZ3HTx4EN7e3gXWeOvVqxd8fX3x7t078fpVxPNPasKECQVKkz9+/BjOzs7Q0NAoUFIIUKx3CA8PD2hqamLv3r0A8tZ98/LyQs2aNVGjRg1YWVlBW1ub1476xs6dO1GlShVxDaT79+9j6tSpqFmzpsz9bfv27di2bZtCJQG/J3+CuVOnTli7di1evnyJs2fPom7dumjUqJE4oDA5ORldunRB48aN8fHjR4W+f/Xo0QODBg2S2XbixAl0795dZm23ojJjkpM1xcCGDRuwdu1aAED//v1RtWpVREVFFei4tLCwgIuLizxClLtNmzZBS0tLplMjLCwMrVu3ltnv6NGjaNq0KQIDAwFAXFyVR0b8fdIHxa5du9C0aVM0aNAA5ubm4kKqb9++xfDhw2FjY4PJkyfLM9T/3IMHD9C0aVPxxVS6QHTVqlWhpqaG06dPA8jrfNq1axefb/ns3r0bgiDAwsICgiDA3t6+QE3uffv2QRAEDBs2TE5Ryse3MxbWr1+PatWqiefTokWLULp0aXGkzYcPH/DkyRPs3r1brKUMKG5D+I/ExMSgTJkymD59Oi5cuADgf/c0W1tb2NraIjExEcHBwdDW1lbI2SPJyclo0KABGjZsiO7du2PNmjVYtGgRJk6ciGnTpinsopZ/x5EjR8T/vnbtWlhYWKB3794/TNjk5OQgOzsbe/bsQXR0tMKVK8z/Arp8+XIEBwejTJkyBUqiubm5oUGDBqhQoQKMjIxgYGAAIO+crV27tsIdNyBv9kL//v0LjCSMioqCpaUlunXrJpbiu3btWrFbL/BXyH9+TpgwAaNHj0b16tWhrKyMbt264datW8jNzcWePXtgb2+PihUrwsbGBh4eHsV24MTjx4/h5OSEhQsXAsibFaenpwcrKysIgoB58+aJ+yYlJSnszJr8g5MiIyOxa9cuvHz5EgCwZMkSlCxZEjNmzMDjx4+RkZGBcePGISAgoEiMDC4sDh48iPbt26N27dpo1qwZYmJi8PHjR8THx6NKlSriu5eir7EXFhYGbW1tcRaS9NyMjo6GIAgQBKHIdHT+LJcuXZKp+OHn54eyZcsiPj4eAPDs2TMkJycjLCwMW7ZsQVpampwiLTy+XXdt9uzZaNSokcw+T58+xfDhw+Hg4PDdwV3F7Xn4Z27cuCHzd2JiIlq1agUPDw+Z0u43btyAgYGBTMLm4sWL4qAbRfPixQuxDTVv3jxYWFgUmEX57t07xMfHY+PGjUXq+uRkTRF39epVmJubo2HDhti9ezcAoGfPnqhXrx7Wrl1boBSQojZAZs+ejXr16gHIy+wvWLAA06dPh62tLb58+SLzgrVmzRqoqqryou4/QUJCAkqVKoWZM2di8eLFGDp0KARBEGfTvHr1CiEhITAwMMCsWbPkHO1/Iy4uDsOGDcOYMWOQmZmJx48fw8DAAH369MH9+/dhZWWFqlWriqP3FXk0hFT++uZdu3bFqlWr8OrVKyQmJkJFRQXe3t4FRhIePHiwQCOnOOvfv784zVd6Xx89ejT8/f0BQJyl9dtvvwHIS9TcunWrwL+jqM+EP3Lt2jXUrFkTK1askNkuLYN2/fp11K9fH3p6ejAwMFDo0XMXL14U17ApSo3fwmDLli1wdHQUO8gBIDIy8ocJG1NTU8TExMiU91JUY8aMgZaWFtatW4fly5fD09MTampqMmUyT5w4gfXr12Pr1q3iC/+AAQNgbW2tkKVtwsLCUL9+fQQHBxeYMTN8+HCoqKjAyclJYV/2f6a5c+dCQ0MDJ06cwMWLF7F161ZoamrCy8sLt2/fFve7c+eOzCjY4jhwIj09HZMmTcLTp0/x9OlTGBkZISAgAO/evYOPjw8EQZApZajIYmJiUL58edSpUwe1a9dGy5YtxaRpREQEVFRUULt2bRgYGEBDQ0Oh2x5/Rf73KekzIDMzE3fu3IGLiwusra3RoEEDHD58GAYGBujatatCdQ7/qP1/4cIFmJubY8yYMTLrph4+fBi9e/fGnDlziuW96nskEgnev3+PSpUqoV27drh69ar4mTRhI51hw75PmnRes2YNDAwMCgxI3b9/P5SVlRVi3c8/snv3bmhpacm0zw4fPoxq1apBXV1dfBZIr9ubN2/CxMQEBgYGMiW7Fc3x48dRt25d1K5dG927d4ejoyMaNWqECxcuFIv2LCdrirCQkBC4ubmhSZMmqFChAvT19cXFpXx8fGBkZIT169cXmGGjiJ1z58+fh6GhIVq0aAFBELBz505s2bIFJUuWlFncDMibWm5kZMTTyv+F3Nxc5OTkwNPTEwEBATKfrVq1CoIgYNu2bQDysuHjxo0rlh19Fy5cQMWKFbF161ZxRERQUBA6d+4sJlK9vb2hpKSEatWqITMzk5M1/+/YsWPw8vJC69atZUZBnz59GqVLl1b4tTB27twpjiJJT08HkJesCQsLw4EDB6CmpiYmanJzc7Fu3TosXLhQIUvF/V0JCQkwNDQEkDf9fMWKFXB0dES5cuXEhWhzc3Nx69YtsbSjIktJSYG1tTU8PDwUapH7f+vevXtiOyP/iLn8CRvpbODs7Gx07NgROjo62LFjhzzCLTRevnwJGxsbmVI2jx8/xoQJE6CqqooFCxYU+M7JkycREBCAihUrKtyI4AcPHiAzMxM5OTmYNWsWGjdujAEDBsi83G/ZsgWWlpbw8PDgtu9P0LlzZ3GGvtS+ffugqqoKDw8PJCcnF/hOcW77STt8J0+eDGdnZ/HvCRMmQFdXF5UqVcKrV6+K9TH4kfzlonv16oU1a9aIZZFbtWoFc3NzcbZRamoqtm3bhrVr1yrk7MC/Q3pcDx8+jLFjx8Ld3R0xMTEyg5bOnz+P4OBg6OjooGTJkjAyMlKYTs/819r69esxffp0REVFicmqCRMmwNbWFv369cPt27dx+/ZttG/fHn5+fuL3FCVhA+StEVW9enV07dq1wAwbTU3NAmsesTzr169Hz549kZubi1OnTqFWrVqYNGkSXrx4Ie5z7do1mJqaKnSyZtGiRbh9+7aYXHj16hWAvHfNo0ePolq1ajKlCaXX77Vr12BjY6PQz4OnT58iPj4es2bNQmhoKBwdHSEIAho3bozy5cvD0dER7du3x7JlywqUji8KOFlTRK1evRoaGhpITk7Gmzdv8OzZMzg5OcHKygo7d+4EAPj6+kJTUxP79u2Tc7SFQ//+/cWLV6p79+6oWLEiEhMTxQZaSEgITExMuBPuH5DeAKUP4caNGyMkJARA3qgmaSMwKCgI9vb24uiB4phAvHPnDiZMmIBRo0YBgLgWT/PmzTFt2jRxv379+mHnzp0yDReWVx5IS0sLysrK4qxBqTNnzkBNTQ0dO3bEkydP5BShfHzbyFizZg3atGmDR48eYceOHRAEAcrKyoiOjhb3ef/+PVq1aoXRo0f/6nCLBOkxlT4Dbty4gdq1a6Njx44wMzODq6srhgwZggMHDkAQBF7M9zvOnz+P5s2b84zUv2D9+vUypX5SU1NhbW2NGTNmiNu+l7D5+vUrunXrJpPYUUSvX7+GlpZWgTUcHj58CGtrawiCUGBtswMHDqB169YK1xkQGxuLBg0aYOXKlcjKysLXr18RFhYmdsJJ73ljx47F+PHjFXLG0c8kkUiQk5ODdu3aoVevXgDyrltpp+bkyZOhqqqKgICAYlXuVvoMlbbx09LScOHCBTx79kwcIPL161e4ubnB3d1d/N6QIUOwcuVKhV8bSfr8dHJykul0O3ToEFq2bAkzMzOF7oz7p7Zv3w5VVVW4ubnBwcEB1atXR7du3WTKjwJ5pefmz5+vMLPz879HjB07FqqqqnBwcIAgCOjcuTPS0tIgkUgwa9Ys2NraQhAE1K1bV2bB96LW4fl3SH+bdP1c6d9JSUmoUqUK3NzcZGbYuLm5oWbNmuKC7+x/pk2bBm1tbfHYLF68GOrq6hg+fDji4uKQmpoKJycn2NraFsu+oL9i3LhxqFChgjjr9vr16yhdurRM38eRI0dQuXJluLq6ituk56X0mlQU+Wcif/z4scDnT548QbVq1bBs2TLs2rULCxcuROfOnXHz5s1fHepPwcmaImrs2LGws7NDbm6ueHN78uQJGjVqBF1dXTFhM3XqVIW7iL8nMzMTLVq0QJ8+fWBsbAwvLy8AeS8WPj4+KF26NExMTGBra4sKFSrw1PJ/YcuWLahVqxY+ffqE4cOHw8DAQOxQl77ITZ48GU2bNpVnmP+p9+/fw8rKClpaWhg6dKjMZz179kS1atWwfft29O/fH9WqVVP4lzBpBweQN0tEWoP7zp070NfXh4uLi7huiNTx48dRpUqVYjHF9d9YtmwZbG1t0b17dzx//hzTpk1DyZIlceDAAdy5cwe3bt2Ck5MTLC0tFWoU3F8lbfTt27cPgYGBOHv2LLKzs7F582Z0794doaGhuHnzpjgap3nz5lzy4Ae4PNefu3nzJszMzNCsWTPx3nX37l14e3vDzs5OZv0GacImMDAQ58+fl1fIcvW9DqGcnBz06dMHXbt2lSkpBQABAQFo1KgRnJ2dC3xX0WYV7t27F6qqqli4cKHM+jPZ2dniDJvKlSvD2dkZqqqqCtNR+TP9qMMyPDwcSkpKOHfuHID/DUiaP38+nJ2dUbFiRYwdO/YP/42iIioqChs3bhQ7Nrds2YLq1atDS0sLhoaG6NKli5icXrRoEUqWLImRI0fC19cXFStW/G55VkUjXa+sQoUKYskgqcTERLRp0wa6uro86+1vePToEYyNjbFs2TJx265du9CuXTt4eHjg/v37MteeInYU37lzB23atEFSUhKAvFH6VatWRfv27cW1Qb9+/YqDBw/i9OnTCrXg+/79+xEQECAOQJKeKxcuXED58uXRuXNnmcEfPFDp+2UHgbw1swcPHiz+vXLlSjRp0gRqamowMTFB06ZNxb5KRbsOX7x4gQYNGiAiIgJAXqImPT0dPj4+0NTUREJCgrivNGHj5uYmr3DlTnqOxcfHw9PTE0ZGRhgxYgRiYmIA5J13mZmZsLa2LjYDKzlZU8RIT9IpU6bAyspK7ByR3uQOHz6MMmXKwN7