Projet spécialité Data-IA¶

Uncomment if you use Drive

In [ ]:
# from google.colab import drive
# drive.mount("/content/drive", force_remount=True)

Mounted at /content/drive

Analyse de données : l'évolution et la prévision de la production automobile dans le monde¶

Ce projet a pour but d'analyser l'évolution et les tendances de ces dernières années en matière de production/vente automobile, dans le monde.

Nous allons tout d'abord analyser la production mondiale, puis par continent. Pour ensuite s'interesser à plusieurs pays choisis.

En corrélation avec cette analyse, nous devrons également analyser l'évolution de la population. Car c'est celle-ci qui determinera les facteurs de production/ventes.

Dans une façon de penser plus "vert", nous pouvons réduire la pollution mondiale en adaptant la production de véhicules afin de limiter la surproduction, mais cela permettrait aussi de générer plus de revenu et de faire plus d'économie pour vous les grands groupes de l'automobile.

Uncomment if you use Drive

In [ ]:
# %pip install -qq pycountry-convert==0.7.2
In [3]:
import datetime # get actual date
import warnings # omit warnings from functions

""" Scrapping """
import requests # make requests on a website
from bs4 import BeautifulSoup # parse HTML

""" Data Analyse """
import pycountry_convert as pc # To have for example continent of a country
import pandas as pd # Work with CSV, make DataFrame analyse
import matplotlib.pyplot as plt # To draw graphics

""" Previsions """
from statsmodels.tsa.statespace.sarimax import SARIMAX
from statsmodels.tsa.seasonal import seasonal_decompose
from statsmodels.tsa.arima.model import ARIMA

Analyses production¶

Scrapping des données de production mondiale¶

Nous devons dans un premier temps trouver les données à analyser.

  • Concernant la production automobile, nous avons trouver un site repertoriant les principaux pays producteurs de véihicules automobiles : https://www.oica.net/category/production-statistics/. Ce site est composé d'une table ayant un pays pour chaque ligne. Il est structuré d'une façon à ce qu'une méthode de scrapping puisse être facilement effectuée une page correspondant à une année. Ainsi, pour l'année 2010, les données se trouve sur l'URL /production/statistics/2010-statistics/.

Sur ce site, nous avons décidé de récupérer les données depuis 1999.

Pour un scrapping, nous avons besoin des modules requests et beautiful soup.

L'idée est donc de scraper ces données, dans la catégorie production-statistics/{ANNÉE}-statistics

In [4]:
def get_current_year() -> int:
    """
      Get the current year
      For automatisation of the dataset. In 2025,
      the program will research for the 2025's web page
    """
    today = datetime.date.today()
    year = today.year

    return year

def convert_to_csv(world_production_list: list, start, end):
    """
      Convert the world production list to a csv file
    """
    df = pd.DataFrame(world_production_list)
    # print(df.head(10))
    df.to_csv(f'datasets/world_car_production_{start}_{end}.csv', index=False, sep=';')

def scrape_page(soup: BeautifulSoup, world_production_list: list, start, end):
    """
      Scrap pages of the website
    """
    table = soup.find("tbody")
    countries = table.find_all("tr")

    for country_tr in countries:
        country_name = country_tr.find("td", {"class": f"column-1"}).text
        nbr_cars = country_tr.find("td", {"class": f"column-2"}).text
        nbr_commercial_vehicle = country_tr.find("td", {"class": f"column-3"}).text
        total = country_tr.find("td", {"class": f"column-4"}).text
        percent_change = country_tr.find("td", {"class": f"column-5"}).text

        # print(country_tr)
        # print(country_name)

        dict = {
            'Year': '',
            'Country_Name': '',
            'Nbr_Cars': '',
            'Nbr_Commercial_Vehicle': '',
            'Total': '',
            'Percent_Change': ''
        }

        dict['Year'] = start
        dict["Country_Name"] = country_name
        dict["Nbr_Cars"] = nbr_cars
        dict["Nbr_Commercial_Vehicle"] = nbr_commercial_vehicle
        dict["Total"] = total
        dict["Percent_Change"] = percent_change

        world_production_list.append(dict)

    start += 1

    if start <= end_year:
        print('Access to the next page')
        next_url = f'{target}{start}-statistics'
        print(f"Next URL : {next_url}")
        req = requests.get(target +  next_url)
        next_soup = BeautifulSoup(req.text, "html.parser")
        scrape_page(next_soup, world_production_list, start, end)

    return

if __name__ == "__main__":
    begin_year = 2000
    end_year = get_current_year() - 1

    target = f'https://www.oica.net/category/production-statistics/'
    req = requests.get(target + f'{begin_year}-statistics')

    if req.status_code != 200:
        print("Error")
        exit(0)
    else:
        print(f"Access to website {target}, status = {req.status_code}")

    soup = BeautifulSoup(req.text, "html.parser")

    print(f"Start year {begin_year}; End year : {end_year}")

    world_production_list = []
    scrape_page(soup, world_production_list, begin_year, end_year)
    print(world_production_list)
    convert_to_csv(world_production_list, begin_year, end_year)