eHnv27BG/p0g1WH9E+qK+atUqGBoaiuVsAGDbtm1YvHgxFi5cWGDxcvbnpOflkydP4OrqiqVLlwLI61B3cHCAp6enTKf6wIED0a5dO3z69KnIv6j+SEpKCurWrQszMzNcvnxZ3J6amgoXFxfo6OjA3NxcoROD8fHxMiVptm/fjkaNGkFfXx8dO3bE3r17cf/+fejr66Nr164FEjbcOZwnOjoadnZ2cHd3x4kTJzBs2DCULVsWWlpasLS0hL29fbFdvPifyn/fiYmJQZkyZTBjxgxxFsP3TJgwATVr1uSFt9k/JpFIsHXrVjg4OMDR0VE8l+7du4eAgAA0btxYJmETFRUFPT09BAcH4/Pnz8X2efk9+V/anz9/LtNRuWvXLhgYGGDEiBHiaLkPHz6gU6dOWLt2rbifIh0vKYlEgszMTLRr1w4jR46U+Sz/c+DMmTMYM2YMRo4cyYmafyD/+fn06VOZxGFubi48PT1Rvnx5HDlyBB8+fMCnT5/g4uKCuLg4LF++HMrKykW+lGtOTg6sra1hZmaGnTt34tKlS6hbty4WL16My5cvIyIiAi1btkSDBg3w6NEjZGdnY/LkyTAzM0ObNm0UriThj2RnZ2PLli0wMDBAy5YtxdK2UgkJCejUqZPCD+z6M/nv948fP0aNGjUKDK7ZuXMntLW1ceDAgV8dXqEyY8YMODo6wtXVVRwgBwBXrlxBtWrV0LFjx+/ORFWUd4g9e/ZAEAT069dPXPhees/funUrSpUqhc6dO+PatWvyDLPQy87OxsSJE9GqVSuZGZQvXrzAjRs3cPnyZfG4KkIS8Ftv3rxB69atMXToUCxatAi6urrirC1/f3+oqanJJGyOHj0KJSUl9OjRQ14hy430/r5r1y6UKVMG48ePx7p16+Dg4IC6devKlJft2LEj+vbtW+C7RREna4qoK1euQElJSVyoXWrfvn1wc3NDixYt0KpVK3z+/FlOERZeHz9+RFRUFAwNDcUZNuzfS0pKgqenJ1q3bi2TmFm9ejUcHBygo6MDf39/dOrUCWpqajIJjOLq8uXLMDU1RZ8+fWRq3EokEjx8+FChS448f/4cenp66NWrF+7du4dr165BXV0d06ZNw8yZMxEUFISSJUsiOjoa9+7dg76+Pry8vHD27Fnx3yjKD9+fIf/vj4qKgoODA9zd3ZGeno6bN29i//79OHv2rEI3hL/1bbmVy5cvo3r16li1apXM9vwlavbs2QNfX19UrlxZoZOr7N/J38mxefNmtG3bFk5OTuKIzLt37343YbNu3TqF6qT7tqb0hAkTYGpqCm1tbZiammL9+vUA8srJmZiYwMLCAh07doSlpSUaNmwoHmdFfj5kZWXB2NgYK1asAFCwgy1/Z7CijWT9GfIfswkTJsDCwgJqampwdXXFtm3bIJFI8OzZM/j7+6NkyZIwNjaGnp4eDA0N8fXrV+zduxd169aVWby7qJFeX5mZmXB2dkaTJk0we/Zs+Pn5yZxvJ06cgIODA7y9vcVk4cePHxVuppuU9Lg9evQIDx8+FJPNEokEW7Zsga2tLdq1a1fg3FDU4/V37dixA5GRkbh8+TL09PSwefNmALKlgiwtLTFo0CB5hSgX397n9+/fDyUlJWhpaYkJB+m5mZqailq1asHOzq5YlWv8kW+rO0jLg549exZKSkro27evmLAB8sqLNm3aFHXr1lW4Utx/Jjw8HE2bNsXRo0fx/PlzAMD9+/ehrq6ORYsW/fB7itwO2bJlC3R0dKCkpITp06eL2yUSyXcTNidOnFCYGanx8fFif6FEIsHLly/RvHlzcW3KzMxMmSo20nuYv78/XF1di8V7ACdrirDVq1dDWVkZI0aMwIULF3Dv3j20b98eYWFhuH79OgRBwMGDB+UdZqGUkZGBqKgomJiYoGPHjvIOp1iYO3cu9PX1Ubly5QKjws6dO4cJEybAxcUF/fv3V6iRKCkpKbCwsECfPn1katwyIDk5GVZWVhgwYADGjh0rrm8E5JWSW7JkCZSVlXHo0CFcuXIFGhoa6N27Nyeh8/k2YWNnZwcPD48C61oockNYasiQIRg8eLBMR1JcXBzq168PIO9lfvXq1WjZsiWqVauGnj17AgA2btyIQYMG4fr163KJmxUP0ms1MTER/v7+sLS0hCAIcHJyEmeNSGfY2NnZYerUqfIMV66kxyosLAwVK1bE+vXrcfDgQXh5ecHY2Fhcr+bUqVNYvHgxevTogdGjR/MMwnzq168Pf39/8W/pMbl16xZ+++03cQFb9s9NnDgRVapUwdatW3H37l1YWVnB3NwcK1euFJ+58fHxWL58OSIjI8UBE4MHD0bTpk2L/GLm0t8jLTVdunRpNGzYsMDAkLlz58LQ0FDh1wKV3te2b98OAwMD6Ovro3z58ujXr584y3Lz5s2wtbWFi4tLgXcp9n3S43r9+nWUKFECUVFRAIDevXtDS0tLpmMzOzsbjo6OMgMiFMmFCxfEgYKnTp2CsrIyfHx8xEGW0mOZkpICV1fXYv3u8KPqDnp6eujYsSMOHjwoDo4OCAgQB12OHz8eS5YsQWZmprxCL3QkEgk+f/6MuLg4ODo6wsLCAhYWFti0aRNev36NRYsWwcXFhZNb+UivtePHj0MQBFSvXh3jx4+XeX+XJmw0NTWxa9cueYUqF/kH9UrfvzMyMmBpaYmbN2/i/v37qF69uswMmn379uHx48c4depUselr5GRNERcTE4PKlSujRo0aqF69OszNzZGVlYUHDx6gbt26CjF74Z/KyMjAsmXLYGNjo/DrXvwbZ8+exdGjRyGRSLBo0SLUqlULnp6e3BGQT0pKCmxsbODp6cnlRr6RnJwMGxsb6OjoYMCAATKfvXv3Dn5+fvD09ASQ92KhCKO8/q5vEzb29vZiTW72PwcPHhRnxkgTfqdPn0a9evXQvXt3WFpawsXFBf369cPWrVshCAISEhKQnZ3NJffYT3Hw4EEIgoAFCxZg//79GDt2LMzNzeHo6CiTsOnevTtat26tUJ2bY8eOxeLFi8W/09PT0bhxY7GsqtSIESOgp6eHkydPfvffUdQZhDdv3kRSUhKOHj0KIG8hXxMTkwKdkiEhIWjUqFGRntVRGJw+fRpmZmZITEwEkNfhoqqqCgsLCxgbGyMyMrJA0vDevXsIDAyEpqZmkX8/k7Y7pOdRZmYmOnXqBE1NTURGRsrMBDl16hRq1KjBAx6QV8ZGVVUVEREROHLkCHbs2IFKlSqhc+fOePLkCXJzc7Fx40YYGxvD3d29WHeW/0ynTp1CXFycuBYUkDeDS7pGVGRkJDZv3oxRo0ZBQ0NDYUam5xcXFwcdHR0sXrxYLH12+PBhlCxZEn5+fgUSNlLF8Rz8K9UdlJSUsGHDBqSmpkJbWxt16tSBmZkZNDQ0uIQj/vi8OHLkCEaPHo1q1aqhbdu2sLCwgIGBgVgdozieU//Uq1evsH//fixbtgyGhoYYOXKkzPu7RCJBt27dUKNGDWRkZMgx0l8vOTkZ1tbWYoUa6azx3377DXXq1EGfPn3EdlZaWho8PT2L3bqynKwpBp48eYIzZ87g+PHj4s1v9OjRqFevnsy0TVbQp0+fivzINnmRjqJo1KiRWE4uNzcXc+bMga2tLQIDA8WXOEXtPMnv/PnzaN68OS9C+B2XL1+Grq4u6tWrV2DNkDFjxsDU1JQ7y/9E/per6OhoNGvWDKNGjVK4dS5+JP+Lwd69exEQEIBXr17hy5cvWLp0Kbp164YRI0aII+c+fPiApk2bih1xjP0b0jIbAwcOFJPPUps2bYKpqalMSbS0tDSFar+9ffsWDg4OaNasmTgqOjs7G0ZGRuLCq/lnVDZu3Bju7u4AFLvcmVRsbCx0dXVhZGQEVVVVDBgwAEeOHMGAAQNgYmICT09PTJs2DT4+PihXrhx3NP0D355nT58+xYoVK5CdnY1Dhw6hUqVKiIqKQk5OjtipN3v2bPHZ8/79e2zevBmurq5FPlEjde7cObi7u4sdcJmZmXBycoK5uTmWL1+OT58+ISMjA8OGDUOdOnV4pgjy2rTt2rWT2Xbx4kVUqFABQ4YMAZB379u2bRvS0tLkEGHR8+nTJ1hZWUEQBHTp0kXms8zMTPTr1w/GxsaoU6cOGjVqpNDlbH18fGBpaYnw8HCx/+PIkSMoVaoU/P39FWpNxj+r7rB48WIoKysjMTER9+7dw5IlSzB9+nSFTPR9K/871apVqxAUFITBgwdj+fLlMvulpKQgKipKvD5btmyp8DOSpG2J169fF+gTmj17tpiwyX//l0gkCtt/JK1Q07t3bzx9+hTh4eEQBKHAc3TMmDEwMTGRWd+yOOBkTTFz9epV+Pj4oGLFin+4UDJjP8vevXuhoaGB/fv3A8h7gM+ePRu2trbo378/v5zlwwmHH7ty5QoaNGgAPz8/mY6kgIAAtGrVSuFGk/wT+TuTQkJCYGdnhy9fvsgxosJJunBoYGCguIbNt6O8JkyYAF1d3WLX6GPy1b9/fzRq1KjAiPuQkBAIggBra2uFO+ek960XL16ga9euaNGiBSIjIwEA7du3h729vbiv9H7Wr18/hVxg9Xv2798PDQ0NLF++HF++fMHevXvF+9vRo0exZs0aNG/eHE2aNEG3bt1k1s9jf9/27dtx6tQpAHmzSrKzs+Hm5obQ0FDxuu7YsSNq1aqF4OBgmedyRkYGPn78KJe4/wvr16+HmZkZvL29kZSUBCCv49zJyQnq6uowNjaGl5cXTExMZBb/VVQSiQS9evWCk5MTgLx2h/Setm7dOlSuXBkPHjyQZ4hFVmpqKtq3b49q1aqJnZz523VPnjzBy5cvFWat0Pz3nW8TzX5+fjAzM0N4eLg4w+bo0aMQBAHTpk37pXHK29+p7sAKGjFiBLS0tODl5YV27dpBWVkZvXr1KjBI9/Pnz1i4cCFsbGy4wgjy1tZq3LgxdHR0EBISIj4/AWDOnDkwNDREaGgo7t69K8coC4+UlBSYmZmhT58+OHToEEJCQqCkpITZs2dj9uzZ6NevH9TV1Ytl3zcna4qR7OxspKSkYPjw4bw2BvtPfNv4y83NRXp6Ojp37owRI0aIL6q5ubmYO3cujIyMMHToUJ7uyv6SlJQUmJiYQF9fH35+fggMDOTE898kvUYnTZoEfX19njmI/x2T9PR0MTlz9OhRKCkpoU+fPjIzGOLi4tC3b19UqlRJoUdfsp9L+gxcuXIlzMzMcOjQIZkFj7dt2wYbGxt4eXkpXGdd/sTV6dOn0bx5c1hbWyMmJgYpKSnQ0dERZ9FI923SpAmCg4PlEm9h8v79ewQEBGDy5MkA8hbyrV27Ntzc3FCuXDl4eHjIjM7Mf86xv0cikeDJkyeoV6+eTKmlr1+/ws7ODqGhoeI2Hx8f7Nu3T7zui3MbeNOmTbCzs4OnpyfOnz8PIG82Q9euXSEIAn777TeFHBGcf9Hy169fi2XhduzYgdKlS4trykrPjdjYWBgZGSlU6ct/6kfX040bN2BtbY169eqJx1F6z1PUGZirVq3Cxo0bC9z7fX19oa+vj4iICDFhk5KSopCVMP6sukPDhg352fn/8l97J0+ehLa2No4dOwYgrx/ywIED0NDQQP/+/cX9pPfBr1+/QldXFxMnTvylMRcG+e8/SUlJ0NLSwvjx4xEWFgYdHR107txZZp3xefPmQUtLCxMnTlTIa/J7UlJSYGlpicDAQBw4cABLlixB/fr1xQo/xXUgEidriiF+oLD/UlJSEo4cOSKzbf78+dDU1JRZOC43NxeLFy/mafzsb7ly5Qrq1KmDmjVrYsaMGQrXcfkzSCQSbN26lUvd5BMbG4umTZuiTp06GDduHNLT03HmzBlx4dBnz54hJycHERERCAgI4Nr67F/Jv55D/nKrmZmZsLGxgY2NDfbv3y/Othw1ahQGDBig0MnVYcOGwdXVFTY2NlBXV0e9evXw22+/YceOHdDV1YWhoSGcnZ3RuHFjGBkZ8Qss8mYaSRe3f/36NczNzdG7d28AwMaNGyEIAtq0aSOOzlTUDst/6nudwuvWrUPJkiVx+vRpAHnrYri5ucHBwQGDBw+Go6MjGjRoUGwTNTdu3CiwHt6GDRvEtfKknZ2fPn2Ci4uLws0U/HbR8h07dqBp06aoW7cuJkyYgISEBAwePBj16tXDgQMHxP1Gjx4NS0tLXkvqB3777TfMmjVL/PtH19XNmzdhZWUlk7ApbtfgH8n/W3Nzc9G4cWM0bNgQsbGxBfqHLC0tYWJighkzZsjM+FPEZytXd/hz+dsP2dnZiIuLg56eXoFjExMTA01NTXEGKvC/hE3Xrl0RGhqqMNfk5s2bZWYS3b17F3PmzMHUqVPFbUlJSbC0tESnTp1kEjaLFy/mmTXfkJYu7NOnD54+fSqek8W5cg0naxhjf9mLFy/g5uYGQRAwePBgxMbGip+1bt0avXv3xtevX7lDgP0rFy5cQOvWrfHy5Ut5h8KKgeTkZJQvXx5TpkzB4MGDYWZmBldXVzx8+FBM2AQGBuLdu3fIzc2VWRiZsb9L+vzbs2cPnJycYGJigm7dumHXrl0A8kohSTtQjI2N4eTkBBUVFVy7dk2eYcvVmjVroKmpieTkZKSnp+P3339Hq1at0KxZM0RHR+PJkycYN24cgoODMWHCBLEzSRE7lb4lfUldt24dbG1t8fjxYwB5Mx4cHBygo6OjUOsQ/BfWrl2LHTt2iOsm+fv7o0WLFuJxffDgATw8PNC2bVu4ubmJnaLFrUPq8ePHMDExQUBAQIGBWNJr2MvLS1zDRtHkX7T87t27uHHjBjQ0NDB16lQMHjwYlpaW8PT0xPz58zF06FAoKyujUaNGsLOzg4aGBs/m/YG3b98iMDAQtWvXRnh4uLj9jxI2jRs3RpUqVRQ2+bVx40a8evVKLEtoaWmJ7du3y5RG9vX1Rc2aNREQEMDv7eDqDn/k8OHDWL9+PQAgMDAQQ4cOxcWLF1G2bFmxDL7U7du3oa2tjfj4eJntBw4cQIkSJYrtDIhvPX78GHZ2duKAhTdv3qB69epQVVXFoEGDZPY9d+4cLCws0LVrV+zdu1ce4RYZKSkpsLa2hoeHh1hJqjjfvwQAIMYY+4uysrIoMTGR5s2bR+np6VSlShWaOnUq7dmzh65du0ZLly6l6tWryztMVsR9/vyZVFRU5B0GK+Lu3btHmzZtIkEQaOzYsUREFB8fT3PnziV1dXUKDw+nZ8+eka2tLQ0aNIgWLFhAJUqUkHPUrKjbvXs3eXl50bhx46hGjRp0+PBh2rlzJy1fvpzc3d0pKyuLdu7cSVevXqUSJUpQjx49qF69evIOW24mTpxIiYmJdPz4cRIEgQRBoCdPnlCXLl3o7du3NGvWLOrSpYvMd3Jzc0lJSUlOERc+U6dOpa1bt9Lx48dJU1OTQkNDqXr16hQYGEjKysryDq/Iun79OpmYmFDNmjXJ2tqali9fTlevXqVZs2ZR165dycfHh5SVlenr169UsmRJ8fmRk5NDJUuWlHP0/x4AEgSBrly5Qrq6urRq1SratGkTNWnShAYPHkx6enrivvb29nT79m1ycXGhJUuWUOnSpUkQBDlG/+ulpKRQYGAgNW7cmKpUqUJEROPGjSMiori4OFq8eDFpamqSt7c3lS9fnhISEqhChQrUuXNnqlu3rjxDL9Tu3r1Lv/32GyUkJFBAQAANHjyYiIgkEsl322zXrl2jQYMG0cqVK6l27dq/Oly5AUBv3rwhbW1tmjlzJg0fPpyysrLIxcWF3r17R6NGjaJ27dpRmTJlqFevXuTv709NmzalEiVKiNe6IktNTaUuXbrQly9fqH///uTl5UU6OjryDkuuPn78SG5ubvT161cqV64cHTt2jI4fP056enrk4+NDJUuWpOHDh1OTJk2IiOj169fk4OBAYWFh5OLiIvNvPX78mGrWrCmPnyEXWVlZpKqqSqmpqVSjRg26desWeXh4UK1atWjJkiVkZmYm7nvhwgVyd3enJk2a0IoVK6hMmTLyC7yQS0pKohEjRtCmTZuoatWq8g7nP8XJGsbYD0kbbpcvX6abN2/S169fycHBgWrWrEkvX76kBw8e0IgRI4iIKDMzk5KTk2nu3Lk0bNgwOUfOGFN0Hz58oJYtW9KjR4/I39+fZsyYIX62Z88emjt3LmlqatKCBQsoPT2dypYtS0ZGRnKMmBUHd+/eJS8vL/L396d+/frRy5cvydLSktTV1enx48cUGRlJHh4e4v6K3EEi/e0zZ86k7du30/Hjx0lVVZWys7NJWVmZEhMTydXVlXR0dGj69Onk6uqq0Mfrj1y8eJFsbW3JysqKVFRUKCkpiU6cOEGmpqbyDq1I+bbz99WrVzR+/Hh68+YNlShRgi5cuEBTpkyhyMhI+vLlCx06dIhUVVVlkofF5RyV/o6dO3dSYGAgDRw4kMaPH0/z58+n9evXU7NmzWjIkCGkq6tLnz9/puDgYNLV1aWePXtSjRo15B2+3KSkpFC/fv3oxYsX5OnpSTNnzhQ/i4uLowULFpCmpiaNHz9eprOOFSSRSIiIqESJEnT27FnasmULbd26laZNm0a9evUS9/lewkb6HFEk0mt2+vTptHPnTtq4cSPVqVOHsrKyyN3dnZ48eUIqKiokCAK9e/eOUlNTSUlJ6YfHUBElJydTaGgobdiwgbS0tOQdTqHw5s0batKkCd2+fZtmzJhBo0aNIqK8gUkLFy4kiURCXbp0IV1dXQoPD6fXr1/T+fPnxWeiIg+u+fDhA9nZ2ZGJiQmFh4fT7du3yd3dnVq2bEnDhg2jBg0aiPumpKSQpqamzCAI9n0KM6hXHtN5GGNFR0xMDGrWrAlra2s0a9YMysrK2LNnj8w+O3bsQGhoKNTU1HDlyhU5RcoYY7JSUlJgYGCApk2bitOlpeLj49GwYUN4enpyOSX2r0in4H/58gWvX7/GoEGDkJ6ejsePH8PAwAABAQG4desW7O3toaamhk2bNsk54sLl6tWrKFmyJCZNmiSzPT4+Hi4uLhgzZkyxKyn1Xzh9+jS8vb0xYMCAAvc79vfExcWJdfYTExOhq6uL27dvY/Pmzejbty9cXV0hCAL69Okj50j/W3v27IGqqipWrlwps/7M0qVLYWNjAw8PD6xevRqjRo2CsbEx0tPT5Rht4XH58mXo6en9sO1hZmaGHj164NOnT8W6hMu/JT0227dvR+vWrdGmTRuoqKigatWqWLp0qbifoj4fvj13pH8fPXoU9erVw759+8TPPn/+jMWLF2Pw4MEYNmyY2O5V1GP3R4rzGhj/xNu3b9GuXTs0a9YMrVu3xtq1a8XPEhISMHDgQJQvXx7W1tZo27atWApU+gxVdElJSbCysoK/vz/evHmDkydPombNmvDz81OYsnDsn+GZNYyxH7pw4QK1adOGZs6cSX379qXbt29TvXr1aMqUKTRu3LgCIyUyMjJITU1NjhEzxpisK1eukK+vL9nY2FBwcDDVr19f/OzAgQNkaGio8GUO2D+H/x/JeujQIYqPj6fg4GCqVKkSqaur09ChQ+nx48cUHR1NampqFBgYSLGxsWJZBHV19WIxAv9niI6OFsvbuLu7U4UKFSg4OJhMTU3FWXE8+vfPSSQSsZQc++uQbzbM1atXxbJ7q1evpqZNm9LChQtp7dq1lJiYSG/fvqWTJ0+Sn58ftWjRgg4ePFgsj/fnz5+pZ8+eVLduXQoLC6PMzEx68uQJxcXFkZmZGZ04cYJSU1Pp3LlzVKlSJYqKiiILCwt5h11ocNvj50hOTiY7OztasGABdezYkX7//XdaunQpnT17lgYPHkz9+/cnIsV+PuzevZu0tLTI1tZW3Obl5UV37tyh8+fP//C4FJdyjezXeP78OfXu3ZuysrKoV69e5OPjI3727NkzUlVVpfLly5MgCHxufePixYvk7+9PFhYWNHfuXLp+/Tr17NmTzM3NacqUKWRsbCzvEFkhpJhPNMbYX/LgwQNq2bIl9e3bl9LS0qhly5YUFBQk1l/+9OkTEf1vmnrZsmXlFitjjH2PqakpRUVF0YULF2jhwoV0/fp18TMnJyfuLGH/iiAItGPHDnJxcaEKFSrQ69evSV1dnbKzs+nSpUtUo0YNcRCDsrIyTZ8+nS5evEjlypUrlh28/5Sfnx9t2rSJ1q5dS126dCEHBwd69uwZTZkyhYjyOtMVtSPu7yhRogSfV3+TNMFFRPTo0SMyMTGhI0eOkKWlJfXs2ZP69etHderUoXbt2lF0dDTVqlWLevbsSWlpabR//34SBIGK49hHAJSWlkYfP36kN2/e0KhRoyggIIDmzZtHfn5+VLZsWVq1ahWdOXOGEhMTOVHzDW57/ByXL18mAwMD8vf3p+rVq5ONjQ2FhoaSlZUVTZ06ldauXUtEpFDPB+l7N1HeulozZsyg5s2b09ChQ2nr1q1ERBQSEkIqKip04MABIsorRfUt7kxnf4e2tjaFh4dTmTJlaN26dRQVFUW5ubnUvHlzWrJkCWloaJAgCCSRSPjc+oa5uTlFRUVRSkoKhYSEUP369WnVqlV069Yt0tDQkHd4rJDimTWMsR9asGABbd++ndauXUuOjo7Utm1bioiIoBIlSlBcXBzt37+fZs+ezYugMcYKvYsXL1JQUBDp6+vTxIkTFXpBd/bz3L59m9q2bUsjRoygfv36yXw2cuRI2r59O4WEhNCNGzcoJiaGTp06xfWo/8DTp0/p999/p0+fPpG9vT0pKSnxCE32n8k/Gn/atGl0/PhxGjNmDDk4OBARUVRUFCUmJtLBgwdJS0uLdHR0aMOGDaSpqSn+G8W5Hv/atWspKCiIlJWVqWXLltSpUyfq2bMnDR48mK5evUr79+/na/NPcNvj34mLi6P+/ftTQkICmZiYiNuPHz9Obdq0ISUlJZo7dy4FBQXJMcpfJ//95sGDB6SlpUUZGRl09epVmjdvHt29e5d0dHSod+/eNG7cOOrcuTPNmTNHzlGz4iQtLU1s13758oXKlClDycnJVKpUKXmHVuhdvHiRAgICSF9fn1asWEGlSpUiVVVVeYfFCinFGYLAGPuhH+Vs7ezsSElJiaysrKhFixa0fPly8bMjR47Qq1evKCcn51eFyRhj/5i5uTmFh4fTs2fPqHz58vIOhxUTjx49ImVlZWrXrp24TfpM9fLyojZt2tCcOXPo9OnTFB8fz4maP1GtWjWytrYmBwcHUlJSotzcXO4MZv8ZaaJm5MiRtGjRIgoODiZ9fX3xc39/f5o5cybNnDmTnj9/Tvv27aOlS5fK/BvFNVFDRNSzZ0+6cOECxcTE0I4dO8jb25uI8jqMa9So8d3R+kwWtz3+uu+9j9aoUYPKlClDW7dupVevXonbq1SpQg4ODhQSEkJt2rT5lWHKRUREBF26dEm834SGhpKzszPp6enRnDlzqG7durRnzx7at28fqaioUGxsLN2/f58WL15MJ0+elHP0rDjR09Oj8PBwmj17No0ZM4YuXrxIpUqV4j6hv8Dc3JyWLVtGz58/p8zMTE7UsD/EM2sYY2Kt7itXrlB6ejqpqqqSra0tZWdn08CBA2nXrl00fvx48vPzo3fv3lF4eDitXLmSjh07JlODmTHGCrvPnz+TioqKvMNgxcTOnTspODiYTpw4QTo6OjJrhpw6dYqUlJSoQYMGlJ2dzaUOGCuEjhw5Qn369KEtW7aQlZUVff36lT58+EDnz58nJycnMVl4/fp1iomJoTFjxihsAvHmzZu0bt06Wrp0KZ08eVJmpgP7Y9z2+GPSd9FTp07RtWvXSCKRiLNlli5dSqNGjaLBgweTq6srGRoa0syZM+nq1au0Zs0aqlChgpyj/2+lpaVRs2bNyNnZmUaOHEnXr1+n/v37U3h4OF25coXi4+OpWrVqNGzYMLK3tyciotTUVDpx4gRNmTKFgoODacyYMQq9rg/7bxXnGab/BX4esL+CkzWMKagZM2ZQRkYGTZ06lUqUKEGxsbHk4+ND1atXpzt37lBISAjNnj2bvn79Sj4+PnT9+nV68OABmZqa0osXL2jbtm1kbm4u75/BGGOMyU1aWhrVr1+fhg4dSmFhYTKfDR06lNTU1Gjy5MncQcJYIfFth+Xu3btp0KBBdO/ePbpz5w5t2LCBNm/eTC9evCAzMzM6evRogU4oRSzNl5ycTPPmzaNLly7Rpk2bqGHDhvIOiRUzsbGx5O3tTXXq1KGnT5+StrY2HTx4kLS1tSkiIoIiIiLo+fPnVLFiRXr27BkdPXqUzMzM5B32L3Hp0iXq06cP2dvbU4kSJcjY2Jh69+5NRER79uyh+fPnU/ny5WnIkCHUvHlz8XtLliyhKVOm0M2bN6lixYryCp8xxtjfpFitTMaYSE1NjcaOHUtly5alPn360PTp0yk8PJzs7e0pOTmZvL296e3bt7Ry5UrasGED3bhxg5KTk6lu3bqkq6tL1atXl/dPYIwxxuRKWg4iKCiIsrOzqWfPnqSkpETR0dEUHR1NZ86c4UQNY4WI9HrcsGEDdejQgfT19alixYpkZmZG6enp1KFDBxozZgw1a9aMjIyMKC4ujjp16iTzbyhaooaIyNjYmPr160e6urpUs2ZNeYfDignpjJovX77Qzp07KSIigjp37kyPHj0if39/atasGR0+fJj69etHLVq0oKdPn9KbN2/I2tqaatWqJe/wfxkzMzNasWIFBQYG0r1792jChAniZx06dCAiovnz59PixYspJyeHWrZsSUREzs7OtGrVKnr58iUnaxhjrAhRvJYmY4wA0KBBg0hVVZUCAwPpw4cPZGpqSm5ubqSurk61a9emcuXKkaurKwmCQPPnz6cGDRpQgwYN5B06Y4wxVqj4+fmRuro6BQYG0qZNm0hFRYWUlJTo8OHDvJg0Y4XA27dvSVNTU/z7+PHjFBoaSp6enmRsbEyLFi2iY8eOUYMGDahZs2akqalJr169IktLy2JfYumvUlVVFUssMfazCIJAx48fp6FDh1LNmjXJ0tKS1NXVqX79+hQTE0PdunWjFi1a0OHDh8nQ0JAMDQ3lHbLcWFhYUFRUFHXq1In27t1LLVu2FN/NO3ToQCVKlKBRo0bRoUOHxGTNxo0b6erVqzL3P8YYY4Ufl0FjTMFIL3lBEAgAbdq0iXr27EmVKlWi5ORkql69ulgiYv/+/eTm5kadO3emJUuWcL19xhhj7AeePn1KDx8+JEEQSE9Pj6pUqSLvkBhTeP3796fDhw/TkSNHqGrVqkSUl6zp27cvXb58uUDd+K9fv9Lbt2+pb9++9OrVKzp58iTX4mfsP3ThwgXq2bMn3b9/ny5dukT16tUT30WfPHlCnp6edOfOHUpJSeHKDkR0+fJl6tWrF1lZWdHgwYNl1o89ffo0NWrUSLxnbdmyherUqUOWlpbyCpcxxtg/wHUZGFNAgiDQoUOHaPjw4dSwYUPauHEjvXr1ilauXCk2jgFQmzZtaNOmTXTgwAH6/PmzvMNmjDHGCq1q1aqRra0tNW7cmBM1jBUSQ4cOpdzcXPL09KTff/+diIg+fvxIampqpKKiQgDEgUyfP3+mTZs2kaenJ7148YKOHz9OSkpKlJubK8+fwFixZmZmRmvXriVdXV3y9/en7Oxs8V20Ro0atHHjRjI1NeV30f/XsGFDWrVqFSUnJ9OiRYvo+vXr4mdNmjSRuWd5eHhwooYxxoogTtYwpmAEQaAdO3aQi4sLVahQgbKyssjd3Z1+++03mjp1Ks2YMYMkEok486Zjx450//590tbWlnfojDHGGGOM/akDBw7Qx48fqW7dunTgwAF68uQJubu708uXL+n9+/dUtmxZIsprFwuCQEREKioqVKFCBXJzc6NTp06RsrIy5eTk8Mwaxn4SaWI0PT2dPnz4QO/evaOSJUuSubk5rV+/nl68eEGOjo6UnZ0tvovWqlWL9u3bR7Vr15Zz9IWHubk5RUZG0qVLl2jixImUlpYm8znfsxhjrGjjMmiMKZjbt29T27ZtacSIEdSvXz+Zz1asWEH9+vWjadOm0ahRo3hRZMYYY4wxVqRs3LiRvL29KSIignr06EFqamr04MEDatWqFRkaGlLbtm0pIiKC3N3dqXTp0lS1alXKzMyk58+fU/fu3cW1pnJzc7nTk7GfBAAJgkDx8fEUFhZGWVlZ9OXLF1qxYgXZ2dkREVFycjK5u7tTrVq16MCBA6SsrCznqAu38+fP02+//UaRkZH83s4YY8UIJ2sYUzCHDh2iAQMG0IEDB0hHR4eISCx9RkS0YcMG8vHxodmzZ1NISIg8Q2WMMcYYY+xvGzduHM2ZM4cWLVpE3t7eYsKmbdu2dPv2bbK3tyc1NTWxJFpWVhapqKjQnj17OEHD2E+U/z0zLi6OunfvTmPHjiVbW1uKjIykPXv20IoVK6hbt25ERJSSkkItW7YkW1tb2rt3rzxDLxKkSbD8x5kxxljRVlLeATDGfq2MjAzKysoS/5aWPCMiOnr0KFlaWtKWLVvIxMREXiEyxhhjjDH2t0lnw0ybNo0A0MCBA4mIyNvbm3R1dWnfvn3UuXNnysrKoi1btny3zC/PqGHs37t+/ToZGxuLCYRHjx7RvHnzaMqUKTR06FB6/PgxnT59mqpUqULe3t7i2lIWFhZ05MgRUlNTk/MvKBqk5eI4UcMYY8UH39EZUzANGzak9PR0WrFiBRERlShRQkzW7Nq1izZu3EhdunQhIyMjeYbJGGOMMcbY35J/ce2wsDAaOXIkDRw4kNavX08ZGRmkq6tLsbGx9Pr1a/Lw8KBHjx5R/kITADhRw9i/tHXrVvL29qYNGzaI23JycsjJyYn8/f3p2bNn1Lp1a3J0dKTLly9T27ZtKTg4mNavX09ERGZmZlSnTh15hV/kSN/lGWOMFQ88s4YxBaOnp0fh4eEUFBRE2dnZ1LNnT1JSUqLo6GiKjo6mM2fO8EsqY4wxxhgrMvKXAMrfjp0+fTrl5uYWmGGTmJhIpqamNGPGDIqIiBD3505Pxv49CwsLqly5MkVHR5MgCNS9e3fS19cnHx8fKl++PIWFhVGdOnVowYIFVLp0adLR0aFjx47R8OHDycXFhcqVKyfvn8AYY4zJDSdrGFNAfn5+pK6uToGBgbRp0yZSUVEhJSUlOnz4sLioKmOMMcYYY4Vd/kTNunXr6Pr166SsrEwNGzYkNzc3mjVrFhERDRw4kARBoB49epCuri7dvn2btLS05Bk6Y8