Access to website https://www.oica.net/category/production-statistics/, status = 200
Start year 2000; End year : 2023
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2001-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2002-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2003-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2004-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2005-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2006-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2007-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2008-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2009-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2010-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2011-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2012-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2013-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2014-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2015-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2016-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2017-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2018-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2019-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2020-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2021-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2022-statistics
Access to the next page
Next URL : https://www.oica.net/category/production-statistics/2023-statistics
[{'Year': 2000, 'Country_Name': 'Argentina', 'Nbr_Cars': '238,921', 'Nbr_Commercial_Vehicle': '100,711', 'Total': '339,632', 'Percent_Change': '11.4%'}, {'Year': 2000, 'Country_Name': 'Australia', 'Nbr_Cars': '323,649', 'Nbr_Commercial_Vehicle': '23,473', 'Total': '347,122', 'Percent_Change': '14.6%'}, {'Year': 2000, 'Country_Name': 'Austria', 'Nbr_Cars': '115,979', 'Nbr_Commercial_Vehicle': '25,047', 'Total': '141,026', 'Percent_Change': '1.2%'}, {'Year': 2000, 'Country_Name': 'Belgium', 'Nbr_Cars': '912,233', 'Nbr_Commercial_Vehicle': '121,061', 'Total': '1,033,294', 'Percent_Change': '1.6%'}, {'Year': 2000, 'Country_Name': 'Brazil', 'Nbr_Cars': '1,351,998', 'Nbr_Commercial_Vehicle': '329,519', 'Total': '1,681,517', 'Percent_Change': '24.5%'}, {'Year': 2000, 'Country_Name': 'Canada', 'Nbr_Cars': '1,550,500', 'Nbr_Commercial_Vehicle': '1,411,136', 'Total': '2,961,636', 'Percent_Change': '-3.2%'}, {'Year': 2000, 'Country_Name': 'China', 'Nbr_Cars': '604,677', 'Nbr_Commercial_Vehicle': '1,464,392', 'Total': '2,069,069', 'Percent_Change': '13.1%'}, {'Year': 2000, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '428,224', 'Nbr_Commercial_Vehicle': '27,268', 'Total': '455,492', 'Percent_Change': '21.1%'}, {'Year': 2000, 'Country_Name': 'Egypt', 'Nbr_Cars': '39,616', 'Nbr_Commercial_Vehicle': '20,149', 'Total': '59,765', 'Percent_Change': '-21.4%'}, {'Year': 2000, 'Country_Name': 'Finland', 'Nbr_Cars': '38,468', 'Nbr_Commercial_Vehicle': '458', 'Total': '38,926', 'Percent_Change': '13.2%'}, {'Year': 2000, 'Country_Name': 'France', 'Nbr_Cars': '2,879,810', 'Nbr_Commercial_Vehicle': '468,551', 'Total': '3,348,361', 'Percent_Change': '5.3%'}, {'Year': 2000, 'Country_Name': 'Germany', 'Nbr_Cars': '5,131,918', 'Nbr_Commercial_Vehicle': '394,697', 'Total': '5,526,615', 'Percent_Change': '-2.8%'}, {'Year': 2000, 'Country_Name': 'Hungary', 'Nbr_Cars': '134,029', 'Nbr_Commercial_Vehicle': '3,369', 'Total': '137,398', 'Percent_Change': '7.2%'}, {'Year': 2000, 'Country_Name': 'India', 'Nbr_Cars': '517,957', 'Nbr_Commercial_Vehicle': '283,403', 'Total': '801,360', 'Percent_Change': '-2.1%'}, {'Year': 2000, 'Country_Name': 'Indonesia', 'Nbr_Cars': '257,058', 'Nbr_Commercial_Vehicle': '35,652', 'Total': '292,710', 'Percent_Change': '228.9%'}, {'Year': 2000, 'Country_Name': 'Iran', 'Nbr_Cars': '274,985', 'Nbr_Commercial_Vehicle': '3,000', 'Total': '277,985', 'Percent_Change': '132.8%'}, {'Year': 2000, 'Country_Name': 'Italy', 'Nbr_Cars': '1,422,284', 'Nbr_Commercial_Vehicle': '316,031', 'Total': '1,738,315', 'Percent_Change': '2.2%'}, {'Year': 2000, 'Country_Name': 'Japan', 'Nbr_Cars': '8,359,434', 'Nbr_Commercial_Vehicle': '1,781,362', 'Total': '10,140,796', 'Percent_Change': '2.5%'}, {'Year': 2000, 'Country_Name': 'Malaysia', 'Nbr_Cars': '280,283', 'Nbr_Commercial_Vehicle': '2,547', 'Total': '282,830', 'Percent_Change': '11.3%'}, {'Year': 2000, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,279,089', 'Nbr_Commercial_Vehicle': '656,438', 'Total': '1,935,527', 'Percent_Change': '24.9%'}, {'Year': 2000, 'Country_Name': 'Netherlands', 'Nbr_Cars': '215,085', 'Nbr_Commercial_Vehicle': '52,234', 'Total': '267,319', 'Percent_Change': '-13.0%'}, {'Year': 2000, 'Country_Name': 'Poland', 'Nbr_Cars': '481,689', 'Nbr_Commercial_Vehicle': '23,283', 'Total': '504,972', 'Percent_Change': '-12.2%'}, {'Year': 2000, 'Country_Name': 'Portugal', 'Nbr_Cars': '178,509', 'Nbr_Commercial_Vehicle': '68,215', 'Total': '246,724', 'Percent_Change': '-2.2%'}, {'Year': 2000, 'Country_Name': 'Romania', 'Nbr_Cars': '64,181', 'Nbr_Commercial_Vehicle': '13,984', 'Total': '78,165', 'Percent_Change': '-26.9%'}, {'Year': 2000, 'Country_Name': 'Russia', 'Nbr_Cars': '969,235', 'Nbr_Commercial_Vehicle': '236,346', 'Total': '1,205,581', 'Percent_Change': '3.1%'}, {'Year': 2000, 'Country_Name': 'Serbia', 'Nbr_Cars': '11,091', 'Nbr_Commercial_Vehicle': '1,649', 'Total': '12,740', 'Percent_Change': '141.8%'}, {'Year': 2000, 'Country_Name': 'Slovakia', 'Nbr_Cars': '181,333', 'Nbr_Commercial_Vehicle': '450', 'Total': '181,783', 'Percent_Change': '43.3%'}, {'Year': 2000, 'Country_Name': 'Slovenia', 'Nbr_Cars': '122,949', 'Nbr_Commercial_Vehicle': '0', 'Total': '122,949', 'Percent_Change': '4.1%'}, {'Year': 2000, 'Country_Name': 'South Africa', 'Nbr_Cars': '230,577', 'Nbr_Commercial_Vehicle': '126,787', 'Total': '357,364', 'Percent_Change': '12.6%'}, {'Year': 2000, 'Country_Name': 'South Korea', 'Nbr_Cars': '2,602,008', 'Nbr_Commercial_Vehicle': '512,990', 'Total': '3,114,998', 'Percent_Change': '9.6%'}, {'Year': 2000, 'Country_Name': 'Spain', 'Nbr_Cars': '2,366,359', 'Nbr_Commercial_Vehicle': '666,515', 'Total': '3,032,874', 'Percent_Change': '6.3%'}, {'Year': 2000, 'Country_Name': 'Sweden', 'Nbr_Cars': '259,959', 'Nbr_Commercial_Vehicle': '41,384', 'Total': '301,343', 'Percent_Change': '20.2%'}, {'Year': 2000, 'Country_Name': 'Taiwan', 'Nbr_Cars': '263,013', 'Nbr_Commercial_Vehicle': '109,600', 'Total': '372,613', 'Percent_Change': '5.6%'}, {'Year': 2000, 'Country_Name': 'Thailand', 'Nbr_Cars': '97,129', 'Nbr_Commercial_Vehicle': '314,592', 'Total': '411,721', 'Percent_Change': '27.6%'}, {'Year': 2000, 'Country_Name': 'Turkey', 'Nbr_Cars': '297,476', 'Nbr_Commercial_Vehicle': '133,471', 'Total': '430,947', 'Percent_Change': '44.7%'}, {'Year': 2000, 'Country_Name': 'Ukraine', 'Nbr_Cars': '18,124', 'Nbr_Commercial_Vehicle': '13,131', 'Total': '31,255', 'Percent_Change': '63.0%'}, {'Year': 2000, 'Country_Name': 'UK', 'Nbr_Cars': '1,641,452', 'Nbr_Commercial_Vehicle': '172,442', 'Total': '1,813,894', 'Percent_Change': '-8.1%'}, {'Year': 2000, 'Country_Name': 'USA', 'Nbr_Cars': '5,542,217', 'Nbr_Commercial_Vehicle': '7,257,640', 'Total': '12,799,857', 'Percent_Change': '-1.7%'}, {'Year': 2000, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '32,273', 'Nbr_Commercial_Vehicle': '0', 'Total': '32,273', 'Percent_Change': '-27.4%'}, {'Year': 2000, 'Country_Name': 'Others', 'Nbr_Cars': '127,445', 'Nbr_Commercial_Vehicle': '63,204', 'Total': '190,649', 'Percent_Change': '59.3%'}, {'Year': 2001, 'Country_Name': 'Argentina', 'Nbr_Cars': '169,580', 'Nbr_Commercial_Vehicle': '65,978', 'Total': '235,558', 'Percent_Change': '-30.6%'}, {'Year': 2001, 'Country_Name': 'Australia', 'Nbr_Cars': '285,870', 'Nbr_Commercial_Vehicle': '33,505', 'Total': '319,375', 'Percent_Change': '-8.0%'}, {'Year': 2001, 'Country_Name': 'Austria', 'Nbr_Cars': '131,098', 'Nbr_Commercial_Vehicle': '24,305', 'Total': '155,403', 'Percent_Change': '10.2%'}, {'Year': 2001, 'Country_Name': 'Belgium', 'Nbr_Cars': '1,058,656', 'Nbr_Commercial_Vehicle': '128,601', 'Total': '1,187,257', 'Percent_Change': '14.9%'}, {'Year': 2001, 'Country_Name': 'Brazil', 'Nbr_Cars': '1,501,586', 'Nbr_Commercial_Vehicle': '315,651', 'Total': '1,817,237', 'Percent_Change': '8.1%'}, {'Year': 2001, 'Country_Name': 'Canada', 'Nbr_Cars': '1,274,853', 'Nbr_Commercial_Vehicle': '1,257,889', 'Total': '2,532,742', 'Percent_Change': '-14.5%'}, {'Year': 2001, 'Country_Name': 'China', 'Nbr_Cars': '703,521', 'Nbr_Commercial_Vehicle': '1,630,919', 'Total': '2,334,440', 'Percent_Change': '12.8%'}, {'Year': 2001, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '456,927', 'Nbr_Commercial_Vehicle': '8,341', 'Total': '465,268', 'Percent_Change': '2.1%'}, {'Year': 2001, 'Country_Name': 'Egypt', 'Nbr_Cars': '37,006', 'Nbr_Commercial_Vehicle': '19,091', 'Total': '56,097', 'Percent_Change': '-6.1%'}, {'Year': 2001, 'Country_Name': 'Finland', 'Nbr_Cars': '41,916', 'Nbr_Commercial_Vehicle': '404', 'Total': '42,320', 'Percent_Change': '8.7%'}, {'Year': 2001, 'Country_Name': 'France', 'Nbr_Cars': '3,181,549', 'Nbr_Commercial_Vehicle': '446,869', 'Total': '3,628,418', 'Percent_Change': '8.4%'}, {'Year': 2001, 'Country_Name': 'Germany', 'Nbr_Cars': '5,301,189', 'Nbr_Commercial_Vehicle': '390,488', 'Total': '5,691,677', 'Percent_Change': '3.0%'}, {'Year': 2001, 'Country_Name': 'Hungary', 'Nbr_Cars': '140,401', 'Nbr_Commercial_Vehicle': '3,912', 'Total': '144,313', 'Percent_Change': '5.0%'}, {'Year': 2001, 'Country_Name': 'India', 'Nbr_Cars': '654,557', 'Nbr_Commercial_Vehicle': '160,054', 'Total': '814,611', 'Percent_Change': '1.7%'}, {'Year': 2001, 'Country_Name': 'Indonesia', 'Nbr_Cars': '32,237', 'Nbr_Commercial_Vehicle': '246,950', 'Total': '279,187', 'Percent_Change': '-4.6%'}, {'Year': 2001, 'Country_Name': 'Iran', 'Nbr_Cars': '316,334', 'Nbr_Commercial_Vehicle': '6,882', 'Total': '323,216', 'Percent_Change': '16.3%'}, {'Year': 2001, 'Country_Name': 'Italy', 'Nbr_Cars': '1,271,780', 'Nbr_Commercial_Vehicle': '307,916', 'Total': '1,579,696', 'Percent_Change': '-9.1%'}, {'Year': 2001, 'Country_Name': 'Japan', 'Nbr_Cars': '8,117,563', 'Nbr_Commercial_Vehicle': '1,659,628', 'Total': '9,777,191', 'Percent_Change': '-3.6%'}, {'Year': 2001, 'Country_Name': 'Malaysia', 'Nbr_Cars': '344,686', 'Nbr_Commercial_Vehicle': '14,099', 'Total': '358,785', 'Percent_Change': '26.9%'}, {'Year': 2001, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,000,715', 'Nbr_Commercial_Vehicle': '840,293', 'Total': '1,841,008', 'Percent_Change': '-4.9%'}, {'Year': 2001, 'Country_Name': 'Netherlands', 'Nbr_Cars': '189,261', 'Nbr_Commercial_Vehicle': '49,682', 'Total': '238,943', 'Percent_Change': '-10.6%'}, {'Year': 2001, 'Country_Name': 'Poland', 'Nbr_Cars': '335,996', 'Nbr_Commercial_Vehicle': '11,879', 'Total': '347,875', 'Percent_Change': '-31.1%'}, {'Year': 2001, 'Country_Name': 'Portugal', 'Nbr_Cars': '177,357', 'Nbr_Commercial_Vehicle': '62,362', 'Total': '239,719', 'Percent_Change': '-2.8%'}, {'Year': 2001, 'Country_Name': 'Romania', 'Nbr_Cars': '56,774', 'Nbr_Commercial_Vehicle': '11,987', 'Total': '68,761', 'Percent_Change': '-12.0%'}, {'Year': 2001, 'Country_Name': 'Russia', 'Nbr_Cars': '1,021,682', 'Nbr_Commercial_Vehicle': '229,000', 'Total': '1,250,682', 'Percent_Change': '3.7%'}, {'Year': 2001, 'Country_Name': 'Serbia', 'Nbr_Cars': '7,489', 'Nbr_Commercial_Vehicle': '1,490', 'Total': '8,979', 'Percent_Change': '-29.5%'}, {'Year': 2001, 'Country_Name': 'Slovakia', 'Nbr_Cars': '181,644', 'Nbr_Commercial_Vehicle': '359', 'Total': '182,003', 'Percent_Change': '0.1%'}, {'Year': 2001, 'Country_Name': 'Slovenia', 'Nbr_Cars': '116,082', 'Nbr_Commercial_Vehicle': '0', 'Total': '116,082', 'Percent_Change': '-5.6%'}, {'Year': 2001, 'Country_Name': 'South Africa', 'Nbr_Cars': '270,538', 'Nbr_Commercial_Vehicle': '136,498', 'Total': '407,036', 'Percent_Change': '13.9%'}, {'Year': 2001, 'Country_Name': 'South Korea', 'Nbr_Cars': '2,471,444', 'Nbr_Commercial_Vehicle': '474,885', 'Total': '2,946,329', 'Percent_Change': '-5.4%'}, {'Year': 2001, 'Country_Name': 'Spain', 'Nbr_Cars': '2,211,172', 'Nbr_Commercial_Vehicle': '638,716', 'Total': '2,849,888', 'Percent_Change': '-6.0%'}, {'Year': 2001, 'Country_Name': 'Sweden', 'Nbr_Cars': '251,035', 'Nbr_Commercial_Vehicle': '38,112', 'Total': '289,147', 'Percent_Change': '-4.0%'}, {'Year': 2001, 'Country_Name': 'Taiwan', 'Nbr_Cars': '195,109', 'Nbr_Commercial_Vehicle': '76,595', 'Total': '271,704', 'Percent_Change': '-27.1%'}, {'Year': 2001, 'Country_Name': 'Thailand', 'Nbr_Cars': '156,066', 'Nbr_Commercial_Vehicle': '303,352', 'Total': '459,418', 'Percent_Change': '11.6%'}, {'Year': 2001, 'Country_Name': 'Turkey', 'Nbr_Cars': '175,343', 'Nbr_Commercial_Vehicle': '95,342', 'Total': '270,685', 'Percent_Change': '-37.2%'}, {'Year': 2001, 'Country_Name': 'Ukraine', 'Nbr_Cars': '24,995', 'Nbr_Commercial_Vehicle': '6,829', 'Total': '31,824', 'Percent_Change': '1.8%'}, {'Year': 2001, 'Country_Name': 'UK', 'Nbr_Cars': '1,492,365', 'Nbr_Commercial_Vehicle': '192,873', 'Total': '1,685,238', 'Percent_Change': '-7.1%'}, {'Year': 2001, 'Country_Name': 'USA', 'Nbr_Cars': '4,879,119', 'Nbr_Commercial_Vehicle': '6,545,570', 'Total': '11,424,689', 'Percent_Change': '-10.7%'}, {'Year': 2001, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '32,425', 'Nbr_Commercial_Vehicle': '8,580', 'Total': '41,005', 'Percent_Change': '27.1%'}, {'Year': 2001, 'Country_Name': 'Others', 'Nbr_Cars': '121,532', 'Nbr_Commercial_Vehicle': '52,617', 'Total': '174,149', 'Percent_Change': '-8.7%'}, {'Year': 2002, 'Country_Name': 'Argentina', 'Nbr_Cars': '111,340', 'Nbr_Commercial_Vehicle': '48,061', 'Total': '159,401', 'Percent_Change': '-32.3%'}, {'Year': 2002, 'Country_Name': 'Australia', 'Nbr_Cars': '306,876', 'Nbr_Commercial_Vehicle': '36,996', 'Total': '343,872', 'Percent_Change': '7.7%'}, {'Year': 2002, 'Country_Name': 'Austria', 'Nbr_Cars': '132,768', 'Nbr_Commercial_Vehicle': '19,851', 'Total': '152,619', 'Percent_Change': '-1.8%'}, {'Year': 2002, 'Country_Name': 'Belgium', 'Nbr_Cars': '936,903', 'Nbr_Commercial_Vehicle': '120,286', 'Total': '1,057,189', 'Percent_Change': '-11.0%'}, {'Year': 2002, 'Country_Name': 'Brazil', 'Nbr_Cars': '1,520,285', 'Nbr_Commercial_Vehicle': '271,245', 'Total': '1,791,530', 'Percent_Change': '-1.4%'}, {'Year': 2002, 'Country_Name': 'Canada', 'Nbr_Cars': '1,369,042', 'Nbr_Commercial_Vehicle': '1,260,395', 'Total': '2,629,437', 'Percent_Change': '3.8%'}, {'Year': 2002, 'Country_Name': 'China', 'Nbr_Cars': '1,101,696', 'Nbr_Commercial_Vehicle': '2,185,108', 'Total': '3,286,804', 'Percent_Change': '40.8%'}, {'Year': 2002, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '441,312', 'Nbr_Commercial_Vehicle': '5,776', 'Total': '447,088', 'Percent_Change': '-3.9%'}, {'Year': 2002, 'Country_Name': 'Egypt', 'Nbr_Cars': '27,422', 'Nbr_Commercial_Vehicle': '17,751', 'Total': '45,173', 