VSnTp1KCIiggYNGkSRkZEEgHr06EE1a9aknJwcunXrFunq6pK6ujoR5SVJN2/eTDY2NpyoYYwxpvAE5J/3zRhTKE+fPqWHDx+SIAikp6dHVapUkXdIjDHGGGOM/W0jRoyg1atXU8uWLen69euUm5tL1tbWtGbNGiIiGj16NC1cuJDCwsKof//+pKqqSkS8Rg1j/5W0tDQaNGgQZWZmUt++fcnLy4uIiIYPH06rVq2iSZMm0eXLl2n37t109uxZqlu3rpwjZowxxuSPkzWMMcYYY4wxxoqsQ4cOkZ+fH23ZsoWaNm1KHz9+pK1bt9LcuXOpefPm9NtvvxER0aBBg+jy5ct07NgxLnnG2C+QP2Hj7+9P3t7e9OXLF+rfvz+dO3eONDU1acmSJWRmZibvUBljjLFCgZM1jDHGGGOMMcaKDAAyyZaYmBgaMWIEpaamkpqaGhERffjwgVauXElbtmyhTZs2Ue3atWW+++2/wRj7b/xohs3Lly+pbNmyVLZsWTlHyBhjjBUeJeQdAGOMMcYYY4wx9ldJkyyrV6+miIgIqlChApUoUYJSU1PFfcqVK0fOzs6UkpJC9+/fl/kuJ2oY+3X09PRoyZIlVKZMGYqKiqJVq1YREVHlypU5UcMYY4x9g5M1jDHGGGOMMcaKlM+fP9O2bdvo0KFDZGZmRqVKlaIVK1ZQWlqauI+6ujqZmJiI69NIcaKGsV9LT0+PwsPD6fPnz7R792768OGDvENijDHGCiUug8YYY4wxxhhjrMiQzoy5dOkSNW3alPbt20cqKirUpk0bcnJyIkdHRzIyMqKwsDB6/fo1nTt3jpSUlOQdNmMK7+HDh1SiRAmqWbOmvENhjDHGCiVO1jDGGGOMMcYYK7S+V7YMAH358oUGDBhAubm5FB0dTUePHqU5c+bQ5cuXqUKFClSlShXau3cvKSsrU25uLidsGGOMMcZYocbJGsYYY4wxxhhjhd6SJUtISUmJvL29qVy5ckREtH79egoKCqIjR46QtbU1vX//nr58+UKfPn0iXV1dEgSBcnJyqGTJknKOnjHGGGOMsT/GyRrGGGOMMcYYY4VaZmYmjR07liIiIqh169ZkZmZGU6dOJSIiPz8/ev78OcXExJCamprM9yQSCZUowUu1MsYYY4yxwo9brYwxxhhjjDHGCrUyZcrQggUL6OrVq9SgQQOKiYmhOnXq0IIFC6hGjRpUunRpevDgQYHvcaKGMcYYY4wVFTyzhjHGGGOMMcZYkZGTk0M5OTkUGhpKaWlpdPToUfrw4QPNnDmTRo4cKe/wGGOMMcYY+0c4WcMYY4wxxhhjrMgAQIIgEBFRWloaHTt2jLZv306xsbG8Ng1jjDHGGCuyOFnDGGOMMcYYY6xIyZ+wyS8nJ4cTNowxxhhjrEjiZA1jjDHGGGOMsSLtR8kbxhhjjDHGigpebZExxhhjjDHGWJHGiRrGGGOMMVbUcbKGMcYYY4wxxhhjjDHGGGNMjjhZwxhjjDHGGGOMMcYYY4wxJkecrGGMMcYYY4wxxhhjjDHGGJMjTtYwxhhjjDHGGGOMMcYYY4zJESdrGGOMMcYYY4wxxhhjjDHG5IiTNYwxxhhjjDHGGGOMMcYYY3LEyRrGGGOMMcYY+wdu3rxJjRs3JhUVFTIzM5N3OIwxxhhjjLEijJM1jDHGGGOMMfYPTJw4kcqWLUu3bt2ixMTEn/Jv6urq0sKFC3/Kv8UYY4wxxhgrOjhZwxhjjDHGGGP/wL1798jOzo50dHSoYsWK8g5HxtevX3/p9xhjjDHGGGP/DidrGGOMMcYYY4WWg4MDDRo0iIYMGUKamppUpUoVWrlyJX369Il69epF6urqVKdOHUpISCAiotzcXOrduzfp6emRqqoqGRoa0qJFi2T+TT8/P+rUqRPNnTuXqlatShUrVqQBAwZQdna2uI8gCLRz506Z72loaFB0dLT4eXJyMk2ZMoUEQaBJkyYREdGoUaPIwMCAypQpQ/r6+jR+/HiZf5eIKC4ujqytrUlFRYUqVapEnTt3Fn/rw4cPaejQoSQIAgmCQEREkyZNKlBmbeHChaSrq1vgN4WFhVG1atXI0NCQiIgeP35M7u7upKGhQRUqVCBXV1d68ODBn36PMcYYY4wx9mtxsoYxxhhjjDFWqK1Zs4YqVapE58+fp0GDBlG/fv2oW7du1KRJE0pJSSEnJyfy8fGhzMxMkkgkVKNGDdq2bRtdv36dJkyYQGPGjKGtW7fK/JtHjhyhe/fu0ZEjR2jNmjUUHR0tJmL+imfPnlH9+vVp+PDh9OzZMwoJCSEiInV1dYqOjqbr16/TokWLaOXKlbRgwQLxe/Hx8dS5c2dq164dXbx4kRITE8nGxoaIiHbs2EE1atSgKVOm0LNnz+jZs2d/6zglJibSrVu36ODBg7Rnzx7Kzs6mNm3akLq6Op04cYJOnTpFampq1LZtW5kZNN9+jzHGGGOMMfbrlZR3AIwxxhhjjDH2Rxo2bEjjxo0jIqLQ0FCaOXMmVapUifr27UtERBMmTKCIiAi6cuUKNW7cmCZPnix+V09Pj86cOUNbt24ld3d3cbumpiaFh4eTkpIS1atXj9q3b0+JiYniv/lntLW1qWTJkqSmpkba2tridmmcRHnrz4SEhNDmzZtp5MiRREQUFhZGnp6eMjE2bNiQiIgqVKhASkpKpK6uLvNv/lVly5alyMhIKlWqFBERrV+/niQSCUVGRoqzdFavXk0aGhp09OhRcnJy+u73GGOMMcYYY78eJ2sYY4wxxhhjhZqpqan435WUlKhixYrUoEEDcVuVKlWIiOjly5dERLR06VKKioqiR48eUVZWFn39+rVAGbH69euTkpKS+HfVqlUpNTX1X8e6ZcsWWrx4Md27d48yMjIoJyeHypUrJ35+6dKlv5wQ+rsaNGggk3C5fPky3b17l9TV1WX2+/z5M927d++H32OMMcYYY4z9epysYYwxxhhjjBVqysrKMn8LgiCzTTprRCKR0ObNmykkJITmzZtHtra2pK6uTnPmzKFz58796b8pkUhk/gYgs8+3a89868yZM9SjRw+aPHkytWnThsqXL0+bN2+mefPmifuoqqr+hV8sq0SJEn8plrJly8r8nZGRQZaWlrRhw4YC+2ppaf3we4wxxhhjjLFfj5M1jDHGGGOMsWLj1KlT1KRJE+rfv7+4Lf8skr9KS0tLZs2YO3fuUGZm5h9+5/Tp06Sjo0Njx44Vtz18+FBmH1NTU0pMTKRevXp9998oVaoU5ebmFojl+fPnBEBMTF26dOlPf4OFhQVt2bKFKle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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "from difflib import get_close_matches\n", + "\n", + "title = cars['title']\n", + "\n", + "# Function to extract make from title\n", + "def extract_make(title):\n", + " title_lower = title.lower()\n", + " for make in kbb_make:\n", + " if make in title_lower:\n", + " return make\n", + " elif (len(make) >= 4 and make[:4] in title_lower):\n", + " return make\n", + " return None\n", + "\n", + "def extract_model_wreg(title, make):\n", + " title_lower = title.lower()\n", + "\n", + " # Check if the make is in the kbb_models dictionary\n", + " make_models = kbb_models.get(make, [])\n", + "\n", + " # Use regex to find patterns like \"2021 RAM 3500\" in the title\n", + " match = re.search(r'\\b\\d{4}\\s*[a-zA-Z0-9-]+\\s*([a-zA-Z0-9-]+)\\b', title)\n", + "\n", + " if match:\n", + " # Extracted model is in the first capturing group\n", + " model = match.group(1)\n", + "\n", + " if model is not None:\n", + " # Handle models with dashes\n", + " model = model.replace(\"-\", \"\")\n", + "\n", + " # Compare with the kbb_models dictionary\n", + " matched_model = get_close_matches(model, make_models, n=1)\n", + "\n", + " if matched_model:\n", + " return matched_model[0]\n", + " else:\n", + " # If no direct match, try finding a close match using pieces of words\n", + " title_words = re.findall(r'\\b\\w+\\b', title)\n", + " extracted_model_pieces = []\n", + "\n", + " for word in title_words:\n", + " # Check if the word is part of the make name, if yes, skip it\n", + " if make is not None and word.lower() in make.lower():\n", + " continue\n", + "\n", + " extracted_model_pieces.append(word)\n", + " current_model_attempt = ' '.join(extracted_model_pieces)\n", + "\n", + " # Check