'Percent_Change': '-19.5%'}, {'Year': 2002, 'Country_Name': 'Finland', 'Nbr_Cars': '41,068', 'Nbr_Commercial_Vehicle': '393', 'Total': '41,461', 'Percent_Change': '-2.0%'}, {'Year': 2002, 'Country_Name': 'France', 'Nbr_Cars': '3,292,797', 'Nbr_Commercial_Vehicle': '309,073', 'Total': '3,601,870', 'Percent_Change': '-0.7%'}, {'Year': 2002, 'Country_Name': 'Germany', 'Nbr_Cars': '5,123,238', 'Nbr_Commercial_Vehicle': '346,071', 'Total': '5,469,309', 'Percent_Change': '-3.9%'}, {'Year': 2002, 'Country_Name': 'Hungary', 'Nbr_Cars': '138,239', 'Nbr_Commercial_Vehicle': '3,274', 'Total': '141,513', 'Percent_Change': '-1.9%'}, {'Year': 2002, 'Country_Name': 'India', 'Nbr_Cars': '703,948', 'Nbr_Commercial_Vehicle': '190,848', 'Total': '894,796', 'Percent_Change': '9.8%'}, {'Year': 2002, 'Country_Name': 'Indonesia', 'Nbr_Cars': '193,492', 'Nbr_Commercial_Vehicle': '105,765', 'Total': '299,257', 'Percent_Change': '7.2%'}, {'Year': 2002, 'Country_Name': 'Iran', 'Nbr_Cars': '439,116', 'Nbr_Commercial_Vehicle': '12,959', 'Total': '452,075', 'Percent_Change': '39.9%'}, {'Year': 2002, 'Country_Name': 'Italy', 'Nbr_Cars': '1,125,769', 'Nbr_Commercial_Vehicle': '301,312', 'Total': '1,427,081', 'Percent_Change': '-9.7%'}, {'Year': 2002, 'Country_Name': 'Japan', 'Nbr_Cars': '8,618,354', 'Nbr_Commercial_Vehicle': '1,638,961', 'Total': '10,257,315', 'Percent_Change': '4.9%'}, {'Year': 2002, 'Country_Name': 'Malaysia', 'Nbr_Cars': '380,000', 'Nbr_Commercial_Vehicle': '15,380', 'Total': '395,380', 'Percent_Change': '10.2%'}, {'Year': 2002, 'Country_Name': 'Mexico', 'Nbr_Cars': '960,097', 'Nbr_Commercial_Vehicle': '844,573', 'Total': '1,804,670', 'Percent_Change': '-2.0%'}, {'Year': 2002, 'Country_Name': 'Netherlands', 'Nbr_Cars': '182,368', 'Nbr_Commercial_Vehicle': '48,923', 'Total': '231,291', 'Percent_Change': '-3.2%'}, {'Year': 2002, 'Country_Name': 'Poland', 'Nbr_Cars': '287,534', 'Nbr_Commercial_Vehicle': '23,598', 'Total': '311,132', 'Percent_Change': '-10.6%'}, {'Year': 2002, 'Country_Name': 'Portugal', 'Nbr_Cars': '182,573', 'Nbr_Commercial_Vehicle': '68,259', 'Total': '250,832', 'Percent_Change': '4.6%'}, {'Year': 2002, 'Country_Name': 'Romania', 'Nbr_Cars': '65,266', 'Nbr_Commercial_Vehicle': '14,190', 'Total': '79,456', 'Percent_Change': '15.6%'}, {'Year': 2002, 'Country_Name': 'Russia', 'Nbr_Cars': '980,061', 'Nbr_Commercial_Vehicle': '239,689', 'Total': '1,219,750', 'Percent_Change': '-2.5%'}, {'Year': 2002, 'Country_Name': 'Serbia', 'Nbr_Cars': '10,271', 'Nbr_Commercial_Vehicle': '1,701', 'Total': '11,972', 'Percent_Change': '33.3%'}, {'Year': 2002, 'Country_Name': 'Slovakia', 'Nbr_Cars': '225,442', 'Nbr_Commercial_Vehicle': '276', 'Total': '225,718', 'Percent_Change': '24.0%'}, {'Year': 2002, 'Country_Name': 'Slovenia', 'Nbr_Cars': '126,661', 'Nbr_Commercial_Vehicle': '0', 'Total': '126,661', 'Percent_Change': '9.1%'}, {'Year': 2002, 'Country_Name': 'South Africa', 'Nbr_Cars': '276,499', 'Nbr_Commercial_Vehicle': '127,942', 'Total': '404,441', 'Percent_Change': '-0.6%'}, {'Year': 2002, 'Country_Name': 'South Korea', 'Nbr_Cars': '2,651,273', 'Nbr_Commercial_Vehicle': '496,311', 'Total': '3,147,584', 'Percent_Change': '6.8%'}, {'Year': 2002, 'Country_Name': 'Spain', 'Nbr_Cars': '2,266,902', 'Nbr_Commercial_Vehicle': '588,337', 'Total': '2,855,239', 'Percent_Change': '0.2%'}, {'Year': 2002, 'Country_Name': 'Sweden', 'Nbr_Cars': '237,975', 'Nbr_Commercial_Vehicle': '38,218', 'Total': '276,193', 'Percent_Change': '-4.5%'}, {'Year': 2002, 'Country_Name': 'Taiwan', 'Nbr_Cars': '231,506', 'Nbr_Commercial_Vehicle': '102,193', 'Total': '333,699', 'Percent_Change': '22.8%'}, {'Year': 2002, 'Country_Name': 'Thailand', 'Nbr_Cars': '169,321', 'Nbr_Commercial_Vehicle': '415,630', 'Total': '584,951', 'Percent_Change': '27.3%'}, {'Year': 2002, 'Country_Name': 'Turkey', 'Nbr_Cars': '204,198', 'Nbr_Commercial_Vehicle': '142,367', 'Total': '346,565', 'Percent_Change': '28.0%'}, {'Year': 2002, 'Country_Name': 'Ukraine', 'Nbr_Cars': '50,393', 'Nbr_Commercial_Vehicle': '3,380', 'Total': '53,773', 'Percent_Change': '69.0%'}, {'Year': 2002, 'Country_Name': 'UK', 'Nbr_Cars': '1,629,934', 'Nbr_Commercial_Vehicle': '193,084', 'Total': '1,823,018', 'Percent_Change': '8.2%'}, {'Year': 2002, 'Country_Name': 'USA', 'Nbr_Cars': '5,018,777', 'Nbr_Commercial_Vehicle': '7,260,805', 'Total': '12,279,582', 'Percent_Change': '7.5%'}, {'Year': 2002, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '22,705', 'Nbr_Commercial_Vehicle': '6,849', 'Total': '29,554', 'Percent_Change': '-27.9%'}, {'Year': 2002, 'Country_Name': 'Others', 'Nbr_Cars': '119,255', 'Nbr_Commercial_Vehicle': '49,106', 'Total': '168,361', 'Percent_Change': '-3.3%'}, {'Year': 2003, 'Country_Name': 'Argentina', 'Nbr_Cars': '109,364', 'Nbr_Commercial_Vehicle': '59,812', 'Total': '169,176', 'Percent_Change': '6.1%'}, {'Year': 2003, 'Country_Name': 'Australia', 'Nbr_Cars': '365,611', 'Nbr_Commercial_Vehicle': '47,650', 'Total': '413,261', 'Percent_Change': '20.2%'}, {'Year': 2003, 'Country_Name': 'Austria', 'Nbr_Cars': '118,650', 'Nbr_Commercial_Vehicle': '21,006', 'Total': '139,656', 'Percent_Change': '-8.5%'}, {'Year': 2003, 'Country_Name': 'Belgium', 'Nbr_Cars': '791,703', 'Nbr_Commercial_Vehicle': '112,680', 'Total': '909,383', 'Percent_Change': '-14.5%'}, {'Year': 2003, 'Country_Name': 'Brazil', 'Nbr_Cars': '1,505,139', 'Nbr_Commercial_Vehicle': '322,652', 'Total': '1,827,791', 'Percent_Change': '2.0%'}, {'Year': 2003, 'Country_Name': 'Canada', 'Nbr_Cars': '1,340,175', 'Nbr_Commercial_Vehicle': '1,212,687', 'Total': '2,552,862', 'Percent_Change': '-2.9%'}, {'Year': 2003, 'Country_Name': 'China', 'Nbr_Cars': '2,018,875', 'Nbr_Commercial_Vehicle': '2,424,811', 'Total': '4,443686', 'Percent_Change': '35.2%'}, {'Year': 2003, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '436,279', 'Nbr_Commercial_Vehicle': '5,420', 'Total': '441,699', 'Percent_Change': '-1.2%'}, {'Year': 2003, 'Country_Name': 'Egypt', 'Nbr_Cars': '32,581', 'Nbr_Commercial_Vehicle': '17,431', 'Total': '50,012', 'Percent_Change': '10.7%'}, {'Year': 2003, 'Country_Name': 'Finland', 'Nbr_Cars': '19,226', 'Nbr_Commercial_Vehicle': '432', 'Total': '19,658', 'Percent_Change': '-52.6%'}, {'Year': 2003, 'Country_Name': 'France', 'Nbr_Cars': '3,220,329', 'Nbr_Commercial_Vehicle': '399,737', 'Total': '3,620,066', 'Percent_Change': '0.5%'}, {'Year': 2003, 'Country_Name': 'Germany', 'Nbr_Cars': '5,145,403', 'Nbr_Commercial_Vehicle': '361,226', 'Total': '5,506,629', 'Percent_Change': '0.7%'}, {'Year': 2003, 'Country_Name': 'Hungary', 'Nbr_Cars': '122,338', 'Nbr_Commercial_Vehicle': '3,778', 'Total': '126,116', 'Percent_Change': '-10.9%'}, {'Year': 2003, 'Country_Name': 'India', 'Nbr_Cars': '907,968', 'Nbr_Commercial_Vehicle': '253,555', 'Total': '1,161,523', 'Percent_Change': '29.8%'}, {'Year': 2003, 'Country_Name': 'Indonesia', 'Nbr_Cars': '203,196', 'Nbr_Commercial_Vehicle': '118,848', 'Total': '322,044', 'Percent_Change': '7.6%'}, {'Year': 2003, 'Country_Name': 'Iran', 'Nbr_Cars': '516,930', 'Nbr_Commercial_Vehicle': '65,169', 'Total': '582,099', 'Percent_Change': '28.8%'}, {'Year': 2003, 'Country_Name': 'Italy', 'Nbr_Cars': '1,026,454', 'Nbr_Commercial_Vehicle': '295,177', 'Total': '1,321,631', 'Percent_Change': '-7.4%'}, {'Year': 2003, 'Country_Name': 'Japan', 'Nbr_Cars': '8,478,328', 'Nbr_Commercial_Vehicle': '1,807,890', 'Total': '10,286,218', 'Percent_Change': '0.3%'}, {'Year': 2003, 'Country_Name': 'Malaysia', 'Nbr_Cars': '324,911', 'Nbr_Commercial_Vehicle': '19,373', 'Total': '344,284', 'Percent_Change': '-12.9%'}, {'Year': 2003, 'Country_Name': 'Mexico', 'Nbr_Cars': '774,048', 'Nbr_Commercial_Vehicle': '801,399', 'Total': '1,575,447', 'Percent_Change': '-12.7%'}, {'Year': 2003, 'Country_Name': 'Netherlands', 'Nbr_Cars': '163,080', 'Nbr_Commercial_Vehicle': '52,201', 'Total': '215,281', 'Percent_Change': '-6.9%'}, {'Year': 2003, 'Country_Name': 'Poland', 'Nbr_Cars': '306,847', 'Nbr_Commercial_Vehicle': '15,214', 'Total': '322,061', 'Percent_Change': '3.5%'}, {'Year': 2003, 'Country_Name': 'Portugal', 'Nbr_Cars': '165,576', 'Nbr_Commercial_Vehicle': '73,785', 'Total': '239,361', 'Percent_Change': '-4.6%'}, {'Year': 2003, 'Country_Name': 'Romania', 'Nbr_Cars': '75,706', 'Nbr_Commercial_Vehicle': '19,541', 'Total': '95,247', 'Percent_Change': '19.9%'}, {'Year': 2003, 'Country_Name': 'Russia', 'Nbr_Cars': '1,010,436', 'Nbr_Commercial_Vehicle': '268,356', 'Total': '1,278,792', 'Percent_Change': '4.8%'}, {'Year': 2003, 'Country_Name': 'Serbia', 'Nbr_Cars': '12,996', 'Nbr_Commercial_Vehicle': '907', 'Total': '13,903', 'Percent_Change': '16.1%'}, {'Year': 2003, 'Country_Name': 'Slovakia', 'Nbr_Cars': '281,160', 'Nbr_Commercial_Vehicle': '187', 'Total': '281,347', 'Percent_Change': '24.6%'}, {'Year': 2003, 'Country_Name': 'Slovenia', 'Nbr_Cars': '110,597', 'Nbr_Commercial_Vehicle': '7,602', 'Total': '118,199', 'Percent_Change': '-6.7%'}, {'Year': 2003, 'Country_Name': 'South Africa', 'Nbr_Cars': '291,249', 'Nbr_Commercial_Vehicle': '130,086', 'Total': '421,335', 'Percent_Change': '4.2%'}, {'Year': 2003, 'Country_Name': 'South Korea', 'Nbr_Cars': '2,767,716', 'Nbr_Commercial_Vehicle': '410,154', 'Total': '3,177,870', 'Percent_Change': '1.0%'}, {'Year': 2003, 'Country_Name': 'Spain', 'Nbr_Cars': '2,399,374', 'Nbr_Commercial_Vehicle': '630,452', 'Total': '3,029,826', 'Percent_Change': '6.1%'}, {'Year': 2003, 'Country_Name': 'Sweden', 'Nbr_Cars': '280,394', 'Nbr_Commercial_Vehicle': '42,638', 'Total': '323,032', 'Percent_Change': '17.0%'}, {'Year': 2003, 'Country_Name': 'Taiwan', 'Nbr_Cars': '264,837', 'Nbr_Commercial_Vehicle': '121,849', 'Total': '386,686', 'Percent_Change': '15.9%'}, {'Year': 2003, 'Country_Name': 'Thailand', 'Nbr_Cars': '251,691', 'Nbr_Commercial_Vehicle': '490,371', 'Total': '742,062', 'Percent_Change': '26.9%'}, {'Year': 2003, 'Country_Name': 'Turkey', 'Nbr_Cars': '294,116', 'Nbr_Commercial_Vehicle': '239,238', 'Total': '533,354', 'Percent_Change': '53.9%'}, {'Year': 2003, 'Country_Name': 'Ukraine', 'Nbr_Cars': '103,000', 'Nbr_Commercial_Vehicle': '4,890', 'Total': '107,890', 'Percent_Change': '100.6%'}, {'Year': 2003, 'Country_Name': 'UK', 'Nbr_Cars': '1,657,558', 'Nbr_Commercial_Vehicle': '188,871', 'Total': '1,846,429', 'Percent_Change': '1.3%'}, {'Year': 2003, 'Country_Name': 'USA', 'Nbr_Cars': '4,510,469', 'Nbr_Commercial_Vehicle': '7,604,502', 'Total': '12,114,971', 'Percent_Change': '-1.3%'}, {'Year': 2003, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '39,196', 'Nbr_Commercial_Vehicle': '7,278', 'Total': '46,474', 'Percent_Change': '57.3%'}, {'Year': 2003, 'Country_Name': 'Others', 'Nbr_Cars': '144,607', 'Nbr_Commercial_Vehicle': '66,666', 'Total': '211,753', 'Percent_Change': '25.5%'}, {'Year': 2004, 'Country_Name': 'Argentina', 'Nbr_Cars': '171,400', 'Nbr_Commercial_Vehicle': '89,002', 'Total': '260,402', 'Percent_Change': '53.9%'}, {'Year': 2004, 'Country_Name': 'Australia', 'Nbr_Cars': '337,510', 'Nbr_Commercial_Vehicle': '73,896', 'Total': '411,406', 'Percent_Change': '-0.4%'}, {'Year': 2004, 'Country_Name': 'Austria', 'Nbr_Cars': '227,244', 'Nbr_Commercial_Vehicle': '21,474', 'Total': '248,718', 'Percent_Change': '78.1%'}, {'Year': 2004, 'Country_Name': 'Belgium', 'Nbr_Cars': '857,119', 'Nbr_Commercial_Vehicle': '43,154', 'Total': '900,273', 'Percent_Change': '-0.5%'}, {'Year': 2004, 'Country_Name': 'Brazil', 'Nbr_Cars': '1,862,780', 'Nbr_Commercial_Vehicle': '454,447', 'Total': '2,317,227', 'Percent_Change': '26.8%'}, {'Year': 2004, 'Country_Name': 'Canada', 'Nbr_Cars': '1,335,516', 'Nbr_Commercial_Vehicle': '1,376,020', 'Total': '2,711,536', 'Percent_Change': '6.2%'}, {'Year': 2004, 'Country_Name': 'China', 'Nbr_Cars': '2,480,231', 'Nbr_Commercial_Vehicle': '2,754,265', 'Total': '5,234,496', 'Percent_Change': '17.8%'}, {'Year': 2004, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '443,065', 'Nbr_Commercial_Vehicle': '5,295', 'Total': '448,360', 'Percent_Change': '1.5%'}, {'Year': 2004, 'Country_Name': 'Egypt', 'Nbr_Cars': '34,591', 'Nbr_Commercial_Vehicle': '14,744', 'Total': '49,335', 'Percent_Change': '-1.4%'}, {'Year': 2004, 'Country_Name': 'Finland', 'Nbr_Cars': '10,051', 'Nbr_Commercial_Vehicle': '459', 'Total': '10,510', 'Percent_Change': '-46.5%'}, {'Year': 2004, 'Country_Name': 'France', 'Nbr_Cars': '3,227,416', 'Nbr_Commercial_Vehicle': '438,574', 'Total': '3,665,990', 'Percent_Change': '1.3%'}, {'Year': 2004, 'Country_Name': 'Germany', 'Nbr_Cars': '5,192,101', 'Nbr_Commercial_Vehicle': '377,853', 'Total': '5,569,954', 'Percent_Change': '1.1%'}, {'Year': 2004, 'Country_Name': 'Hungary', 'Nbr_Cars': '118,590', 'Nbr_Commercial_Vehicle': '4,076', 'Total': '122,666', 'Percent_Change': '-2.7%'}, {'Year': 2004, 'Country_Name': 'India', 'Nbr_Cars': '1,178,354', 'Nbr_Commercial_Vehicle': '332,803', 'Total': '1,511,157', 'Percent_Change': '30.1%'}, {'Year': 2004, 'Country_Name': 'Indonesia', 'Nbr_Cars': '262,752', 'Nbr_Commercial_Vehicle': '145,559', 'Total': '408,311', 'Percent_Change': '26.8%'}, {'Year': 2004, 'Country_Name': 'Iran', 'Nbr_Cars': '707,773', 'Nbr_Commercial_Vehicle': '80,885', 'Total': '788,658', 'Percent_Change': '35.5%'}, {'Year': 2004, 'Country_Name': 'Italy', 'Nbr_Cars': '833,578', 'Nbr_Commercial_Vehicle': '308,527', 'Total': '1,142,105', 'Percent_Change': '-13.6%'}, {'Year': 2004, 'Country_Name': 'Japan', 'Nbr_Cars': '8,720,385', 'Nbr_Commercial_Vehicle': '1,791,133', 'Total': '10,511,518', 'Percent_Change': '2.2%'}, {'Year': 2004, 'Country_Name': 'Malaysia', 'Nbr_Cars': '364,852', 'Nbr_Commercial_Vehicle': '107,123', 'Total': '471,975', 'Percent_Change': '37.1%'}, {'Year': 2004, 'Country_Name': 'Mexico', 'Nbr_Cars': '903,313', 'Nbr_Commercial_Vehicle': '673,846', 'Total': '1,577,159', 'Percent_Change': '0.1%'}, {'Year': 2004, 'Country_Name': 'Netherlands', 'Nbr_Cars': '187,600', 'Nbr_Commercial_Vehicle': '59,903', 'Total': '247,503', 'Percent_Change': '15.0%'}, {'Year': 2004, 'Country_Name': 'Poland', 'Nbr_Cars': '523,000', 'Nbr_Commercial_Vehicle': '78,000', 'Total': '601,000', 'Percent_Change': '86.6%'}, {'Year': 2004, 'Country_Name': 'Portugal', 'Nbr_Cars': '150,781', 'Nbr_Commercial_Vehicle': '75,947', 'Total': '226,728', 'Percent_Change': '-5.3%'}, {'Year': 2004, 'Country_Name': 'Romania', 'Nbr_Cars': '98,997', 'Nbr_Commercial_Vehicle': '23,188', 'Total': '122,185', 'Percent_Change': '28.3%'}, {'Year': 2004, 'Country_Name': 'Russia', 'Nbr_Cars': '1,110,079', 'Nbr_Commercial_Vehicle': '276,048', 'Total': '1,386,127', 'Percent_Change': '8.4%'}, {'Year': 2004, 'Country_Name': 'Serbia', 'Nbr_Cars': '13,266', 'Nbr_Commercial_Vehicle': '1,928', 'Total': '15,194', 'Percent_Change': '9.3%'}, {'Year': 2004, 'Country_Name': 'Slovakia', 'Nbr_Cars': '223,542', 'Nbr_Commercial_Vehicle': '0', 'Total': '223,542', 'Percent_Change': '-20.5%'}, {'Year': 2004, 'Country_Name': 'Slovenia', 'Nbr_Cars': '116,609', 'Nbr_Commercial_Vehicle': '15,037', 'Total': '131,646', 'Percent_Change': '11.4%'}, {'Year': 2004, 'Country_Name': 'South Africa', 'Nbr_Cars': '300,963', 'Nbr_Commercial_Vehicle': '154,739', 'Total': '455,702', 'Percent_Change': '8.2%'}, {'Year': 2004, 'Country_Name': 'South Korea', 'Nbr_Cars': '3,122,600', 'Nbr_Commercial_Vehicle': '346,864', 'Total': '3,469,464', 'Percent_Change': '9.2%'}, {'Year': 2004, 'Country_Name': 'Spain', 'Nbr_Cars': '2,402,501', 'Nbr_Commercial_Vehicle': '609,673', 'Total': '3,012,174', 'Percent_Change': '-0.6%'}, {'Year': 2004, 'Country_Name': 'Sweden', 'Nbr_Cars': '290,383', 'Nbr_Commercial_Vehicle': '49,887', 'Total': '340,270', 'Percent_Change': '5.3%'}, {'Year': 2004, 'Country_Name': 'Taiwan', 'Nbr_Cars': '299,639', 'Nbr_Commercial_Vehicle': '131,175', 'Total': '430,814', 'Percent_Change': '11.4%'}, {'Year': 2004, 'Country_Name': 'Thailand', 'Nbr_Cars': '299,439', 'Nbr_Commercial_Vehicle': '628,542', 'Total': '927,981', 'Percent_Change': '25.1%'}, {'Year': 2004, 'Country_Name': 'Turkey', 'Nbr_Cars': '447,152', 'Nbr_Commercial_Vehicle': '376,256', 'Total': '823,408', 'Percent_Change': '54.4%'}, {'Year': 2004, 'Country_Name': 'Ukraine', 'Nbr_Cars': '179,098', 'Nbr_Commercial_Vehicle': '7,792', 'Total': '186,890', 'Percent_Change': '73.2%'}, {'Year': 2004, 'Country_Name': 'UK', 'Nbr_Cars': '1,647,246', 'Nbr_Commercial_Vehicle': '209,293', 'Total': '1,856,539', 'Percent_Change': '0.5%'}, {'Year': 2004, 'Country_Name': 'USA', 'Nbr_Cars': '4,229,625', 'Nbr_Commercial_Vehicle': '7,759,762', 'Total': '11,989,387', 'Percent_Change': '-1.0%'}, {'Year': 2004, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '66,896', 'Nbr_Commercial_Vehicle': '13,833', 'Total': '80,729', 'Percent_Change': '73.7%'}, {'Year': 2004, 'Country_Name': 'Others', 'Nbr_Cars': '226,533', 'Nbr_Commercial_Vehicle': '84,517', 'Total': '311,050', 'Percent_Change': '47.2%'}, {'Year': 2005, 'Country_Name': 'Argentina', 'Nbr_Cars': '182,761', 'Nbr_Commercial_Vehicle': '136,994', 'Total': '319,755', 'Percent_Change': '22.8%'}, {'Year': 2005, 'Country_Name': 'Australia', 'Nbr_Cars': '316,414', 'Nbr_Commercial_Vehicle': '78,299', 'Total': '394,713', 'Percent_Change': '-4.1%'}, {'Year': 2005, 'Country_Name': 'Austria', 'Nbr_Cars': '230,505', 'Nbr_Commercial_Vehicle': '22,774', 'Total': '253,279', 'Percent_Change': '1.8%'}, {'Year': 2005, 'Country_Name': 'Belgium', 'Nbr_Cars': '895,109', 'Nbr_Commercial_Vehicle': '31,406', 'Total': '926,515', 'Percent_Change': '2.9%'}, {'Year': 2005, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,011,817', 'Nbr_Commercial_Vehicle': '519,023', 'Total': '2,530,840', 'Percent_Change': '9.2%'}, {'Year': 2005, 'Country_Name': 'Canada', 'Nbr_Cars': '1,356,271', 'Nbr_Commercial_Vehicle': '1,331,621', 'Total': '2,687,892', 'Percent_Change': '-0.9%'}, {'Year': 2005, 'Country_Name': 'China', 'Nbr_Cars': '3,941,767', 'Nbr_Commercial_Vehicle': '1,775,852', 'Total': '5,717,619', 'Percent_Change': '9.2%'}, {'Year': 2005, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '596,774', 'Nbr_Commercial_Vehicle': '5,463', 'Total': '602,237', 'Percent_Change': '34.3%'}, {'Year': 2005, 'Country_Name': 'Egypt', 'Nbr_Cars': '43,638', 'Nbr_Commercial_Vehicle': '20,911', 'Total': '64,549', 'Percent_Change': '30.8%'}, {'Year': 2005, 'Country_Name': 'Finland', 'Nbr_Cars': '21,233', 'Nbr_Commercial_Vehicle': '411', 'Total': '21,644', 'Percent_Change': '105.9%'}, {'Year': 2005, 'Country_Name': 'France', 'Nbr_Cars': '3,112,961', 'Nbr_Commercial_Vehicle': '436,047', 'Total': '3,549,008', 'Percent_Change': '-3.2%'}, {'Year': 2005, 'Country_Name': 'Germany', 'Nbr_Cars': '5,350,187', 'Nbr_Commercial_Vehicle': '407,523', 'Total': '5,757,710', 'Percent_Change': '3.4%'}, {'Year': 2005, 'Country_Name': 'Hungary', 'Nbr_Cars': '148,533', 'Nbr_Commercial_Vehicle': '3,482', 'Total': '152,015', 'Percent_Change': '23.9%'}, {'Year': 2005, 'Country_Name': 'India', 'Nbr_Cars': '1,264,111', 'Nbr_Commercial_Vehicle': '374,563', 'Total': '1,638,674', 'Percent_Change': '8.4%'}, {'Year': 2005, 'Country_Name': 'Indonesia', 'Nbr_Cars': '332,590', 'Nbr_Commercial_Vehicle': '168,120', 'Total': '500,710', 'Percent_Change': '22.6%'}, {'Year': 2005, 'Country_Name': 'Iran', 'Nbr_Cars': '923,800', 'Nbr_Commercial_Vehicle': '153,390', 'Total': '1,077,190', 'Percent_Change': '36.6%'}, {'Year': 2005, 'Country_Name': 'Italy', 'Nbr_Cars': '725,528', 'Nbr_Commercial_Vehicle': '312,824', 'Total': '1,038,352', 'Percent_Change': '-9.1%'}, {'Year': 2005, 'Country_Name': 'Japan', 'Nbr_Cars': '9,016,735', 'Nbr_Commercial_Vehicle': '1,782,924', 'Total': '10,799,659', 'Percent_Change': '2.7%'}, {'Year': 2005, 'Country_Name': 'Malaysia', 'Nbr_Cars': '404,571', 'Nbr_Commercial_Vehicle': '158,837', 'Total': '563,408', 'Percent_Change': '19.4%'}, {'Year': 2005, 'Country_Name': 'Mexico', 'Nbr_Cars': '846,048', 'Nbr_Commercial_Vehicle': '838,190', 'Total': '1,684,238', 'Percent_Change': '6.8%'}, {'Year': 2005, 'Country_Name': 'Netherlands', 'Nbr_Cars': '115,121', 'Nbr_Commercial_Vehicle': '65,627', 'Total': '180,748', 'Percent_Change': '-27.0%'}, {'Year': 2005, 'Country_Name': 'Poland', 'Nbr_Cars': '540,100', 'Nbr_Commercial_Vehicle': '73,100', 'Total': '613,200', 'Percent_Change': '2.0%'}, {'Year': 2005, 'Country_Name': 'Portugal', 'Nbr_Cars': '137,602', 'Nbr_Commercial_Vehicle': '83,458', 'Total': '221,060', 'Percent_Change': '-2.5%'}, {'Year': 2005, 'Country_Name': 'Romania', 'Nbr_Cars': '174,538', 'Nbr_Commercial_Vehicle': '20,644', 'Total': '194,802', 'Percent_Change': '59.4%'}, {'Year': 2005, 'Country_Name': 'Russia', 'Nbr_Cars': '1,068,511', 'Nbr_Commercial_Vehicle': '285,993', 'Total': '1,354,504', 'Percent_Change': '-2.3%'}, {'Year': 2005, 'Country_Name': 'Serbia', 'Nbr_Cars': '12,574', 'Nbr_Commercial_Vehicle': '1,605', 'Total': '14,179', 'Percent_Change': '-6.7%'}, {'Year': 2005, 'Country_Name': 'Slovakia', 'Nbr_Cars': '218,349', 'Nbr_Commercial_Vehicle': '0', 'Total': '218,349', 'Percent_Change': '-2.3%'}, {'Year': 2005, 'Country_Name': 'Slovenia', 'Nbr_Cars': '138,393', 'Nbr_Commercial_Vehicle': '39,558', 'Total': '177,951', 'Percent_Change': '35.2%'}, {'Year': 2005, 'Country_Name': 'South Africa', 'Nbr_Cars': '324,875', 'Nbr_Commercial_Vehicle': '200,352', 'Total': '525,227', 'Percent_Change': '15.3%'}, {'Year': 2005, 'Country_Name': 'South Korea', 'Nbr_Cars': '3,357,094', 'Nbr_Commercial_Vehicle': '342,256', 'Total': '3,699,350', 'Percent_Change': '6.6%'}, {'Year': 2005, 'Country_Name': 'Spain', 'Nbr_Cars': '2,098,168', 'Nbr_Commercial_Vehicle': '654,332', 'Total': '2,752,500', 'Percent_Change': '-8.6%'}, {'Year': 2005, 'Country_Name': 'Sweden', 'Nbr_Cars': '288,659', 'Nbr_Commercial_Vehicle': '50,570', 'Total': '339,229', 'Percent_Change': '-0.3%'}, {'Year': 2005, 'Country_Name': 'Taiwan', 'Nbr_Cars': '323,819', 'Nbr_Commercial_Vehicle': '122,526', 'Total': '446,345', 'Percent_Change': '3.6%'}, {'Year': 2005, 'Country_Name': 'Thailand', 'Nbr_Cars': '277,562', 'Nbr_Commercial_Vehicle': '845,150', 'Total': '1,122,712', 'Percent_Change': '21.0%'}, {'Year': 2005, 'Country_Name': 'Turkey', 'Nbr_Cars': '453,663', 'Nbr_Commercial_Vehicle': '425,789', 'Total': '879,452', 'Percent_Change': '6.8%'}, {'Year': 2005, 'Country_Name': 'Ukraine', 'Nbr_Cars': '196,722', 'Nbr_Commercial_Vehicle': '19,037', 'Total': '215,759', 'Percent_Change': '15.4%'}, {'Year': 2005, 'Country_Name': 'UK', 'Nbr_Cars': '1,596,356', 'Nbr_Commercial_Vehicle': '206,753', 'Total': '1,803,109', 'Percent_Change': '-2.9%'}, {'Year': 2005, 'Country_Name': 'USA', 'Nbr_Cars': '4,321,272', 'Nbr_Commercial_Vehicle': '7,625,381', 'Total': '11,946,653', 'Percent_Change': '-0.4%'}, {'Year': 2005, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '87,512', 'Nbr_Commercial_Vehicle': '8,302', 'Total': '95,814', 'Percent_Change': '18.7%'}, {'Year': 2005, 'Country_Name': 'Others', 'Nbr_Cars': '372,593', 'Nbr_Commercial_Vehicle': '122,898', 'Total': '495,491', 'Percent_Change': '59.3%'}, {'Year': 2006, 'Country_Name': 'Argentina', 'Nbr_Cars': '263,120', 'Nbr_Commercial_Vehicle': '168,981', 'Total': '432,101', 'Percent_Change': '35,1%'}, {'Year': 2006, 'Country_Name': 'Australia', 'Nbr_Cars': '270,000', 'Nbr_Commercial_Vehicle': '60,900', 'Total': '330,900', 'Percent_Change': '-16,2%'}, {'Year': 2006, 'Country_Name': 'Austria', 'Nbr_Cars': '248,059', 'Nbr_Commercial_Vehicle': '26,873', 'Total': '274,932', 'Percent_Change': '8,6%'}, {'Year': 2006, 'Country_Name': 'Belgium', 'Nbr_Cars': '881,929', 'Nbr_Commercial_Vehicle': '36,127', 'Total': '918,056', 'Percent_Change': '-1,2%'}, {'Year': 2006, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,092,029', 'Nbr_Commercial_Vehicle': '519,005', 'Total': '2,611,034', 'Percent_Change': '3,3%'}, {'Year': 2006, 'Country_Name': 'Canada', 'Nbr_Cars': '1,389,536', 'Nbr_Commercial_Vehicle': '1,182,756', 'Total': '2,572,292', 'Percent_Change': '-4,3%'}, {'Year': 2006, 'Country_Name': 'China', 'Nbr_Cars': '5,233,132', 'Nbr_Commercial_Vehicle': '1,955,576', 'Total': '7,188,708', 'Percent_Change': '25,9%'}, {'Year': 2006, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '848,922', 'Nbr_Commercial_Vehicle': '5,985', 'Total': '854,907', 'Percent_Change': '41,3%'}, {'Year': 2006, 'Country_Name': 'Egypt', 'Nbr_Cars': '59,462', 'Nbr_Commercial_Vehicle': '32,056', 'Total': '91,518', 'Percent_Change': '41,8%'}, {'Year': 2006, 'Country_Name': 'Finland', 'Nbr_Cars': '32,417', 'Nbr_Commercial_Vehicle': '353', 'Total': '32,770', 'Percent_Change': '51,4%'}, {'Year': 2006, 'Country_Name': 'France', 'Nbr_Cars': '2,723,196', 'Nbr_Commercial_Vehicle': '446,023', 'Total': '3,169,219', 'Percent_Change': '-10,7%'}, {'Year': 2006, 'Country_Name': 'Germany', 'Nbr_Cars': '5,398,508', 'Nbr_Commercial_Vehicle': '421,106', 'Total': '5,819,614', 'Percent_Change': '1,1%'}, {'Year': 2006, 'Country_Name': 'Hungary', 'Nbr_Cars': '187,633', 'Nbr_Commercial_Vehicle': '3,190', 'Total': '190,823', 'Percent_Change': '25,5%'}, {'Year': 2006, 'Country_Name': 'India', 'Nbr_Cars': '1,473,000', 'Nbr_Commercial_Vehicle': '546,808', 'Total': '2,019,808', 'Percent_Change': '24,2%'}, {'Year': 2006, 'Country_Name': 'Indonesia', 'Nbr_Cars': '256,285', 'Nbr_Commercial_Vehicle': '40,777', 'Total': '297,062', 'Percent_Change': '-40,7%'}, {'Year': 2006, 'Country_Name': 'Iran', 'Nbr_Cars': '800,000', 'Nbr_Commercial_Vehicle': '104,500', 'Total': '904,500', 'Percent_Change': '10,7%'}, {'Year': 2006, 'Country_Name': 'Italy', 'Nbr_Cars': '892,502', 'Nbr_Commercial_Vehicle': '319,092', 'Total': '1,211,594', 'Percent_Change': '16,7%'}, {'Year': 2006, 'Country_Name': 'Japan', 'Nbr_Cars': '9,756,515', 'Nbr_Commercial_Vehicle': '1,727,718', 'Total': '11,484,233', 'Percent_Change': '6,3%'}, {'Year': 2006, 'Country_Name': 'Malaysia', 'Nbr_Cars': '377,952', 'Nbr_Commercial_Vehicle': '125,021', 'Total': '502,973', 'Percent_Change': '-10,8%'}, {'Year': 2006, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,097,619', 'Nbr_Commercial_Vehicle': '947,899', 'Total': '2,045,518', 'Percent_Change': '22,4%'}, {'Year': 2006, 'Country_Name': 'Netherlands', 'Nbr_Cars': '87,332', 'Nbr_Commercial_Vehicle': '72,122', 'Total': '159,454', 'Percent_Change': '-11,8%'}, {'Year': 2006, 'Country_Name': 'Poland', 'Nbr_Cars': '632,300', 'Nbr_Commercial_Vehicle': '82,300', 'Total': '714,600', 'Percent_Change': '14,2%'}, {'Year': 2006, 'Country_Name': 'Portugal', 'Nbr_Cars': '143,478', 'Nbr_Commercial_Vehicle': '83,847', 'Total': '227,325', 'Percent_Change': '3,7%'}, {'Year': 2006, 'Country_Name': 'Romania', 'Nbr_Cars': '201,663', 'Nbr_Commercial_Vehicle': '11,934', 'Total': '213,597', 'Percent_Change': '9,6%'}, {'Year': 2006, 'Country_Name': 'Russia', 'Nbr_Cars': '1,177,918', 'Nbr_Commercial_Vehicle': '330,440', 'Total': '1,508,358', 'Percent_Change': '11,6%'}, {'Year': 2006, 'Country_Name': 'Serbia', 'Nbr_Cars': '9,832', 'Nbr_Commercial_Vehicle': '1,350', 'Total': '11,182', 'Percent_Change': '-21,1%'}, {'Year': 2006, 'Country_Name': 'Slovakia', 'Nbr_Cars': '295,391', 'Nbr_Commercial_Vehicle': '0', 'Total': '295,391', 'Percent_Change': '35,3%'}, {'Year': 2006, 'Country_Name': 'Slovenia', 'Nbr_Cars': '115,000', 'Nbr_Commercial_Vehicle': '35,320', 'Total': '150,320', 'Percent_Change': '-15,5%'}, {'Year': 2006, 'Country_Name': 'South Africa', 'Nbr_Cars': '334,482', 'Nbr_Commercial_Vehicle': '253,237', 'Total': '587,719', 'Percent_Change': '11,9%'}, {'Year': 2006, 'Country_Name': 'South Korea', 'Nbr_Cars': '3,489,136', 'Nbr_Commercial_Vehicle': '350,966', 'Total': '3,840,102', 'Percent_Change': '3,8%'}, {'Year': 2006, 'Country_Name': 'Spain', 'Nbr_Cars': '2,078,639', 'Nbr_Commercial_Vehicle': '698,796', 'Total': '2,777,435', 'Percent_Change': '0,9%'}, {'Year': 2006, 'Country_Name': 'Sweden', 'Nbr_Cars': '288,583', 'Nbr_Commercial_Vehicle': '44,585', 'Total': '333,168', 'Percent_Change': '-1,6%'}, {'Year': 2006, 'Country_Name': 'Taiwan', 'Nbr_Cars': '211,306', 'Nbr_Commercial_Vehicle': '91,915', 'Total': '303,221', 'Percent_Change': '-32,1%'}, {'Year': 2006, 'Country_Name': 'Thailand', 'Nbr_Cars': '298,819', 'Nbr_Commercial_Vehicle': '895,607', 'Total': '1,194,426', 'Percent_Change': '6,1%'}, {'Year': 2006, 'Country_Name': 'Turkey', 'Nbr_Cars': '545,682', 'Nbr_Commercial_Vehicle': '442,098', 'Total': '987,780', 'Percent_Change': '12,4%'}, {'Year': 2006, 'Country_Name': 'Ukraine', 'Nbr_Cars': '274,860', 'Nbr_Commercial_Vehicle': '20,400', 'Total': '295,260', 'Percent_Change': '36,8%'}, {'Year': 2006, 'Country_Name': 'UK', 'Nbr_Cars': '1,442,085', 'Nbr_Commercial_Vehicle': '206,303', 'Total': '1,648,388', 'Percent_Change': '-8,6%'}, {'Year': 2006, 'Country_Name': 'USA', 'Nbr_Cars': '4,366,220', 'Nbr_Commercial_Vehicle': '6,897,766', 'Total': '11,263,986', 'Percent_Change': '-6,0%'}, {'Year': 2006, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '100,000', 'Nbr_Commercial_Vehicle': '10,000', 'Total': '110,000', 'Percent_Change': '14,8%'}, {'Year': 2006, 'Country_Name': 'Others', 'Nbr_Cars': '376,110', 'Nbr_Commercial_Vehicle': '155,496', 'Total': '531,606', 'Percent_Change': '2.3%'}, {'Year': 2007, 'Country_Name': 'Argentina', 'Nbr_Cars': '350,735', 'Nbr_Commercial_Vehicle': '193,912', 'Total': '544,647', 'Percent_Change': '26.0%'}, {'Year': 2007, 'Country_Name': 'Australia', 'Nbr_Cars': '283,348', 'Nbr_Commercial_Vehicle': '51,269', 'Total': '334,617', 'Percent_Change': '0.9%'}, {'Year': 2007, 'Country_Name': 'Austria', 'Nbr_Cars': '199,969', 'Nbr_Commercial_Vehicle': '28,097', 'Total': '228,066', 'Percent_Change': '-17.0%'}, {'Year': 2007, 'Country_Name': 'Belgium', 'Nbr_Cars': '789,674', 'Nbr_Commercial_Vehicle': '44,729', 'Total': '834,403', 'Percent_Change': '-9.1%'}, {'Year': 2007, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,391,354', 'Nbr_Commercial_Vehicle': '585,796', 'Total': '2,977,150', 'Percent_Change': '14.8%'}, {'Year': 2007, 'Country_Name': 'Canada', 'Nbr_Cars': '1,342,133', 'Nbr_Commercial_Vehicle': '1,236,657', 'Total': '2,578,790', 'Percent_Change': '0.3%'}, {'Year': 2007, 'Country_Name': 'China', 'Nbr_Cars': '6,381,116', 