if the current attempt is a close match\n", + " matched_model = get_close_matches(current_model_attempt, make_models, n=1)\n", + " if matched_model:\n", + " return matched_model[0]\n", + "\n", + " # If still no match, return the original extracted model\n", + " return model\n", + " else:\n", + " return None\n", + " else:\n", + " return None\n", + "\n", + "# Apply the extraction functions\n", + "cars['manufacturer'] = cars['title'].apply(extract_make)\n", + "cars['model'] = cars.apply(lambda row: extract_model_wreg(row['title'], row['manufacturer']), axis=1)\n", + "\n", + "# Print the DataFrame with 'manufacturer' and 'model'\n", + "result_df = cars[['manufacturer', 'model']]\n", + "print(result_df)\n", + "\n", + "# Save the selected columns to CSV\n", + "result_df.to_csv('output.csv', index=False)\n", + "\n", + "fig, ax = plt.subplots(figsize=(20, 10))\n", + "sns.barplot(data=cars, x='manufacturer', y='price', estimator=np.median, ax=ax).set(title='Median List Price by Manufacturer')\n", + "plt.xticks(rotation=45)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 187, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "manufacturer\n", + "ram 34990.0\n", + "subaru 31495.0\n", + "gmc 31240.5\n", + "cadillac 29490.0\n", + "dodge 29286.0\n", + "ford 28440.0\n", + "land rover 27224.0\n", + "nissan 25683.0\n", + "chevrolet 24429.0\n", + "jeep 23995.5\n", + "hyundai 18995.0\n", + "volkswagen 17895.0\n", + "lexus 17805.0\n", + "infiniti 17392.5\n", + "bmw 16745.0\n", + "honda 14945.0\n", + "buick 13500.0\n", + "kia 12747.5\n", + "toyota 12248.0\n", + "acura 8750.0\n", + "Name: price, dtype: float64" + ] + }, + "execution_count": 187, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.groupby(['manufacturer'])['price'].median().sort_values(ascending = False)" + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "manufacturer\n", + "ford 49\n", + "chevrolet 35\n", + "ram 17\n", + "nissan 11\n", + "gmc 8\n", + "jeep 8\n", + "toyota 7\n", + "cadillac 5\n", + "dodge 5\n", + "kia 4\n", + "land rover 3\n", + "lexus 3\n", + "volkswagen 3\n", + "honda 2\n", + "bmw 2\n", + "infiniti 2\n", + "acura 2\n", + "subaru 1\n", + "hyundai 1\n", + "buick 1\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 188, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars['manufacturer'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 189, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "169" + ] + }, + "execution_count": 189, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 190, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " manufacturer model\n", + "0 gmc Terrain\n", + "1 ford Edge\n", + "2 ford F350\n", + "3 chevrolet 3500HD\n", + "4 ford F250\n", + ".. ... ...\n", + "170 ford F250\n", + "172 toyota Prius\n", + "173 chevrolet Silverado 1500 Crew Cab\n", + "174 ford F350\n", + "175 ford F350\n", + "\n", + "[169 rows x 2 columns]\n" + ] + } + ], + "source": [ + "# Drop rows where either 'manufacturer' or 'model' is empty\n", + "cars.dropna(subset=['manufacturer', 'model'], inplace=True)\n", + "\n", + "# Print the DataFrame with 'manufacturer' and 'model'\n", + "result_df = cars[['manufacturer', 'model']]\n", + "print(result_df)\n", + "\n", + "# Save the selected columns to CSV\n", + "#result_df.to_csv('outputff.csv', index=False)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 191, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "169" + ] + }, + "execution_count": 191, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 192, + "metadata": {}, + "outputs": [], + "source": [ + "numeric_columns = ['price', 'year', 'odometer','age']\n", + "#cars.groupby(['title_status'])[numeric_columns].median()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Modeling" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Segmentation" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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sourcescraper-versionscrape-datetitlepricelocationodometerimagesyearagemanufacturermodel_with_dictmodel_without_dictmodel_wregmodel
0craigslist12023-11-132015 GMC Terrian SLT Leather Seats SUV8495Clyde165['https://images.craigslist.org/00q0q_fqrDYmbI...20158gmcAcadiaNoneTerrainTerrain
1craigslist12023-11-132012 Ford Edge SUV5900Abilene127['https://images.craigslist.org/00u0u_djFxYThj...201211fordEdgeNoneEdgeEdge
2craigslist12023-11-132014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF...29999WWW.GETADIESEL.COM227['https://images.craigslist.org/00z0z_fBJpyxit...20149fordBroncoF350F350F350
3craigslist12023-11-131-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR...42900WWW.GETADIESEL.COM143['https://images.craigslist.org/00J0J_cBZBKQMO...20194chevroletBlazerOWNER 20193500HD3500HD
4craigslist12023-11-132017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ...42897WWW.GETADIESEL.COM180['https://images.craigslist.org/00v0v_3LJpHDnn...20176fordBroncoF250F250F250
\n", + "
" + ], + "text/plain": [ + " source scraper-version scrape-date \\\n", + "0 craigslist 1 2023-11-13 \n", + "1 craigslist 1 2023-11-13 \n", + "2 craigslist 1 2023-11-13 \n", + "3 craigslist 1 2023-11-13 \n", + "4 craigslist 1 2023-11-13 \n", + "\n", + " title price \\\n", + "0 2015 GMC Terrian SLT Leather Seats SUV 8495 \n", + "1 2012 Ford Edge SUV 5900 \n", + "2 2014 FORD F-350 KING RANCH 4X4 DIESEL NAV ROOF... 29999 \n", + "3 1-OWNER 2019 CHEVY 3500HD LTZ 4X4 DURAMAX SKIR... 42900 \n", + "4 2017 FORD F-250 KING RANCH FX4 DIESEL NAV BDS ... 42897 \n", + "\n", + " location odometer \\\n", + "0 Clyde 165 \n", + "1 Abilene 127 \n", + "2 WWW.GETADIESEL.COM 227 \n", + "3 WWW.GETADIESEL.COM 143 \n", + "4 WWW.GETADIESEL.COM 180 \n", + "\n", + " images year age manufacturer \\\n", + "0 ['https://images.craigslist.org/00q0q_fqrDYmbI... 2015 8 gmc \n", + "1 ['https://images.craigslist.org/00u0u_djFxYThj... 2012 11 ford \n", + "2 ['https://images.craigslist.org/00z0z_fBJpyxit... 2014 9 ford \n", + "3 ['https://images.craigslist.org/00J0J_cBZBKQMO... 2019 4 chevrolet \n", + "4 ['https://images.craigslist.org/00v0v_3LJpHDnn... 2017 6 ford \n", + "\n", + " model_with_dict model_without_dict model_wreg model \n", + "0 Acadia None Terrain Terrain \n", + "1 Edge None Edge Edge \n", + "2 Bronco F350 F350 F350 \n", + "3 Blazer OWNER 2019 3500HD 3500HD \n", + "4 Bronco F250 F250 F250 " + ] + }, + "execution_count": 193, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cars.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 206, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " manufacturer model year price kbb_price \\\n", + "0 gmc Terrain 2015 8495 8092 \n", + "1 ford Edge 2012 5900 7199 \n", + "2 ford F350 2014 29999 16934 \n", + "4 ford F250 2017 42897 21218 \n", + "6 ford F250 2014 39995 14463 \n", + ".. ... ... ... ... ... \n", + "170 ford F250 2017 38500 21218 \n", + "172 toyota Prius 2013 12248 10574 \n", + "173 chevrolet Silverado 1500 Crew Cab 2019 32792 24966 \n", + "174 ford F350 2020 49781 45503 \n", + "175 ford F350 2020 49781 45503 \n", + "\n", + " price_difference fraudulent \n", + "0 403.0 False \n", + "1 1299.0 False \n", + "2 13065.0 True \n", + "4 21679.0 True \n", + "6 25532.0 True \n", + ".. ... ... \n", + "170 17282.0 True \n", + "172 1674.0 False \n", + "173 7826.0 False \n", + "174 4278.0 False \n", + "175 4278.0 False \n", + "\n", + "[135 rows x 7 columns]\n", + "Results have been saved to price_comparison_results.csv\n" + ] + } + ], + "source": [ + "import requests\n", + "from bs4 import BeautifulSoup\n", + "from concurrent.futures import ThreadPoolExecutor\n", + "import pandas as pd\n", + "import numpy as np\n", + "from difflib import get_close_matches\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "# Function to scrape current market price from Kelly Blue Book\n", + "def get_kbb_price(row):\n", + " base_url = 'https://www.kbb.com/'\n", + " \n", + " # Check if vehicle_make and vehicle_model are not None or float\n", + " if isinstance(row['manufacturer'], str) and isinstance(row['model'], str):\n", + " # Replace spaces with dashes in the manufacturer and model for the URL\n", + " make_url_part = row[\"manufacturer\"].lower().replace(\" \", \"-\")\n", + " model_url_part = row[\"model\"].lower().replace(\" \", \"-\")\n", + " \n", + " search_url = f'{base_url}{make_url_part}/{model_url_part}/{row[\"year\"]}/'\n", + " #print(search_url)\n", + " try:\n", + " response = requests.get(search_url)\n", + " soup = BeautifulSoup(response.text, 'html.parser')\n", + " # Extract relevant information (adjust based on the actual HTML structure)\n", + " # Extract the price information from the HTML code\n", + " #price_field = soup.find('div', {'class': 'nationalBaseDefaultPrice'})\n", + " #kbb_price = price_field['content'] if price_field else None\n", + "\n", + " # Use regular expression to extract the price information\n", + " pattern = re.compile(r'\"nationalBaseDefaultPrice\":(\\d+),')\n", + " match = pattern.search(response.text)\n", + " \n", + " kbb_price = match.group(1) if match else None\n", + "\n", + " return kbb_price\n", + "\n", + " #return kbb_price.text.strip() if kbb_price else None\n", + " except Exception as e:\n", + " print(f\"Error: {e}\")\n", + " return None\n", + " else:\n", + " return None\n", + "\n", + "\n", + "# Use ThreadPoolExecutor to parallelize the scraping process\n", + "with ThreadPoolExecutor(max_workers=5) as executor:\n", + " kbb_prices = list(executor.map(get_kbb_price, cars.to_dict(orient='records')))\n", + "\n", + "# Add the kbb_prices to the DataFrame\n", + "cars['kbb_price'] = kbb_prices\n", + "\n", + "# Drop rows where kbb_price is empty\n", + "cars = cars.dropna(subset=['kbb_price'])\n", + "\n", + "# Compare the actual market price with the dataset using absolute difference\n", + "cars['price_difference'] = np.abs(cars['price'] - cars['kbb_price'].astype(float))\n", + "\n", + "# Print the results\n", + "#print(cars[['manufacturer', 'model', 'year', 'price', 'kbb_price', 'price_difference']])\n", + "\n", + "# Flag rows with price difference greater than 10000 as fraudulent\n", + "cars['fraudulent'] = np.where(cars['price_difference'] > 10000, True, False)\n", + "\n", + "# Print the