'Nbr_Commercial_Vehicle': '2,501,340', 'Total': '8,882,456', 'Percent_Change': '22.0%'}, {'Year': 2007, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '925,060', 'Nbr_Commercial_Vehicle': '13,588', 'Total': '938,648', 'Percent_Change': '9.8%'}, {'Year': 2007, 'Country_Name': 'Egypt', 'Nbr_Cars': '68,934', 'Nbr_Commercial_Vehicle': '35,539', 'Total': '104,473', 'Percent_Change': '14.2%'}, {'Year': 2007, 'Country_Name': 'Finland', 'Nbr_Cars': '24,000', 'Nbr_Commercial_Vehicle': '303', 'Total': '24,303', 'Percent_Change': '-25.8%'}, {'Year': 2007, 'Country_Name': 'France', 'Nbr_Cars': '2,550,869', 'Nbr_Commercial_Vehicle': '464,985', 'Total': '3,015,854', 'Percent_Change': '-4.8%'}, {'Year': 2007, 'Country_Name': 'Germany', 'Nbr_Cars': '5,709,139', 'Nbr_Commercial_Vehicle': '504,321', 'Total': '6,213,460', 'Percent_Change': '6.8%'}, {'Year': 2007, 'Country_Name': 'Hungary', 'Nbr_Cars': '287,982', 'Nbr_Commercial_Vehicle': '4,045', 'Total': '292,027', 'Percent_Change': '53.5%'}, {'Year': 2007, 'Country_Name': 'India', 'Nbr_Cars': '1,713,479', 'Nbr_Commercial_Vehicle': '540,250', 'Total': '2,253,729', 'Percent_Change': '11.6%'}, {'Year': 2007, 'Country_Name': 'Indonesia', 'Nbr_Cars': '309,208', 'Nbr_Commercial_Vehicle': '102,430', 'Total': '411,638', 'Percent_Change': '38.6%'}, {'Year': 2007, 'Country_Name': 'Iran', 'Nbr_Cars': '882,000', 'Nbr_Commercial_Vehicle': '115,240', 'Total': '997,240', 'Percent_Change': '10.3%'}, {'Year': 2007, 'Country_Name': 'Italy', 'Nbr_Cars': '910,860', 'Nbr_Commercial_Vehicle': '373,452', 'Total': '1,284,312', 'Percent_Change': '6.0%'}, {'Year': 2007, 'Country_Name': 'Japan', 'Nbr_Cars': '9,944,637', 'Nbr_Commercial_Vehicle': '1,651,690', 'Total': '11,596,327', 'Percent_Change': '1.0%'}, {'Year': 2007, 'Country_Name': 'Malaysia', 'Nbr_Cars': '347,971', 'Nbr_Commercial_Vehicle': '93,690', 'Total': '441,661', 'Percent_Change': '-12.2%'}, {'Year': 2007, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,209,097', 'Nbr_Commercial_Vehicle': '886,148', 'Total': '2,095,245', 'Percent_Change': '2.4%'}, {'Year': 2007, 'Country_Name': 'Netherlands', 'Nbr_Cars': '61,912', 'Nbr_Commercial_Vehicle': '76,656', 'Total': '138,568', 'Percent_Change': '-13.1%'}, {'Year': 2007, 'Country_Name': 'Poland', 'Nbr_Cars': '695,000', 'Nbr_Commercial_Vehicle': '97,703', 'Total': '792,703', 'Percent_Change': '10.9%'}, {'Year': 2007, 'Country_Name': 'Portugal', 'Nbr_Cars': '134,047', 'Nbr_Commercial_Vehicle': '42,195', 'Total': '176,242', 'Percent_Change': '-22.5%'}, {'Year': 2007, 'Country_Name': 'Romania', 'Nbr_Cars': '234,103', 'Nbr_Commercial_Vehicle': '7,609', 'Total': '241,712', 'Percent_Change': '13.2%'}, {'Year': 2007, 'Country_Name': 'Russia', 'Nbr_Cars': '1,288,652', 'Nbr_Commercial_Vehicle': '371,468', 'Total': '1,660,120', 'Percent_Change': '10.4%'}, {'Year': 2007, 'Country_Name': 'Serbia', 'Nbr_Cars': '8,236', 'Nbr_Commercial_Vehicle': '1,667', 'Total': '9,903', 'Percent_Change': '-11.4%'}, {'Year': 2007, 'Country_Name': 'Slovakia', 'Nbr_Cars': '571,071', 'Nbr_Commercial_Vehicle': '0', 'Total': '571,071', 'Percent_Change': '93.3%'}, {'Year': 2007, 'Country_Name': 'Slovenia', 'Nbr_Cars': '174,209', 'Nbr_Commercial_Vehicle': '24,193', 'Total': '198,402', 'Percent_Change': '29.6%'}, {'Year': 2007, 'Country_Name': 'South Africa', 'Nbr_Cars': '276,018', 'Nbr_Commercial_Vehicle': '258,472', 'Total': '534,490', 'Percent_Change': '-9.1%'}, {'Year': 2007, 'Country_Name': 'South Korea', 'Nbr_Cars': '3,723,482', 'Nbr_Commercial_Vehicle': '362,826', 'Total': '4,086,308', 'Percent_Change': '6.4%'}, {'Year': 2007, 'Country_Name': 'Spain', 'Nbr_Cars': '2,195,780', 'Nbr_Commercial_Vehicle': '693,923', 'Total': '2,889,703', 'Percent_Change': '4.0%'}, {'Year': 2007, 'Country_Name': 'Sweden', 'Nbr_Cars': '316,850', 'Nbr_Commercial_Vehicle': '49,170', 'Total': '366,020', 'Percent_Change': '9.9%'}, {'Year': 2007, 'Country_Name': 'Taiwan', 'Nbr_Cars': '212,685', 'Nbr_Commercial_Vehicle': '70,354', 'Total': '283,039', 'Percent_Change': '-6.7%'}, {'Year': 2007, 'Country_Name': 'Thailand', 'Nbr_Cars': '315,444', 'Nbr_Commercial_Vehicle': '971,902', 'Total': '1,287,346', 'Percent_Change': '7.8%'}, {'Year': 2007, 'Country_Name': 'Turkey', 'Nbr_Cars': '634,883', 'Nbr_Commercial_Vehicle': '464,530', 'Total': '1,099,413', 'Percent_Change': '11.3%'}, {'Year': 2007, 'Country_Name': 'Ukraine', 'Nbr_Cars': '380,061', 'Nbr_Commercial_Vehicle': '22,530', 'Total': '402,591', 'Percent_Change': '39.7%'}, {'Year': 2007, 'Country_Name': 'UK', 'Nbr_Cars': '1,534,567', 'Nbr_Commercial_Vehicle': '215,686', 'Total': '1,750,253', 'Percent_Change': '6.1%'}, {'Year': 2007, 'Country_Name': 'USA', 'Nbr_Cars': '3,924,268', 'Nbr_Commercial_Vehicle': '6,856,461', 'Total': '10,780,729', 'Percent_Change': '-4.5%'}, {'Year': 2007, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '170,000', 'Nbr_Commercial_Vehicle': '14,900', 'Total': '184,900', 'Percent_Change': '68.1%'}, {'Year': 2007, 'Country_Name': 'Others', 'Nbr_Cars': '420,770', 'Nbr_Commercial_Vehicle': '282,019', 'Total': '702789', 'Percent_Change': '32.2%'}, {'Year': 2008, 'Country_Name': 'Argentina', 'Nbr_Cars': '399,236', 'Nbr_Commercial_Vehicle': '197,509', 'Total': '596,745', 'Percent_Change': '9.6%'}, {'Year': 2008, 'Country_Name': 'Australia', 'Nbr_Cars': '285,590', 'Nbr_Commercial_Vehicle': '43,966', 'Total': '329,556', 'Percent_Change': '-1.5%'}, {'Year': 2008, 'Country_Name': 'Austria', 'Nbr_Cars': '125,836', 'Nbr_Commercial_Vehicle': '25,441', 'Total': '151,277', 'Percent_Change': '-33.7%'}, {'Year': 2008, 'Country_Name': 'Belgium', 'Nbr_Cars': '680,131', 'Nbr_Commercial_Vehicle': '44,367', 'Total': '724,498', 'Percent_Change': '-13.2%'}, {'Year': 2008, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,545,729', 'Nbr_Commercial_Vehicle': '670,247', 'Total': '3,215,976', 'Percent_Change': '8.0%'}, {'Year': 2008, 'Country_Name': 'Canada', 'Nbr_Cars': '1,195,436', 'Nbr_Commercial_Vehicle': '886,805', 'Total': '2,082,241', 'Percent_Change': '-19.3%'}, {'Year': 2008, 'Country_Name': 'China', 'Nbr_Cars': '6,737,745', 'Nbr_Commercial_Vehicle': '2,561,435', 'Total': '9,299,180', 'Percent_Change': '4.7%'}, {'Year': 2008, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '934,046', 'Nbr_Commercial_Vehicle': '12,521', 'Total': '946,567', 'Percent_Change': '1.0%'}, {'Year': 2008, 'Country_Name': 'Egypt', 'Nbr_Cars': '77,563', 'Nbr_Commercial_Vehicle': '42,297', 'Total': '119,860', 'Percent_Change': '14.7%'}, {'Year': 2008, 'Country_Name': 'Finland', 'Nbr_Cars': '17,519', 'Nbr_Commercial_Vehicle': '376', 'Total': '17,895', 'Percent_Change': '-26.4%'}, {'Year': 2008, 'Country_Name': 'France', 'Nbr_Cars': '2,145,935', 'Nbr_Commercial_Vehicle': '423,043', 'Total': '2,568,978', 'Percent_Change': '-14.8%'}, {'Year': 2008, 'Country_Name': 'Germany', 'Nbr_Cars': '5,532,030', 'Nbr_Commercial_Vehicle': '513,700', 'Total': '6,045,730', 'Percent_Change': '-2.7%'}, {'Year': 2008, 'Country_Name': 'Hungary', 'Nbr_Cars': '342,359', 'Nbr_Commercial_Vehicle': '3,696', 'Total': '346,055', 'Percent_Change': '18.5%'}, {'Year': 2008, 'Country_Name': 'India', 'Nbr_Cars': '1,846,051', 'Nbr_Commercial_Vehicle': '486,277', 'Total': '2,332,328', 'Percent_Change': '3.5%'}, {'Year': 2008, 'Country_Name': 'Indonesia', 'Nbr_Cars': '431,423', 'Nbr_Commercial_Vehicle': '169,205', 'Total': '600,628', 'Percent_Change': '45.9%'}, {'Year': 2008, 'Country_Name': 'Iran', 'Nbr_Cars': '1,048,307', 'Nbr_Commercial_Vehicle': '225,474', 'Total': '1,273,781', 'Percent_Change': '27.7%'}, {'Year': 2008, 'Country_Name': 'Italy', 'Nbr_Cars': '659,221', 'Nbr_Commercial_Vehicle': '364,553', 'Total': '1,023,774', 'Percent_Change': '-20.3%'}, {'Year': 2008, 'Country_Name': 'Japan', 'Nbr_Cars': '9,928,143', 'Nbr_Commercial_Vehicle': '1,647,501', 'Total': '11,575,644', 'Percent_Change': '-0.2%'}, {'Year': 2008, 'Country_Name': 'Malaysia', 'Nbr_Cars': '484,512', 'Nbr_Commercial_Vehicle': '46,298', 'Total': '530,810', 'Percent_Change': '20.2%'}, {'Year': 2008, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,217,458', 'Nbr_Commercial_Vehicle': '950,486', 'Total': '2,167,944', 'Percent_Change': '3.5%'}, {'Year': 2008, 'Country_Name': 'Netherlands', 'Nbr_Cars': '59,223', 'Nbr_Commercial_Vehicle': '73,271', 'Total': '132,494', 'Percent_Change': '-4.4%'}, {'Year': 2008, 'Country_Name': 'Poland', 'Nbr_Cars': '842,000', 'Nbr_Commercial_Vehicle': '110,840', 'Total': '952,840', 'Percent_Change': '20.2%'}, {'Year': 2008, 'Country_Name': 'Portugal', 'Nbr_Cars': '132,242', 'Nbr_Commercial_Vehicle': '42,913', 'Total': '175,155', 'Percent_Change': '-0.6%'}, {'Year': 2008, 'Country_Name': 'Romania', 'Nbr_Cars': '231,056', 'Nbr_Commercial_Vehicle': '14,252', 'Total': '245,308', 'Percent_Change': '1.5%'}, {'Year': 2008, 'Country_Name': 'Russia', 'Nbr_Cars': '1,469,429', 'Nbr_Commercial_Vehicle': '320,872', 'Total': '1,790,301', 'Percent_Change': '7.8%'}, {'Year': 2008, 'Country_Name': 'Serbia', 'Nbr_Cars': '9,818', 'Nbr_Commercial_Vehicle': '1,810', 'Total': '11,628', 'Percent_Change': '17.4%'}, {'Year': 2008, 'Country_Name': 'Slovakia', 'Nbr_Cars': '575,776', 'Nbr_Commercial_Vehicle': '0', 'Total': '575,776', 'Percent_Change': '0.8%'}, {'Year': 2008, 'Country_Name': 'Slovenia', 'Nbr_Cars': '180,233', 'Nbr_Commercial_Vehicle': '17,610', 'Total': '197,843', 'Percent_Change': '-0.3%'}, {'Year': 2008, 'Country_Name': 'South Africa', 'Nbr_Cars': '321,124', 'Nbr_Commercial_Vehicle': '241,841', 'Total': '562,965', 'Percent_Change': '5.3%'}, {'Year': 2008, 'Country_Name': 'South Korea', 'Nbr_Cars': '3,450,478', 'Nbr_Commercial_Vehicle': '376,204', 'Total': '3,826,682', 'Percent_Change': '-6.8%'}, {'Year': 2008, 'Country_Name': 'Spain', 'Nbr_Cars': '1,943,049', 'Nbr_Commercial_Vehicle': '598,595', 'Total': '2,541,644', 'Percent_Change': '-12.0%'}, {'Year': 2008, 'Country_Name': 'Sweden', 'Nbr_Cars': '252,287', 'Nbr_Commercial_Vehicle': '56,012', 'Total': '308,299', 'Percent_Change': '-15.8%'}, {'Year': 2008, 'Country_Name': 'Taiwan', 'Nbr_Cars': '138,714', 'Nbr_Commercial_Vehicle': '44,260', 'Total': '182,974', 'Percent_Change': '-35.4%'}, {'Year': 2008, 'Country_Name': 'Thailand', 'Nbr_Cars': '401,309', 'Nbr_Commercial_Vehicle': '992,433', 'Total': '1,393,742', 'Percent_Change': '8.3%'}, {'Year': 2008, 'Country_Name': 'Turkey', 'Nbr_Cars': '621,567', 'Nbr_Commercial_Vehicle': '525,543', 'Total': '1,147,110', 'Percent_Change': '4.3%'}, {'Year': 2008, 'Country_Name': 'Ukraine', 'Nbr_Cars': '400,799', 'Nbr_Commercial_Vehicle': '22,328', 'Total': '423,127', 'Percent_Change': '5.1%'}, {'Year': 2008, 'Country_Name': 'UK', 'Nbr_Cars': '1,446,619', 'Nbr_Commercial_Vehicle': '202,896', 'Total': '1,649,515', 'Percent_Change': '-5.8%'}, {'Year': 2008, 'Country_Name': 'USA', 'Nbr_Cars': '3,776,641', 'Nbr_Commercial_Vehicle': '4,895,500', 'Total': '8,672,141', 'Percent_Change': '-19.6%'}, {'Year': 2008, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '195,038', 'Nbr_Commercial_Vehicle': '13,000', 'Total': '208,038', 'Percent_Change': '12.5%'}, {'Year': 2008, 'Country_Name': 'Supplementary', 'Nbr_Cars': '365,165', 'Nbr_Commercial_Vehicle': '162,469', 'Total': '527,634', 'Percent_Change': '-11.8%'}, {'Year': 2009, 'Country_Name': 'Argentina', 'Nbr_Cars': '380,067', 'Nbr_Commercial_Vehicle': '132,857', 'Total': '512,924', 'Percent_Change': '-14.1%'}, {'Year': 2009, 'Country_Name': 'Australia', 'Nbr_Cars': '188,158', 'Nbr_Commercial_Vehicle': '39,125', 'Total': '227,283', 'Percent_Change': '-31.0%'}, {'Year': 2009, 'Country_Name': 'Austria', 'Nbr_Cars': '56,620', 'Nbr_Commercial_Vehicle': '15,714', 'Total': '72,334', 'Percent_Change': '-52.2%'}, {'Year': 2009, 'Country_Name': 'Belgium', 'Nbr_Cars': '524,595', 'Nbr_Commercial_Vehicle': '12,510', 'Total': '537,354', 'Percent_Change': '-25.8%'}, {'Year': 2009, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,575,418', 'Nbr_Commercial_Vehicle': '607,505', 'Total': '3,182,923', 'Percent_Change': '-1.0%'}, {'Year': 2009, 'Country_Name': 'Canada', 'Nbr_Cars': '822,267', 'Nbr_Commercial_Vehicle': '668,215', 'Total': '1,490,482', 'Percent_Change': '-28.4%'}, {'Year': 2009, 'Country_Name': 'China', 'Nbr_Cars': '10,383,831', 'Nbr_Commercial_Vehicle': '3,407,163', 'Total': '13,790,994', 'Percent_Change': '48.3%'}, {'Year': 2009, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '976,435', 'Nbr_Commercial_Vehicle': '6,810', 'Total': '983,243', 'Percent_Change': '3.9%'}, {'Year': 2009, 'Country_Name': 'Egypt', 'Nbr_Cars': '60,249', 'Nbr_Commercial_Vehicle': '32,090', 'Total': '92,339', 'Percent_Change': '-23.0%'}, {'Year': 2009, 'Country_Name': 'Finland', 'Nbr_Cars': '10,907', 'Nbr_Commercial_Vehicle': '64', 'Total': '10,971', 'Percent_Change': '-38.7%'}, {'Year': 2009, 'Country_Name': 'France', 'Nbr_Cars': '1,819,497', 'Nbr_Commercial_Vehicle': '228,196', 'Total': '2,047,693', 'Percent_Change': '-20.3%'}, {'Year': 2009, 'Country_Name': 'Germany', 'Nbr_Cars': '4,964,523', 'Nbr_Commercial_Vehicle': '245,334', 'Total': '5,209,857', 'Percent_Change': '-13.8%'}, {'Year': 2009, 'Country_Name': 'Hungary', 'Nbr_Cars': '212,773', 'Nbr_Commercial_Vehicle': '1,770', 'Total': '214,543', 'Percent_Change': '-38.0%'}, {'Year': 2009, 'Country_Name': 'India', 'Nbr_Cars': '2,175,220', 'Nbr_Commercial_Vehicle': '466,330', 'Total': '2,641,550', 'Percent_Change': '13.3%'}, {'Year': 2009, 'Country_Name': 'Indonesia', 'Nbr_Cars': '352,172', 'Nbr_Commercial_Vehicle': '112,644', 'Total': '464,816', 'Percent_Change': '-22.6%'}, {'Year': 2009, 'Country_Name': 'Iran', 'Nbr_Cars': '1,170,503', 'Nbr_Commercial_Vehicle': '223,572', 'Total': '1,394,075', 'Percent_Change': '9.4%'}, {'Year': 2009, 'Country_Name': 'Italy', 'Nbr_Cars': '661,100', 'Nbr_Commercial_Vehicle': '182,139', 'Total': '843,239', 'Percent_Change': '-17.6%'}, {'Year': 2009, 'Country_Name': 'Japan', 'Nbr_Cars': '6,862,161', 'Nbr_Commercial_Vehicle': '1,071,896', 'Total': '7,934,057', 'Percent_Change': '-31.5%'}, {'Year': 2009, 'Country_Name': 'Malaysia', 'Nbr_Cars': '447,002', 'Nbr_Commercial_Vehicle': '42,267', 'Total': '489,269', 'Percent_Change': '-7.8%'}, {'Year': 2009, 'Country_Name': 'Mexico', 'Nbr_Cars': '942,876', 'Nbr_Commercial_Vehicle': '618,176', 'Total': '1,561,052', 'Percent_Change': '-28.0%'}, {'Year': 2009, 'Country_Name': 'Netherlands', 'Nbr_Cars': '50,620', 'Nbr_Commercial_Vehicle': '26,131', 'Total': '76,751', 'Percent_Change': '-42.1%'}, {'Year': 2009, 'Country_Name': 'Poland', 'Nbr_Cars': '818,800', 'Nbr_Commercial_Vehicle': '60,198', 'Total': '878,998', 'Percent_Change': '-7.7%'}, {'Year': 2009, 'Country_Name': 'Portugal', 'Nbr_Cars': '101,680', 'Nbr_Commercial_Vehicle': '24,335', 'Total': '126,015', 'Percent_Change': '-28.1%'}, {'Year': 2009, 'Country_Name': 'Romania', 'Nbr_Cars': '279,320', 'Nbr_Commercial_Vehicle': '17,178', 'Total': '296,498', 'Percent_Change': '20.9%'}, {'Year': 2009, 'Country_Name': 'Russia', 'Nbr_Cars': '599,265', 'Nbr_Commercial_Vehicle': '125,747', 'Total': '725,012', 'Percent_Change': '-59.5%'}, {'Year': 2009, 'Country_Name': 'Serbia', 'Nbr_Cars': '16,337', 'Nbr_Commercial_Vehicle': '401', 'Total': '16,738', 'Percent_Change': '43.9%'}, {'Year': 2009, 'Country_Name': 'Slovakia', 'Nbr_Cars': '461,340', 'Nbr_Commercial_Vehicle': '0', 'Total': '461,340', 'Percent_Change': '-19.9%'}, {'Year': 2009, 'Country_Name': 'Slovenia', 'Nbr_Cars': '202,570', 'Nbr_Commercial_Vehicle': '10,179', 'Total': '212,749', 'Percent_Change': '7.5%'}, {'Year': 2009, 'Country_Name': 'South Africa', 'Nbr_Cars': '222,981', 'Nbr_Commercial_Vehicle': '150,942', 'Total': '373,923', 'Percent_Change': '-33.6%'}, {'Year': 2009, 'Country_Name': 'South Korea', 'Nbr_Cars': '3,158,417', 'Nbr_Commercial_Vehicle': '354,509', 'Total': '3,512,926', 'Percent_Change': '-8.2%'}, {'Year': 2009, 'Country_Name': 'Spain', 'Nbr_Cars': '1,812,688', 'Nbr_Commercial_Vehicle': '357,390', 'Total': '2,170,078', 'Percent_Change': '-14.6%'}, {'Year': 2009, 'Country_Name': 'Sweden', 'Nbr_Cars': '128,738', 'Nbr_Commercial_Vehicle': '27,698', 'Total': '156,436', 'Percent_Change': '-49.3%'}, {'Year': 2009, 'Country_Name': 'Taiwan', 'Nbr_Cars': '183,986', 'Nbr_Commercial_Vehicle': '42,370', 'Total': '226,356', 'Percent_Change': '23.7%'}, {'Year': 2009, 'Country_Name': 'Thailand', 'Nbr_Cars': '313,442', 'Nbr_Commercial_Vehicle': '685,936', 'Total': '999,378', 'Percent_Change': '-28.3%'}, {'Year': 2009, 'Country_Name': 'Turkey', 'Nbr_Cars': '510,931', 'Nbr_Commercial_Vehicle': '358,674', 'Total': '869,605', 'Percent_Change': '-24.2%'}, {'Year': 2009, 'Country_Name': 'Ukraine', 'Nbr_Cars': '65,646', 'Nbr_Commercial_Vehicle': '3,649', 'Total': '69,295', 'Percent_Change': '-83.6%'}, {'Year': 2009, 'Country_Name': 'UK', 'Nbr_Cars': '999,460', 'Nbr_Commercial_Vehicle': '90,679', 'Total': '1,090,139', 'Percent_Change': '-33.9%'}, {'Year': 2009, 'Country_Name': 'USA', 'Nbr_Cars': '2,195,588', 'Nbr_Commercial_Vehicle': '3,513,843', 'Total': '5,709,431', 'Percent_Change': '-34.3%'}, {'Year': 2009, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '110,200', 'Nbr_Commercial_Vehicle': '7,700', 'Total': '117,900', 'Percent_Change': '-43.3%'}, {'Year': 2009, 'Country_Name': 'Others', 'Nbr_Cars': '302,354', 'Nbr_Commercial_Vehicle': '105,010', 'Total': '407,364', 'Percent_Change': '-23.4%'}, {'Year': 2010, 'Country_Name': 'Argentina', 'Nbr_Cars': '508,401', 'Nbr_Commercial_Vehicle': '208,139', 'Total': '716,540', 'Percent_Change': '39.7%'}, {'Year': 2010, 'Country_Name': 'Australia', 'Nbr_Cars': '205,334', 'Nbr_Commercial_Vehicle': '38,673', 'Total': '244,007', 'Percent_Change': '7.4%'}, {'Year': 2010, 'Country_Name': 'Austria', 'Nbr_Cars': '86,183', 'Nbr_Commercial_Vehicle': '18,814', 'Total': '104,997', 'Percent_Change': '45.2%'}, {'Year': 2010, 'Country_Name': 'Belgium', 'Nbr_Cars': '528,996', 'Nbr_Commercial_Vehicle': '26,306', 'Total': '555,302', 'Percent_Change': '3.3%'}, {'Year': 2010, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,584,690', 'Nbr_Commercial_Vehicle': '797,038', 'Total': '3,381,728', 'Percent_Change': '6.2%'}, {'Year': 2010, 'Country_Name': 'Canada', 'Nbr_Cars': '967,077', 'Nbr_Commercial_Vehicle': '1,101,112', 'Total': '2,068,189', 'Percent_Change': '38.8%'}, {'Year': 2010, 'Country_Name': 'China', 'Nbr_Cars': '13,897,083', 'Nbr_Commercial_Vehicle': '4,367,678', 'Total': '18,264,761', 'Percent_Change': '32.4%'}, {'Year': 2010, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1,069,518', 'Nbr_Commercial_Vehicle': '6,866', 'Total': '1,076,384', 'Percent_Change': '9.5%'}, {'Year': 2010, 'Country_Name': 'Egypt', 'Nbr_Cars': '76,412', 'Nbr_Commercial_Vehicle': '40,271', 'Total': '116,683', 'Percent_Change': '26.4%'}, {'Year': 2010, 'Country_Name': 'Finland', 'Nbr_Cars': '6,385', 'Nbr_Commercial_Vehicle': '280', 'Total': '6,665', 'Percent_Change': '-39.2%'}, {'Year': 2010, 'Country_Name': 'France', 'Nbr_Cars': '1,924,171', 'Nbr_Commercial_Vehicle': '305,250', 'Total': '2,229,421', 'Percent_Change': '8.9%'}, {'Year': 2010, 'Country_Name': 'Germany', 'Nbr_Cars': '5,552,409', 'Nbr_Commercial_Vehicle': '353,576', 'Total': '5,905,985', 'Percent_Change': '13.4%'}, {'Year': 2010, 'Country_Name': 'Hungary', 'Nbr_Cars': '208,571', 'Nbr_Commercial_Vehicle': '2,890', 'Total': '211,461', 'Percent_Change': '-1.4%'}, {'Year': 2010, 'Country_Name': 'India', 'Nbr_Cars': '2,831,542', 'Nbr_Commercial_Vehicle': '725,531', 'Total': '3,557,073', 'Percent_Change': '34.7%'}, {'Year': 2010, 'Country_Name': 'Indonesia', 'Nbr_Cars': '496,524', 'Nbr_Commercial_Vehicle': '205,984', 'Total': '702,508', 'Percent_Change': '51.1%'}, {'Year': 2010, 'Country_Name': 'Iran', 'Nbr_Cars': '1,367,014', 'Nbr_Commercial_Vehicle': '232,440', 'Total': '1,599,454', 'Percent_Change': '14.7%'}, {'Year': 2010, 'Country_Name': 'Italy', 'Nbr_Cars': '573,169', 'Nbr_Commercial_Vehicle': '265,017', 'Total': '838,186', 'Percent_Change': '-0.6%'}, {'Year': 2010, 'Country_Name': 'Japan', 'Nbr_Cars': '8,310,362', 'Nbr_Commercial_Vehicle': '1,318,558', 'Total': '9,628,920', 'Percent_Change': '21.4%'}, {'Year': 2010, 'Country_Name': 'Malaysia', 'Nbr_Cars': '522,568', 'Nbr_Commercial_Vehicle': '45,147', 'Total': '567,715', 'Percent_Change': '16.0%'}, {'Year': 2010, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,386,148', 'Nbr_Commercial_Vehicle': '956,134', 'Total': '2,342,282', 'Percent_Change': '50.0%'}, {'Year': 2010, 'Country_Name': 'Netherlands', 'Nbr_Cars': '48,025', 'Nbr_Commercial_Vehicle': '46,107', 'Total': '94,132', 'Percent_Change': '22.6%'}, {'Year': 2010, 'Country_Name': 'Poland', 'Nbr_Cars': '785,000', 'Nbr_Commercial_Vehicle': '84,474', 'Total': '869,474', 'Percent_Change': '-1.1%'}, {'Year': 2010, 'Country_Name': 'Portugal', 'Nbr_Cars': '114,563', 'Nbr_Commercial_Vehicle': '44,166', 'Total': '158,729', 'Percent_Change': '26.0%'}, {'Year': 2010, 'Country_Name': 'Romania', 'Nbr_Cars': '323,587', 'Nbr_Commercial_Vehicle': '27,325', 'Total': '350,912', 'Percent_Change': '18.4%'}, {'Year': 2010, 'Country_Name': 'Russia', 'Nbr_Cars': '1,208,362', 'Nbr_Commercial_Vehicle': '194,882', 'Total': '1,403,244', 'Percent_Change': '93.5%'}, {'Year': 2010, 'Country_Name': 'Serbia', 'Nbr_Cars': '14,551', 'Nbr_Commercial_Vehicle': '649', 'Total': '15,200', 'Percent_Change': '-9.2%%'}, {'Year': 2010, 'Country_Name': 'Slovakia', 'Nbr_Cars': '561,933', 'Nbr_Commercial_Vehicle': '0', 'Total': '561,933', 'Percent_Change': '21.8%'}, {'Year': 2010, 'Country_Name': 'Slovenia', 'Nbr_Cars': '201,039', 'Nbr_Commercial_Vehicle': '10,301', 'Total': '211,340', 'Percent_Change': '-0.7%'}, {'Year': 2010, 'Country_Name': 'South Africa', 'Nbr_Cars': '295,394', 'Nbr_Commercial_Vehicle': '176,655', 'Total': '472,049', 'Percent_Change': '26.2%'}, {'Year': 2010, 'Country_Name': 'South Korea', 'Nbr_Cars': '3,866,206', 'Nbr_Commercial_Vehicle': '405,535', 'Total': '4,271,741', 'Percent_Change': '21.6%'}, {'Year': 2010, 'Country_Name': 'Spain', 'Nbr_Cars': '1,913,513', 'Nbr_Commercial_Vehicle': '474,387', 'Total': '2,387,900', 'Percent_Change': '10.0%'}, {'Year': 2010, 'Country_Name': 'Sweden', 'Nbr_Cars': '177,084', 'Nbr_Commercial_Vehicle': '40,000', 'Total': '217,084', 'Percent_Change': '38.8%'}, {'Year': 2010, 'Country_Name': 'Taiwan', 'Nbr_Cars': '251,490', 'Nbr_Commercial_Vehicle': '51,966', 'Total': '303,456', 'Percent_Change': '34.1%'}, {'Year': 2010, 'Country_Name': 'Thailand', 'Nbr_Cars': '554,387', 'Nbr_Commercial_Vehicle': '1,090,126', 'Total': '1,644,513', 'Percent_Change': '64.6%'}, {'Year': 2010, 'Country_Name': 'Turkey', 'Nbr_Cars': '603,394', 'Nbr_Commercial_Vehicle': '491,163', 'Total': '1,094,557', 'Percent_Change': '25.9%'}, {'Year': 2010, 'Country_Name': 'Ukraine', 'Nbr_Cars': '75,261', 'Nbr_Commercial_Vehicle': '7,872', 'Total': '83,133', 'Percent_Change': '20.0%'}, {'Year': 2010, 'Country_Name': 'UK', 'Nbr_Cars': '1,270,444', 'Nbr_Commercial_Vehicle': '123,019', 'Total': '1,393,463', 'Percent_Change': '27.8%'}, {'Year': 2010, 'Country_Name': 'USA', 'Nbr_Cars': '2,731,105', 'Nbr_Commercial_Vehicle': '5,011,988', 'Total': '7,743,093', 'Percent_Change': '35.6%'}, {'Year': 2010, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '130,400', 'Nbr_Commercial_Vehicle': '26,480', 'Total': '156,880', 'Percent_Change': '33.1%'}, {'Year': 2010, 'Country_Name': 'Others', 'Nbr_Cars': '373,587', 'Nbr_Commercial_Vehicle': '113,198', 'Total': '486,785', 'Percent_Change': '21.5%'}, {'Year': 2011, 'Country_Name': 'Argentina', 'Nbr_Cars': '577,233', 'Nbr_Commercial_Vehicle': '251,538', 'Total': '828,771', 'Percent_Change': '15.7%'}, {'Year': 2011, 'Country_Name': 'Australia', 'Nbr_Cars': '189,503', 'Nbr_Commercial_Vehicle': '34,690', 'Total': '224,193', 'Percent_Change': '-8.1%'}, {'Year': 2011, 'Country_Name': 'Austria', 'Nbr_Cars': '130,343', 'Nbr_Commercial_Vehicle': '22,162', 'Total': '152,505', 'Percent_Change': '45.2%'}, {'Year': 2011, 'Country_Name': 'Belgium', 'Nbr_Cars': '560,779', 'Nbr_Commercial_Vehicle': '34,305', 'Total': '595,084', 'Percent_Change': '7.2%'}, {'Year': 2011, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,519,389', 'Nbr_Commercial_Vehicle': '888,472', 'Total': '3,407,861', 'Percent_Change': '0.8%'}, {'Year': 2011, 'Country_Name': 'Canada', 'Nbr_Cars': '990,482', 'Nbr_Commercial_Vehicle': '1,144,639', 'Total': '2,135,121', 'Percent_Change': '3.2%'}, {'Year': 2011, 'Country_Name': 'China', 'Nbr_Cars': '14,485,326', 'Nbr_Commercial_Vehicle': '3,933,550', 'Total': '18,418,876', 'Percent_Change': '0.8%'}, {'Year': 2011, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1,191,968', 'Nbr_Commercial_Vehicle': '7,877', 'Total': '1,199,845', 'Percent_Change': '11.5%'}, {'Year': 2011, 'Country_Name': 'Egypt', 'Nbr_Cars': '53,072', 'Nbr_Commercial_Vehicle': '28,659', 'Total': '81,731', 'Percent_Change': '-30.0%'}, {'Year': 2011, 'Country_Name': 'Finland', 'Nbr_Cars': '2,540', 'Nbr_Commercial_Vehicle': '91', 'Total': '2,631', 'Percent_Change': '-60.5%'}, {'Year': 2011, 'Country_Name': 'France', 'Nbr_Cars': '1,931,030', 'Nbr_Commercial_Vehicle': '311,898', 'Total': '2,242,928', 'Percent_Change': '0.6%'}, {'Year': 2011, 'Country_Name': 'Germany', 'Nbr_Cars': '5,871,918', 'Nbr_Commercial_Vehicle': '275,030', 'Total': '6,146,948', 'Percent_Change': '4.1%'}, {'Year': 2011, 'Country_Name': 'Hungary', 'Nbr_Cars': '211,218', 'Nbr_Commercial_Vehicle': '2,313', 'Total': '213,531', 'Percent_Change': '1.0%'}, {'Year': 2011, 'Country_Name': 'India', 'Nbr_Cars': '3,040,144', 'Nbr_Commercial_Vehicle': '887,267', 'Total': '3,927,411', 'Percent_Change': '10.4%'}, {'Year': 2011, 'Country_Name': 'Indonesia', 'Nbr_Cars': '562,250', 'Nbr_Commercial_Vehicle': '276,138', 'Total': '838,388', 'Percent_Change': '19.3%'}, {'Year': 2011, 'Country_Name': 'Iran', 'Nbr_Cars': '1,412,803', 'Nbr_Commercial_Vehicle': '236,508', 'Total': '1,649,311', 'Percent_Change': '3.1%'}, {'Year': 2011, 'Country_Name': 'Italy', 'Nbr_Cars': '485,606', 'Nbr_Commercial_Vehicle': '304,742', 'Total': '790,348', 'Percent_Change': '-5.7%'}, {'Year': 2011, 'Country_Name': 'Japan', 'Nbr_Cars': '7,158,525', 'Nbr_Commercial_Vehicle': '1,240,105', 'Total': '8,398,630', 'Percent_Change': '-12.8%'}, {'Year': 2011, 'Country_Name': 'Malaysia', 'Nbr_Cars': '488,441', 'Nbr_Commercial_Vehicle': '45,254', 'Total': '533,695', 'Percent_Change': '-6.0%'}, {'Year': 2011, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,657,080', 'Nbr_Commercial_Vehicle': '1,023,970', 'Total': '2,681,050', 'Percent_Change': '14.5%'}, {'Year': 2011, 'Country_Name': 'Netherlands', 'Nbr_Cars': '40,772', 'Nbr_Commercial_Vehicle': '32,379', 'Total': '73,151', 'Percent_Change': '-22.3%'}, {'Year': 2011, 'Country_Name': 'Poland', 'Nbr_Cars': '741,000', 'Nbr_Commercial_Vehicle': '97,133', 'Total': '838,133', 'Percent_Change': '-3.6%'}, {'Year': 2011, 'Country_Name': 'Portugal', 'Nbr_Cars': '141,779', 'Nbr_Commercial_Vehicle': '50,463', 'Total': '192,242', 'Percent_Change': '21.1%'}, {'Year': 2011, 'Country_Name': 'Romania', 'Nbr_Cars': '310,243', 'Nbr_Commercial_Vehicle': '24,989', 'Total': '335,232', 'Percent_Change': '-4.5%'}, {'Year': 2011, 'Country_Name': 'Russia', 'Nbr_Cars': '1,744,097', 'Nbr_Commercial_Vehicle': '246,058', 'Total': '1,990,155', 'Percent_Change': '41.8%'}, {'Year': 2011, 'Country_Name': 'Serbia', 'Nbr_Cars': '10,227', 'Nbr_Commercial_Vehicle': '796', 'Total': '11,023', 'Percent_Change': '-27.5%'}, {'Year': 2011, 'Country_Name': 'Slovakia', 'Nbr_Cars': '639,763', 'Nbr_Commercial_Vehicle': '0', 'Total': '639,763', 'Percent_Change': '13.9%'}, {'Year': 2011, 'Country_Name': 'Slovenia', 'Nbr_Cars': '168,955', 'Nbr_Commercial_Vehicle': '5,164', 'Total': '174,119', 'Percent_Change': '-17.6%'}, {'Year': 2011, 'Country_Name': 'South Africa', 'Nbr_Cars': '312,265', 'Nbr_Commercial_Vehicle': '220,280', 'Total': '532,545', 'Percent_Change': '12.8%'}, {'Year': 2011, 'Country_Name': 'South Korea', 'Nbr_Cars': '4,221,617', 'Nbr_Commercial_Vehicle': '435,477', 'Total': '4,657,094', 'Percent_Change': '9.0%'}, {'Year': 2011, 'Country_Name': 'Spain', 'Nbr_Cars': '1,839,068', 'Nbr_Commercial_Vehicle': '534,261', 'Total': '2,373,329', 'Percent_Change': '-0.6%'}, {'Year': 2011, 'Country_Name': 'Sweden', 'Nbr_Cars': '188,969', 'Nbr_Commercial_Vehicle': 'N.A.', 'Total': '188,969', 'Percent_Change': '-13.0%'}, {'Year': 2011, 'Country_Name': 'Taiwan', 'Nbr_Cars': '288,523', 'Nbr_Commercial_Vehicle': '54,773', 'Total': '343,296', 'Percent_Change': '13.1%'}, {'Year': 2011, 'Country_Name': 'Thailand', 'Nbr_Cars': '537,987', 'Nbr_Commercial_Vehicle': '919,811', 'Total': '1,457,798', 'Percent_Change': '-11.4%'}, {'Year': 2011, 'Country_Name': 'Turkey', 'Nbr_Cars': '639,734', 'Nbr_Commercial_Vehicle': '549,397', 'Total': '1,189,131', 'Percent_Change': '8.6%'}, {'Year': 2011, 'Country_Name': 'Ukraine', 'Nbr_Cars': '97,585', 'Nbr_Commercial_Vehicle': '7,069', 'Total': '104,654', 'Percent_Change': '25.9%'}, {'Year': 2011, 'Country_Name': 'UK', 'Nbr_Cars': '1,343,810', 'Nbr_Commercial_Vehicle': '120,189', 'Total': '1,463,999', 'Percent_Change': '5.1%'}, {'Year': 2011, 'Country_Name': 'USA', 'Nbr_Cars': '2,976,991', 'Nbr_Commercial_Vehicle': '5,684,544', 'Total': '8,661,535', 'Percent_Change': '11.9%'}, {'Year': 2011, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '146,300', 'Nbr_Commercial_Vehicle': '33,260', 'Total': '179,560', 'Percent_Change': '14.5%'}, {'Year': 2011, 'Country_Name': 'Others', 'Nbr_Cars': '367,138', 'Nbr_Commercial_Vehicle': '124,373', 'Total': '491,511', 'Percent_Change': '1.0%'}, {'Year': 2012, 'Country_Name': 'Argentina', 'Nbr_Cars': '497,376', 'Nbr_Commercial_Vehicle': '267,119', 'Total': '764,495', 'Percent_Change': '-7.8%'}, {'Year': 2012, 'Country_Name': 'Australia', 'Nbr_Cars': '189,949', 'Nbr_Commercial_Vehicle': '36,553', 'Total': '226,502', 'Percent_Change': '-1.0%'}, {'Year': 2012, 'Country_Name': 'Austria', 'Nbr_Cars': '123,602', 'Nbr_Commercial_Vehicle': '19,487', 'Total': '143,089', 'Percent_Change': '-6.2%'}, {'Year': 2012, 'Country_Name': 'Belgium', 'Nbr_Cars': '504,616', 