results\n", + "output_df = cars[['manufacturer', 'model', 'year', 'price', 'kbb_price', 'price_difference', 'fraudulent']]\n", + "print(output_df)\n", + "\n", + "# Save the results to a CSV file\n", + "output_csv_filename = 'price_comparison_results.csv'\n", + "output_df.to_csv(output_csv_filename, index=False)\n", + "print(f'Results have been saved to {output_csv_filename}')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 207, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Visualize the comparison\n", + "fig, ax = plt.subplots(figsize=(20, 10))\n", + "sns.barplot(data=cars, x='manufacturer', y='price_difference', estimator=np.median, ax=ax).set(title='Median Price Difference by Manufacturer')\n", + "plt.xticks(rotation=45)\n", + "plt.show()\n", + "\n", + "# Visualize the average fraudulent status on a separate plot\n", + "avg_fraudulent_status = cars.groupby('manufacturer')['fraudulent'].mean().reset_index()\n", + "plt.figure(figsize=(12, 6))\n", + "sns.barplot(data=avg_fraudulent_status, x='manufacturer', y='fraudulent', color='red').set(title='Average Fraudulent Status by Manufacturer')\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 208, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " manufacturer model year price kbb_price \\\n", + "1 ford Edge 2012 5900 7199 \n", + "2 ford F350 2014 29999 16934 \n", + "4 ford F250 2017 42897 21218 \n", + "6 ford F250 2014 39995 14463 \n", + "7 ford F250 2014 33885 14463 \n", + ".. ... ... ... ... ... \n", + "166 toyota RAV4 2019 27995 22284 \n", + "169 nissan TITAN 2018 28888 14764 \n", + "170 ford F250 2017 38500 21218 \n", + "172 toyota Prius 2013 12248 10574 \n", + "173 chevrolet Silverado 1500 Crew Cab 2019 32792 24966 \n", + "\n", + " price_difference_percentage \n", + "1 -18.044173 \n", + "2 77.152474 \n", + "4 102.172684 \n", + "6 176.533223 \n", + "7 134.287492 \n", + ".. ... \n", + "166 25.628253 \n", + "169 95.665131 \n", + "170 81.449713 \n", + "172 15.831284 \n", + "173 31.346631 \n", + "\n", + "[117 rows x 6 columns]\n" + ] + } + ], + "source": [ + "cars['kbb_price'] = pd.to_numeric(cars['kbb_price'], errors='coerce')\n", + "\n", + "# Calculate the percentage difference between the actual price and KBB price\n", + "cars['price_difference_percentage'] = ((cars['price'] - cars['kbb_price']) / cars['kbb_price']) * 100\n", + "\n", + "# Set a threshold for percentage difference, beyond which a vehicle is flagged as potentially fraudulent\n", + "fraud_threshold = 10 # You can adjust this threshold based on your criteria\n", + "\n", + "# Create a new column 'fraudulent' to flag potentially fraudulent vehicles\n", + "cars['fraudulent'] = np.abs(cars['price_difference_percentage']) > fraud_threshold\n", + "\n", + "# Print or analyze the flagged vehicles\n", + "fraudulent_vehicles = cars[cars['fraudulent']]\n", + "print(fraudulent_vehicles[['manufacturer', 'model', 'year', 'price', 'kbb_price', 'price_difference_percentage']])" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\"\\n#from sklearn.model_selection import train_test_split\\n#from sklearn.ensemble import IsolationForest\\n#from sklearn.preprocessing import StandardScaler\\n#from sklearn.metrics import classification_report\\n\\n#features = ['year', 'odometer']\\n#target = 'price'\\ndata = cars[features + [target]].copy()\\n\\ntrain_data, test_data = train_test_split(data, test_size=0.2, random_state=42)\\n\\nscaler = StandardScaler()\\ntrain_data[features] = scaler.fit_transform(train_data[features])\\ntest_data[features] = scaler.transform(test_data[features])\\n\\nmodel = IsolationForest(contamination=0.05, random_state=42)\\nmodel.fit(train_data[features])\\n\\ntest_data['anomaly_score'] = model.decision_function(test_data[features])\\n\\nthreshold = -0.2\\n\\ntest_data['anomaly'] = test_data['anomaly_score'] < threshold\\n\\nprint(classification_report(test_data[target], ~test_data['anomaly']))\\n\"" + ] + }, + "execution_count": 90, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "'''\n", + "#from sklearn.model_selection import train_test_split\n", + "#from sklearn.ensemble import IsolationForest\n", + "#from sklearn.preprocessing import StandardScaler\n", + "#from sklearn.metrics import classification_report\n", + "\n", + "#features = ['year', 'odometer']\n", + "#target = 'price'\n", + "data = cars[features + [target]].copy()\n", + "\n", + "train_data, test_data = train_test_split(data, test_size=0.2, random_state=42)\n", + "\n", + "scaler = StandardScaler()\n", + "train_data[features] = scaler.fit_transform(train_data[features])\n", + "test_data[features] = scaler.transform(test_data[features])\n", + "\n", + "model = IsolationForest(contamination=0.05, random_state=42)\n", + "model.fit(train_data[features])\n", + "\n", + "test_data['anomaly_score'] = model.decision_function(test_data[features])\n", + "\n", + "threshold = -0.2\n", + "\n", + "test_data['anomaly'] = test_data['anomaly_score'] < threshold\n", + "\n", + "print(classification_report(test_data[target], ~test_data['anomaly']))\n", + "'''\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}