'Nbr_Commercial_Vehicle': '34,232', 'Total': '538,848', 'Percent_Change': '-9.5%'}, {'Year': 2012, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,589,236', 'Nbr_Commercial_Vehicle': '813,272', 'Total': '3,402,508', 'Percent_Change': '-0.2%'}, {'Year': 2012, 'Country_Name': 'Canada', 'Nbr_Cars': '1,040,298', 'Nbr_Commercial_Vehicle': '1,423,066', 'Total': '2,463,364', 'Percent_Change': '15.4%'}, {'Year': 2012, 'Country_Name': 'China', 'Nbr_Cars': '15,523,658', 'Nbr_Commercial_Vehicle': '3,748,150', 'Total': '19,271,808', 'Percent_Change': '4.6%'}, {'Year': 2012, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1,171,774', 'Nbr_Commercial_Vehicle': '7,221', 'Total': '1,178,995', 'Percent_Change': '-1.7%'}, {'Year': 2012, 'Country_Name': 'Egypt', 'Nbr_Cars': '36,880', 'Nbr_Commercial_Vehicle': '19,600', 'Total': '56,480', 'Percent_Change': '-30.9%'}, {'Year': 2012, 'Country_Name': 'Finland', 'Nbr_Cars': '8,600', 'Nbr_Commercial_Vehicle': '88', 'Total': '8,688', 'Percent_Change': '245.5%'}, {'Year': 2012, 'Country_Name': 'France', 'Nbr_Cars': '1,682,814', 'Nbr_Commercial_Vehicle': '284,951', 'Total': '1,967,765', 'Percent_Change': '-12.3%'}, {'Year': 2012, 'Country_Name': 'Germany', 'Nbr_Cars': '5,388,459', 'Nbr_Commercial_Vehicle': '260,801', 'Total': '5,649,260', 'Percent_Change': '-8.1%'}, {'Year': 2012, 'Country_Name': 'Hungary', 'Nbr_Cars': '215,440', 'Nbr_Commercial_Vehicle': '2,400', 'Total': '217,840', 'Percent_Change': '2.0%'}, {'Year': 2012, 'Country_Name': 'India', 'Nbr_Cars': '3,296,240', 'Nbr_Commercial_Vehicle': '878,473', 'Total': '4,174,713', 'Percent_Change': '6.3%'}, {'Year': 2012, 'Country_Name': 'Indonesia', 'Nbr_Cars': '745,144', 'Nbr_Commercial_Vehicle': '307,751', 'Total': '1,052,895', 'Percent_Change': '25.6%'}, {'Year': 2012, 'Country_Name': 'Iran', 'Nbr_Cars': '856,927', 'Nbr_Commercial_Vehicle': '143,162', 'Total': '1,000,089', 'Percent_Change': '-39.3%'}, {'Year': 2012, 'Country_Name': 'Italy', 'Nbr_Cars': '396,817', 'Nbr_Commercial_Vehicle': '274,951', 'Total': '671,768', 'Percent_Change': '-15.0%'}, {'Year': 2012, 'Country_Name': 'Japan', 'Nbr_Cars': '8,554,503', 'Nbr_Commercial_Vehicle': '1,388,574', 'Total': '9,943,077', 'Percent_Change': '18.4%'}, {'Year': 2012, 'Country_Name': 'Malaysia', 'Nbr_Cars': '509,621', 'Nbr_Commercial_Vehicle': '59,999', 'Total': '569,620', 'Percent_Change': '6.7%'}, {'Year': 2012, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,810,007', 'Nbr_Commercial_Vehicle': '1,191,807', 'Total': '3,001,814', 'Percent_Change': '12.0%'}, {'Year': 2012, 'Country_Name': 'Netherlands', 'Nbr_Cars': '24,895', 'Nbr_Commercial_Vehicle': '30,744', 'Total': '55,639', 'Percent_Change': '-23.9%'}, {'Year': 2012, 'Country_Name': 'Poland', 'Nbr_Cars': '539,671', 'Nbr_Commercial_Vehicle': '115085', 'Total': '654,756', 'Percent_Change': '-21.9%'}, {'Year': 2012, 'Country_Name': 'Portugal', 'Nbr_Cars': '115,735', 'Nbr_Commercial_Vehicle': '47,826', 'Total': '163,561', 'Percent_Change': '-14.9%'}, {'Year': 2012, 'Country_Name': 'Romania', 'Nbr_Cars': '326,556', 'Nbr_Commercial_Vehicle': '11,209', 'Total': '337,765', 'Percent_Change': '0.8%'}, {'Year': 2012, 'Country_Name': 'Russia', 'Nbr_Cars': '1,970,087', 'Nbr_Commercial_Vehicle': '263,016', 'Total': '2,233,103', 'Percent_Change': '12.2%'}, {'Year': 2012, 'Country_Name': 'Serbia', 'Nbr_Cars': '10,227', 'Nbr_Commercial_Vehicle': '805', 'Total': '11,032', 'Percent_Change': '0.1%'}, {'Year': 2012, 'Country_Name': 'Slovakia', 'Nbr_Cars': '926,555', 'Nbr_Commercial_Vehicle': '0', 'Total': '926,555', 'Percent_Change': '44.8%'}, {'Year': 2012, 'Country_Name': 'Slovenia', 'Nbr_Cars': '126,836', 'Nbr_Commercial_Vehicle': '4,113', 'Total': '130,949', 'Percent_Change': '-24.8%'}, {'Year': 2012, 'Country_Name': 'South Africa', 'Nbr_Cars': '274,873', 'Nbr_Commercial_Vehicle': '264,551', 'Total': '539,424', 'Percent_Change': '1.3%'}, {'Year': 2012, 'Country_Name': 'South Korea', 'Nbr_Cars': '4,167,089', 'Nbr_Commercial_Vehicle': '394,677', 'Total': '4,561,766', 'Percent_Change': '-2.0%'}, {'Year': 2012, 'Country_Name': 'Spain', 'Nbr_Cars': '1,539,680', 'Nbr_Commercial_Vehicle': '439,499', 'Total': '1,979,179', 'Percent_Change': '-16.6%'}, {'Year': 2012, 'Country_Name': 'Sweden', 'Nbr_Cars': '162,814', 'Nbr_Commercial_Vehicle': 'N.A.', 'Total': '162,814', 'Percent_Change': '-13.8%'}, {'Year': 2012, 'Country_Name': 'Taiwan', 'Nbr_Cars': '278,043', 'Nbr_Commercial_Vehicle': '60,995', 'Total': '339,038', 'Percent_Change': '-1.2%'}, {'Year': 2012, 'Country_Name': 'Thailand', 'Nbr_Cars': '945,100', 'Nbr_Commercial_Vehicle': '1,484,042', 'Total': '2,429,142', 'Percent_Change': '66.6%'}, {'Year': 2012, 'Country_Name': 'Turkey', 'Nbr_Cars': '577,296', 'Nbr_Commercial_Vehicle': '495,682', 'Total': '1,072,978', 'Percent_Change': '-9.8%'}, {'Year': 2012, 'Country_Name': 'Ukraine', 'Nbr_Cars': '69,687', 'Nbr_Commercial_Vehicle': '6,594', 'Total': '76,281', 'Percent_Change': '-27.1%'}, {'Year': 2012, 'Country_Name': 'UK', 'Nbr_Cars': '1,464,906', 'Nbr_Commercial_Vehicle': '112,039', 'Total': '1,576,945', 'Percent_Change': '7.7%'}, {'Year': 2012, 'Country_Name': 'USA', 'Nbr_Cars': '4,109,013', 'Nbr_Commercial_Vehicle': '6,226,752', 'Total': '10,335,765', 'Percent_Change': '19.3%'}, {'Year': 2012, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '144,980', 'Nbr_Commercial_Vehicle': '19,200', 'Total': '164,180', 'Percent_Change': '-8.6%'}, {'Year': 2012, 'Country_Name': 'Others', 'Nbr_Cars': '463,990', 'Nbr_Commercial_Vehicle': '135,652', 'Total': '599,642', 'Percent_Change': '22.0%'}, {'Year': 2013, 'Country_Name': 'Argentina', 'Nbr_Cars': '506,539', 'Nbr_Commercial_Vehicle': '284,468', 'Total': '791,007', 'Percent_Change': '3.5%'}, {'Year': 2013, 'Country_Name': 'Australia', 'Nbr_Cars': '170,808', 'Nbr_Commercial_Vehicle': '45,118', 'Total': '215,926', 'Percent_Change': '-4.7%'}, {'Year': 2013, 'Country_Name': 'Austria', 'Nbr_Cars': '146,566', 'Nbr_Commercial_Vehicle': '19,862', 'Total': '166,428', 'Percent_Change': '16.3%'}, {'Year': 2013, 'Country_Name': 'Belgium', 'Nbr_Cars': '465,504', 'Nbr_Commercial_Vehicle': '38,000', 'Total': '503,504', 'Percent_Change': '-6.6%'}, {'Year': 2013, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,722,979', 'Nbr_Commercial_Vehicle': '989,401', 'Total': '3,712,380', 'Percent_Change': '9.1%'}, {'Year': 2013, 'Country_Name': 'Canada', 'Nbr_Cars': '965,191', 'Nbr_Commercial_Vehicle': '1,414,615', 'Total': '2,379,834', 'Percent_Change': '-3.4%'}, {'Year': 2013, 'Country_Name': 'China', 'Nbr_Cars': '18,084,169', 'Nbr_Commercial_Vehicle': '4,032,656', 'Total': '22,116,825', 'Percent_Change': '14.8%'}, {'Year': 2013, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1,128,473', 'Nbr_Commercial_Vehicle': '4,458', 'Total': '1,132,931', 'Percent_Change': '-3.9%'}, {'Year': 2013, 'Country_Name': 'Egypt', 'Nbr_Cars': '13,777', 'Nbr_Commercial_Vehicle': '17,027', 'Total': '30,804', 'Percent_Change': '-45.5%'}, {'Year': 2013, 'Country_Name': 'Finland', 'Nbr_Cars': '7,600', 'Nbr_Commercial_Vehicle': '103', 'Total': '7,703', 'Percent_Change': '-11.3%'}, {'Year': 2013, 'Country_Name': 'France', 'Nbr_Cars': '1,458,220', 'Nbr_Commercial_Vehicle': '282,000', 'Total': '1,740,220', 'Percent_Change': '-11.6%'}, {'Year': 2013, 'Country_Name': 'Germany', 'Nbr_Cars': '5,439,904', 'Nbr_Commercial_Vehicle': '278,318', 'Total': '5,718,222', 'Percent_Change': '1.2%'}, {'Year': 2013, 'Country_Name': 'Hungary', 'Nbr_Cars': '317,857', 'Nbr_Commercial_Vehicle': '3,430', 'Total': '321,287', 'Percent_Change': '47.5%'}, {'Year': 2013, 'Country_Name': 'India', 'Nbr_Cars': '3,155,694', 'Nbr_Commercial_Vehicle': '742,731', 'Total': '3,898,425', 'Percent_Change': '-6.6%'}, {'Year': 2013, 'Country_Name': 'Indonesia', 'Nbr_Cars': '924,753', 'Nbr_Commercial_Vehicle': '281,615', 'Total': '1,206,368', 'Percent_Change': '14.6%'}, {'Year': 2013, 'Country_Name': 'Iran', 'Nbr_Cars': '630,639', 'Nbr_Commercial_Vehicle': '113,041', 'Total': '743,680', 'Percent_Change': '-25.6%'}, {'Year': 2013, 'Country_Name': 'Italy', 'Nbr_Cars': '388,465', 'Nbr_Commercial_Vehicle': '269,741', 'Total': '658,206', 'Percent_Change': '-2.0%'}, {'Year': 2013, 'Country_Name': 'Japan', 'Nbr_Cars': '8,189,323', 'Nbr_Commercial_Vehicle': '1,440,858', 'Total': '9,630,181', 'Percent_Change': '-3.1%'}, {'Year': 2013, 'Country_Name': 'Malaysia', 'Nbr_Cars': '543,892', 'Nbr_Commercial_Vehicle': '57,515', 'Total': '601,407', 'Percent_Change': '5.6%'}, {'Year': 2013, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,771,987', 'Nbr_Commercial_Vehicle': '1,282,862', 'Total': '3,054,849', 'Percent_Change': '1.8%'}, {'Year': 2013, 'Country_Name': 'Netherlands', 'Nbr_Cars': '0', 'Nbr_Commercial_Vehicle': '29,183', 'Total': '29,183', 'Percent_Change': '-47.5%'}, {'Year': 2013, 'Country_Name': 'Poland', 'Nbr_Cars': '475,000', 'Nbr_Commercial_Vehicle': '115,159', 'Total': '590,159', 'Percent_Change': '-9.9%'}, {'Year': 2013, 'Country_Name': 'Portugal', 'Nbr_Cars': '109,698', 'Nbr_Commercial_Vehicle': '44,318', 'Total': '154,016', 'Percent_Change': '-5.8%'}, {'Year': 2013, 'Country_Name': 'Romania', 'Nbr_Cars': '410,959', 'Nbr_Commercial_Vehicle': '38', 'Total': '410,997', 'Percent_Change': '21.7%'}, {'Year': 2013, 'Country_Name': 'Russia', 'Nbr_Cars': '1,927,578', 'Nbr_Commercial_Vehicle': '264,667', 'Total': '2,192,245', 'Percent_Change': '-1.8%'}, {'Year': 2013, 'Country_Name': 'Serbia', 'Nbr_Cars': '113,487', 'Nbr_Commercial_Vehicle': '805', 'Total': '113,878', 'Percent_Change': '932.3%'}, {'Year': 2013, 'Country_Name': 'Slovakia', 'Nbr_Cars': '975,000', 'Nbr_Commercial_Vehicle': '0', 'Total': '975,000', 'Percent_Change': '5.2%'}, {'Year': 2013, 'Country_Name': 'Slovenia', 'Nbr_Cars': '89,395', 'Nbr_Commercial_Vehicle': '4,339', 'Total': '93,734', 'Percent_Change': '-28.4%'}, {'Year': 2013, 'Country_Name': 'South Africa', 'Nbr_Cars': '265,257', 'Nbr_Commercial_Vehicle': '280,656', 'Total': '545,913', 'Percent_Change': '1.2%'}, {'Year': 2013, 'Country_Name': 'South Korea', 'Nbr_Cars': '4,122,604', 'Nbr_Commercial_Vehicle': '398,825', 'Total': '4,521,429', 'Percent_Change': '-0.9%'}, {'Year': 2013, 'Country_Name': 'Spain', 'Nbr_Cars': '1,754,668', 'Nbr_Commercial_Vehicle': '408,670', 'Total': '2,163,338', 'Percent_Change': '9.3%'}, {'Year': 2013, 'Country_Name': 'Sweden', 'Nbr_Cars': '161,080', 'Nbr_Commercial_Vehicle': 'N.A.', 'Total': '161,080', 'Percent_Change': '-1.1%'}, {'Year': 2013, 'Country_Name': 'Taiwan', 'Nbr_Cars': '291,037', 'Nbr_Commercial_Vehicle': '47,683', 'Total': '338,720', 'Percent_Change': '-0.1%'}, {'Year': 2013, 'Country_Name': 'Thailand', 'Nbr_Cars': '1,071,076', 'Nbr_Commercial_Vehicle': '1,385,981', 'Total': '2,457,057', 'Percent_Change': '1.1%'}, {'Year': 2013, 'Country_Name': 'Turkey', 'Nbr_Cars': '633,604', 'Nbr_Commercial_Vehicle': '491,930', 'Total': '1,125,534', 'Percent_Change': '4.9%'}, {'Year': 2013, 'Country_Name': 'Ukraine', 'Nbr_Cars': '45,758', 'Nbr_Commercial_Vehicle': '4,691', 'Total': '50,449', 'Percent_Change': '-33.9%'}, {'Year': 2013, 'Country_Name': 'UK', 'Nbr_Cars': '1,509,762', 'Nbr_Commercial_Vehicle': '88,110', 'Total': '1,597,872', 'Percent_Change': '1.3%'}, {'Year': 2013, 'Country_Name': 'USA', 'Nbr_Cars': '4,368,835', 'Nbr_Commercial_Vehicle': '6,697,597', 'Total': '11,066,432', 'Percent_Change': '7.1%'}, {'Year': 2013, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '246,641', 'Nbr_Commercial_Vehicle': '0', 'Total': '246,641', 'Percent_Change': '50.2%'}, {'Year': 2013, 'Country_Name': 'Others', 'Nbr_Cars': '523,679', 'Nbr_Commercial_Vehicle': '119,936', 'Total': '643,615', 'Percent_Change': '7.3%'}, {'Year': 2014, 'Country_Name': 'Argentina', 'Nbr_Cars': '363,711', 'Nbr_Commercial_Vehicle': '253,618', 'Total': '617,329', 'Percent_Change': '-22.0%'}, {'Year': 2014, 'Country_Name': 'Australia', 'Nbr_Cars': '166,933', 'Nbr_Commercial_Vehicle': '13,378', 'Total': '180,311', 'Percent_Change': '-16.5%'}, {'Year': 2014, 'Country_Name': 'Austria', 'Nbr_Cars': '136,000', 'Nbr_Commercial_Vehicle': '18,340', 'Total': '152,000', 'Percent_Change': '-8.7%'}, {'Year': 2014, 'Country_Name': 'Belgium', 'Nbr_Cars': '481,636', 'Nbr_Commercial_Vehicle': '35,195', 'Total': '516,831', 'Percent_Change': '2.6%'}, {'Year': 2014, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,502,293', 'Nbr_Commercial_Vehicle': '644,093', 'Total': '3,146,386', 'Percent_Change': '-15.2%'}, {'Year': 2014, 'Country_Name': 'Canada', 'Nbr_Cars': '913,533', 'Nbr_Commercial_Vehicle': '1,480,621', 'Total': '2,394,154', 'Percent_Change': '0.6%'}, {'Year': 2014, 'Country_Name': 'China', 'Nbr_Cars': '19,928,505', 'Nbr_Commercial_Vehicle': '3,803,095', 'Total': '23,731,600', 'Percent_Change': '7.3%'}, {'Year': 2014, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1,246,506', 'Nbr_Commercial_Vehicle': '4,714', 'Total': '1,251,220', 'Percent_Change': '10.4%'}, {'Year': 2014, 'Country_Name': 'Egypt', 'Nbr_Cars': '17,542', 'Nbr_Commercial_Vehicle': '9,190', 'Total': '42,515', 'Percent_Change': '-38.0%'}, {'Year': 2014, 'Country_Name': 'Finland', 'Nbr_Cars': '45,000', 'Nbr_Commercial_Vehicle': '35', 'Total': '45,035', 'Percent_Change': '484.6%'}, {'Year': 2014, 'Country_Name': 'France', 'Nbr_Cars': '1,499,464', 'Nbr_Commercial_Vehicle': '322,000', 'Total': '1,821,464', 'Percent_Change': '4.7%'}, {'Year': 2014, 'Country_Name': 'Germany', 'Nbr_Cars': '5,604,026', 'Nbr_Commercial_Vehicle': '303,522', 'Total': '5,907,548', 'Percent_Change': '3.3%'}, {'Year': 2014, 'Country_Name': 'Hungary', 'Nbr_Cars': '434,069', 'Nbr_Commercial_Vehicle': '2,400', 'Total': '437,599', 'Percent_Change': '36.2%'}, {'Year': 2014, 'Country_Name': 'India', 'Nbr_Cars': '3,162,372', 'Nbr_Commercial_Vehicle': '682,485', 'Total': '3,844,857', 'Percent_Change': '-1.4%'}, {'Year': 2014, 'Country_Name': 'Indonesia', 'Nbr_Cars': '1,013,172', 'Nbr_Commercial_Vehicle': '285,351', 'Total': '1,298,523', 'Percent_Change': '7.6%'}, {'Year': 2014, 'Country_Name': 'Iran', 'Nbr_Cars': '925,975', 'Nbr_Commercial_Vehicle': '164,871', 'Total': '1,090,846', 'Percent_Change': '46.7%'}, {'Year': 2014, 'Country_Name': 'Italy', 'Nbr_Cars': '401,317', 'Nbr_Commercial_Vehicle': '296,547', 'Total': '697,864', 'Percent_Change': '6.0%'}, {'Year': 2014, 'Country_Name': 'Japan', 'Nbr_Cars': '8,277,070', 'Nbr_Commercial_Vehicle': '1,497,488', 'Total': '9,774,665', 'Percent_Change': '1.5%'}, {'Year': 2014, 'Country_Name': 'Malaysia', 'Nbr_Cars': '545,122', 'Nbr_Commercial_Vehicle': '50,012', 'Total': '595,134', 'Percent_Change': '-1.0%'}, {'Year': 2014, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,915,709', 'Nbr_Commercial_Vehicle': '1,452,301', 'Total': '3,368,010', 'Percent_Change': '10.3%'}, {'Year': 2014, 'Country_Name': 'Netherlands', 'Nbr_Cars': '29,196', 'Nbr_Commercial_Vehicle': '2,232', 'Total': '31,428', 'Percent_Change': '7.7%'}, {'Year': 2014, 'Country_Name': 'Poland', 'Nbr_Cars': '472,600', 'Nbr_Commercial_Vehicle': '120,904', 'Total': '593,504', 'Percent_Change': '0.6%'}, {'Year': 2014, 'Country_Name': 'Portugal', 'Nbr_Cars': '117,744', 'Nbr_Commercial_Vehicle': '43,765', 'Total': '161,509', 'Percent_Change': '4.9%'}, {'Year': 2014, 'Country_Name': 'Romania', 'Nbr_Cars': '391,422', 'Nbr_Commercial_Vehicle': '12', 'Total': '391,434', 'Percent_Change': '-4.8%'}, {'Year': 2014, 'Country_Name': 'Russia', 'Nbr_Cars': '1,682,921', 'Nbr_Commercial_Vehicle': '204,272', 'Total': '1,887,193', 'Percent_Change': '-23.0%'}, {'Year': 2014, 'Country_Name': 'Serbia', 'Nbr_Cars': '101,576', 'Nbr_Commercial_Vehicle': '695', 'Total': '103,150', 'Percent_Change': '-9.4%'}, {'Year': 2014, 'Country_Name': 'Slovakia', 'Nbr_Cars': '971,160', 'Nbr_Commercial_Vehicle': '0', 'Total': '971,160', 'Percent_Change': '-0.4%'}, {'Year': 2014, 'Country_Name': 'Slovenia', 'Nbr_Cars': '118,533', 'Nbr_Commercial_Vehicle': '58', 'Total': '118,591', 'Percent_Change': '26.5%'}, {'Year': 2014, 'Country_Name': 'South Africa', 'Nbr_Cars': '277,491', 'Nbr_Commercial_Vehicle': '288,592', 'Total': '566,083', 'Percent_Change': '3.7%'}, {'Year': 2014, 'Country_Name': 'South Korea', 'Nbr_Cars': '4,124,116', 'Nbr_Commercial_Vehicle': '400,816', 'Total': '4,524,932', 'Percent_Change': '0.1%'}, {'Year': 2014, 'Country_Name': 'Spain', 'Nbr_Cars': '1,898,342', 'Nbr_Commercial_Vehicle': '504,636', 'Total': '2,402,978', 'Percent_Change': '11.1%'}, {'Year': 2014, 'Country_Name': 'Sweden', 'Nbr_Cars': '154,174', 'Nbr_Commercial_Vehicle': 'N.A.', 'Total': '154,174', 'Percent_Change': '-4.3%'}, {'Year': 2014, 'Country_Name': 'Taiwan', 'Nbr_Cars': '332,629', 'Nbr_Commercial_Vehicle': '46,594', 'Total': '379,223', 'Percent_Change': '12.0%'}, {'Year': 2014, 'Country_Name': 'Thailand', 'Nbr_Cars': '743,258', 'Nbr_Commercial_Vehicle': '1,137,329', 'Total': '1,880,587', 'Percent_Change': '-23.5%'}, {'Year': 2014, 'Country_Name': 'Turkey', 'Nbr_Cars': '733,439', 'Nbr_Commercial_Vehicle': '437,006', 'Total': '1,170,445', 'Percent_Change': '4.0%'}, {'Year': 2014, 'Country_Name': 'Ukraine', 'Nbr_Cars': '25,941', 'Nbr_Commercial_Vehicle': '2,810', 'Total': '28,751', 'Percent_Change': '-43.0%'}, {'Year': 2014, 'Country_Name': 'UK', 'Nbr_Cars': '1,528,148', 'Nbr_Commercial_Vehicle': '70,731', 'Total': '1,598,879', 'Percent_Change': '0.1%'}, {'Year': 2014, 'Country_Name': 'USA', 'Nbr_Cars': '4,253,098', 'Nbr_Commercial_Vehicle': '7,407,604', 'Total': '11,660,702', 'Percent_Change': '5.4%'}, {'Year': 2014, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '245,660', 'Nbr_Commercial_Vehicle': '0', 'Total': '245,660', 'Percent_Change': '-0.4%'}, {'Year': 2014, 'Country_Name': 'Others', 'Nbr_Cars': '584,144', 'Nbr_Commercial_Vehicle': '114,998', 'Total': '699,142', 'Percent_Change': '8.7%'}, {'Year': 2015, 'Country_Name': 'Argentina', 'Nbr_Cars': '308,756', 'Nbr_Commercial_Vehicle': '224,927', 'Total': '533,683', 'Percent_Change': '-13.5%'}, {'Year': 2015, 'Country_Name': 'Australia', 'Nbr_Cars': '159,872', 'Nbr_Commercial_Vehicle': '13,137', 'Total': '173,009', 'Percent_Change': '-4.0%'}, {'Year': 2015, 'Country_Name': 'Austria', 'Nbr_Cars': '109,000', 'Nbr_Commercial_Vehicle': '16,500', 'Total': '125,500', 'Percent_Change': '-17.4%'}, {'Year': 2015, 'Country_Name': 'Belgium', 'Nbr_Cars': '369,172', 'Nbr_Commercial_Vehicle': '40,168', 'Total': '409,340', 'Percent_Change': '-20.8%'}, {'Year': 2015, 'Country_Name': 'Brazil', 'Nbr_Cars': '2,018,954', 'Nbr_Commercial_Vehicle': '410,509', 'Total': '2,429,463', 'Percent_Change': '-22.8%'}, {'Year': 2015, 'Country_Name': 'Canada', 'Nbr_Cars': '888,565', 'Nbr_Commercial_Vehicle': '1,394,909', 'Total': '2,283,474', 'Percent_Change': '-4.6%'}, {'Year': 2015, 'Country_Name': 'China', 'Nbr_Cars': '21,079,427', 'Nbr_Commercial_Vehicle': '3,423,899', 'Total': '24,503,326', 'Percent_Change': '3.3%'}, {'Year': 2015, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1,298,236', 'Nbr_Commercial_Vehicle': '5,367', 'Total': '1,303,603', 'Percent_Change': '4.2%'}, {'Year': 2015, 'Country_Name': 'Egypt', 'Nbr_Cars': '12,000', 'Nbr_Commercial_Vehicle': '24,000', 'Total': '36,000', 'Percent_Change': '-15.3%'}, {'Year': 2015, 'Country_Name': 'Finland', 'Nbr_Cars': '69,000', 'Nbr_Commercial_Vehicle': '53', 'Total': '69,053', 'Percent_Change': '53.3%'}, {'Year': 2015, 'Country_Name': 'France', 'Nbr_Cars': '1,553,800', 'Nbr_Commercial_Vehicle': '416,200', 'Total': '1,970,000', 'Percent_Change': '8.2%'}, {'Year': 2015, 'Country_Name': 'Germany', 'Nbr_Cars': '5,707,938', 'Nbr_Commercial_Vehicle': '325,226', 'Total': '6,033,164', 'Percent_Change': '2.1%'}, {'Year': 2015, 'Country_Name': 'Hungary', 'Nbr_Cars': '491,720', 'Nbr_Commercial_Vehicle': '3,650', 'Total': '495,370', 'Percent_Change': '13.2%'}, {'Year': 2015, 'Country_Name': 'India', 'Nbr_Cars': '3,378,063', 'Nbr_Commercial_Vehicle': '747,681', 'Total': '4,125,744', 'Percent_Change': '7.3%'}, {'Year': 2015, 'Country_Name': 'Indonesia', 'Nbr_Cars': '824,445', 'Nbr_Commercial_Vehicle': '274,335', 'Total': '1,098,780', 'Percent_Change': '-15.4%'}, {'Year': 2015, 'Country_Name': 'Iran', 'Nbr_Cars': '884,866', 'Nbr_Commercial_Vehicle': '97,471', 'Total': '982,337', 'Percent_Change': '-9.9%'}, {'Year': 2015, 'Country_Name': 'Italy', 'Nbr_Cars': '663,139', 'Nbr_Commercial_Vehicle': '351,084', 'Total': '1,014,223', 'Percent_Change': '45.3%'}, {'Year': 2015, 'Country_Name': 'Japan', 'Nbr_Cars': '7,830,722', 'Nbr_Commercial_Vehicle': '1,447,516', 'Total': '9,278,238', 'Percent_Change': '-5.1%'}, {'Year': 2015, 'Country_Name': 'Malaysia', 'Nbr_Cars': '558,324', 'Nbr_Commercial_Vehicle': '56,347', 'Total': '614,671', 'Percent_Change': '3.3%'}, {'Year': 2015, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,968,054', 'Nbr_Commercial_Vehicle': '1,597,415', 'Total': '3,565,469', 'Percent_Change': '5.9%'}, {'Year': 2015, 'Country_Name': 'Netherlands', 'Nbr_Cars': '41,870', 'Nbr_Commercial_Vehicle': '2,252', 'Total': '44,122', 'Percent_Change': '40.4%'}, {'Year': 2015, 'Country_Name': 'Poland', 'Nbr_Cars': '534,700', 'Nbr_Commercial_Vehicle': '125,903', 'Total': '660,603', 'Percent_Change': '11.3%'}, {'Year': 2015, 'Country_Name': 'Portugal', 'Nbr_Cars': '115,468', 'Nbr_Commercial_Vehicle': '41,158', 'Total': '156,626', 'Percent_Change': '-3.0%'}, {'Year': 2015, 'Country_Name': 'Romania', 'Nbr_Cars': '387,171', 'Nbr_Commercial_Vehicle': '6', 'Total': '387,177', 'Percent_Change': '-1.1%'}, {'Year': 2015, 'Country_Name': 'Russia', 'Nbr_Cars': '1,214,849', 'Nbr_Commercial_Vehicle': '169,550', 'Total': '1,384,399', 'Percent_Change': '-26.6%'}, {'Year': 2015, 'Country_Name': 'Serbia', 'Nbr_Cars': '82,400', 'Nbr_Commercial_Vehicle': '1,230', 'Total': '83,630', 'Percent_Change': '-18.9%'}, {'Year': 2015, 'Country_Name': 'Slovakia', 'Nbr_Cars': '1,000,001', 'Nbr_Commercial_Vehicle': '0', 'Total': '1,000,001', 'Percent_Change': '3.0%'}, {'Year': 2015, 'Country_Name': 'Slovenia', 'Nbr_Cars': '133,092', 'Nbr_Commercial_Vehicle': '0', 'Total': '133,092', 'Percent_Change': '12.2%'}, {'Year': 2015, 'Country_Name': 'South Africa', 'Nbr_Cars': '341,025', 'Nbr_Commercial_Vehicle': '274,633', 'Total': '615,658', 'Percent_Change': '8.8%'}, {'Year': 2015, 'Country_Name': 'South Korea', 'Nbr_Cars': '4,135,108', 'Nbr_Commercial_Vehicle': '420,849', 'Total': '4,555,957', 'Percent_Change': '0.7%'}, {'Year': 2015, 'Country_Name': 'Spain', 'Nbr_Cars': '2,218,980', 'Nbr_Commercial_Vehicle': '514,221', 'Total': '2,733,201', 'Percent_Change': '13.7%'}, {'Year': 2015, 'Country_Name': 'Sweden', 'Nbr_Cars': '188,987', 'Nbr_Commercial_Vehicle': 'N.A.', 'Total': '188,987', 'Percent_Change': '22.6%'}, {'Year': 2015, 'Country_Name': 'Taiwan', 'Nbr_Cars': '298,418', 'Nbr_Commercial_Vehicle': '52,667', 'Total': '351,085', 'Percent_Change': '-7.4%'}, {'Year': 2015, 'Country_Name': 'Thailand', 'Nbr_Cars': '772,250', 'Nbr_Commercial_Vehicle': '1,143,170', 'Total': '1,915,420', 'Percent_Change': '1.9%'}, {'Year': 2015, 'Country_Name': 'Turkey', 'Nbr_Cars': '791,027', 'Nbr_Commercial_Vehicle': '567,769', 'Total': '1,358,796', 'Percent_Change': '16.1%'}, {'Year': 2015, 'Country_Name': 'Ukraine', 'Nbr_Cars': '5,654', 'Nbr_Commercial_Vehicle': '2,590', 'Total': '8,244', 'Percent_Change': '-71.3%'}, {'Year': 2015, 'Country_Name': 'UK', 'Nbr_Cars': '1,587,677', 'Nbr_Commercial_Vehicle': '94,479', 'Total': '1,682,156', 'Percent_Change': '5.2%'}, {'Year': 2015, 'Country_Name': 'USA', 'Nbr_Cars': '4,163,679', 'Nbr_Commercial_Vehicle': '7,936,416', 'Total': '12,100,095', 'Percent_Change': '3.8%'}, {'Year': 2015, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '185,400', 'Nbr_Commercial_Vehicle': '0', 'Total': '185,400', 'Percent_Change': '-24.5%'}, {'Year': 2015, 'Country_Name': 'Others', 'Nbr_Cars': '693,817', 'Nbr_Commercial_Vehicle': '138,866', 'Total': '832,683', 'Percent_Change': '19.1%'}, {'Year': 2015, 'Country_Name': 'Total', 'Nbr_Cars': '68,539,516', 'Nbr_Commercial_Vehicle': '22,241,067', 'Total': '90,780,583', 'Percent_Change': '1.1%'}, {'Year': 2016, 'Country_Name': 'Argentina', 'Nbr_Cars': '241,315', 'Nbr_Commercial_Vehicle': '231,461', 'Total': '472,776', 'Percent_Change': '-10.2%'}, {'Year': 2016, 'Country_Name': 'Australia', 'Nbr_Cars': '149,000', 'Nbr_Commercial_Vehicle': '12,294', 'Total': '161,294', 'Percent_Change': '-6.8%'}, {'Year': 2016, 'Country_Name': 'Austria', 'Nbr_Cars': '90,000', 'Nbr_Commercial_Vehicle': '18,000', 'Total': '108,000', 'Percent_Change': '-10.9%'}, {'Year': 2016, 'Country_Name': 'Belgium', 'Nbr_Cars': '354,003', 'Nbr_Commercial_Vehicle': '45,424', 'Total': '399,427', 'Percent_Change': '-2.4%'}, {'Year': 2016, 'Country_Name': 'Brazil', 'Nbr_Cars': '1,778,464', 'Nbr_Commercial_Vehicle': '377,892', 'Total': '2,156,356', 'Percent_Change': '-11.2%'}, {'Year': 2016, 'Country_Name': 'Canada', 'Nbr_Cars': '802,057', 'Nbr_Commercial_Vehicle': '1,568,214', 'Total': '2,370,271', 'Percent_Change': '3.8%'}, {'Year': 2016, 'Country_Name': 'China', 'Nbr_Cars': '24,420,744', 'Nbr_Commercial_Vehicle': '3,698,050', 'Total': '28,118,794', 'Percent_Change': '14.5%'}, {'Year': 2016, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1,344,182', 'Nbr_Commercial_Vehicle': '5,714', 'Total': '1,349,896', 'Percent_Change': '8.3%'}, {'Year': 2016, 'Country_Name': 'Egypt', 'Nbr_Cars': '10,930', 'Nbr_Commercial_Vehicle': '25,300', 'Total': '36,230', 'Percent_Change': '0.6%'}, {'Year': 2016, 'Country_Name': 'Finland', 'Nbr_Cars': '55,280', 'Nbr_Commercial_Vehicle': '0', 'Total': '55,280', 'Percent_Change': '-19.9%'}, {'Year': 2016, 'Country_Name': 'France', 'Nbr_Cars': '1,626,000', 'Nbr_Commercial_Vehicle': '456,000', 'Total': '2,082,000', 'Percent_Change': '5.6%'}, {'Year': 2016, 'Country_Name': 'Germany', 'Nbr_Cars': '5,746,808', 'Nbr_Commercial_Vehicle': '315,754', 'Total': '6,062,562', 'Percent_Change': '0.5%'}, {'Year': 2016, 'Country_Name': 'Hungary', 'Nbr_Cars': '472,000', 'Nbr_Commercial_Vehicle': '0', 'Total': '472,000', 'Percent_Change': '-4.7%'}, {'Year': 2016, 'Country_Name': 'India', 'Nbr_Cars': '3,677,605', 'Nbr_Commercial_Vehicle': '811,360', 'Total': '4,488,965', 'Percent_Change': '7.9%'}, {'Year': 2016, 'Country_Name': 'Indonesia', 'Nbr_Cars': '968,101', 'Nbr_Commercial_Vehicle': '209,288', 'Total': '1,177,389', 'Percent_Change': '7.2%'}, {'Year': 2016, 'Country_Name': 'Iran', 'Nbr_Cars': '1,074,000', 'Nbr_Commercial_Vehicle': '90,710', 'Total': '1,164,710', 'Percent_Change': '18.6%'}, {'Year': 2016, 'Country_Name': 'Italy', 'Nbr_Cars': '713,182', 'Nbr_Commercial_Vehicle': '390,334', 'Total': '1,103,516', 'Percent_Change': '8.8%'}, {'Year': 2016, 'Country_Name': 'Japan', 'Nbr_Cars': '7,873,886', 'Nbr_Commercial_Vehicle': '1,330,704', 'Total': '9,204,590', 'Percent_Change': '-0.8%'}, {'Year': 2016, 'Country_Name': 'Malaysia', 'Nbr_Cars': '469,720', 'Nbr_Commercial_Vehicle': '43,725', 'Total': '513,445', 'Percent_Change': '-16.5%'}, {'Year': 2016, 'Country_Name': 'Mexico', 'Nbr_Cars': '1,993,168', 'Nbr_Commercial_Vehicle': '1,604,294', 'Total': '3,597,462', 'Percent_Change': '0.9%'}, {'Year': 2016, 'Country_Name': 'Netherlands', 'Nbr_Cars': '42,150', 'Nbr_Commercial_Vehicle': '2,280', 'Total': '44,430', 'Percent_Change': '0.7%'}, {'Year': 2016, 'Country_Name': 'Poland', 'Nbr_Cars': '554,600', 'Nbr_Commercial_Vehicle': '127,237', 'Total': '681,837', 'Percent_Change': '3.2%'}, {'Year': 2016, 'Country_Name': 'Portugal', 'Nbr_Cars': '99,200', 'Nbr_Commercial_Vehicle': '43,896', 'Total': '143,096', 'Percent_Change': '-8.6%'}, {'Year': 2016, 'Country_Name': 'Romania', 'Nbr_Cars': '358,861', 'Nbr_Commercial_Vehicle': '445', 'Total': '359,306', 'Percent_Change': '-7.2%'}, {'Year': 2016, 'Country_Name': 'Russia', 'Nbr_Cars': '1,124,774', 'Nbr_Commercial_Vehicle': '179,215', 'Total': '1,303,989', 'Percent_Change': '-5.4%'}, {'Year': 2016, 'Country_Name': 'Serbia', 'Nbr_Cars': '79,360', 'Nbr_Commercial_Vehicle': '960', 'Total': '80,320', 'Percent_Change': '-4.0%'}, {'Year': 2016, 'Country_Name': 'Slovakia', 'Nbr_Cars': '1,040,000', 'Nbr_Commercial_Vehicle': '0', 'Total': '1,040,000', 'Percent_Change': '0.1%'}, {'Year': 2016, 'Country_Name': 'Slovenia', 'Nbr_Cars': '133,702', 'Nbr_Commercial_Vehicle': '0', 'Total': '133,702', 'Percent_Change': '0.5%'}, {'Year': 2016, 'Country_Name': 'South Africa', 'Nbr_Cars': '335,539', 'Nbr_Commercial_Vehicle': '263,465', 'Total': '599,004', 'Percent_Change': '-2.7%'}, {'Year': 2016, 'Country_Name': 'South Korea', 'Nbr_Cars': '3,859,991', 'Nbr_Commercial_Vehicle': '368,518', 'Total': '4,228,509', 'Percent_Change': '-7.2%'}, {'Year': 2016, 'Country_Name': 'Spain', 'Nbr_Cars': '2,354,117', 'Nbr_Commercial_Vehicle': '531,805', 'Total': '2,885,922', 'Percent_Change': '5.6%'}, {'Year': 2016, 'Country_Name': 'Sweden', 'Nbr_Cars': '205,374', 'Nbr_Commercial_Vehicle': 'N.A.', 'Total': '205,374', 'Percent_Change': '8.7%'}, {'Year': 2016, 'Country_Name': 'Taiwan', 'Nbr_Cars': '251,096', 'Nbr_Commercial_Vehicle': '58,435', 'Total': '309,531', 'Percent_Change': '-11.8%'}, {'Year': 2016, 'Country_Name': 'Thailand', 'Nbr_Cars': '805,033', 'Nbr_Commercial_Vehicle': '1,139,384', 'Total': '1,944,417', 'Percent_Change': '1.8%'}, {'Year': 2016, 'Country_Name': 'Turkey', 'Nbr_Cars': '950,888', 'Nbr_Commercial_Vehicle': '535,039', 'Total': '1,485,927', 'Percent_Change': '9.4%'}, {'Year': 2016, 'Country_Name': 'Ukraine', 'Nbr_Cars': '4,340', 'Nbr_Commercial_Vehicle': '924', 'Total': '5,264', 'Percent_Change': '-36.1%'}, {'Year': 2016, 'Country_Name': 'UK', 'Nbr_Cars': '1,722,698', 'Nbr_Commercial_Vehicle': '93,924', 'Total': '1,816,622', 'Percent_Change': '8.0%'}, {'Year': 2016, 'Country_Name': 'USA', 'Nbr_Cars': '3,934,357', 'Nbr_Commercial_Vehicle': '8,263,780', 'Total': '12,198,137', 'Percent_Change': '0.8%'}, {'Year': 2016, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '88,152', 'Nbr_Commercial_Vehicle': '0', 'Total': '88,152', 'Percent_Change': '-52.5%'}, {'Year': 2016, 'Country_Name': 'Others', 'Nbr_Cars': '781,708', 'Nbr_Commercial_Vehicle': '138,454', 'Total': '920,162', 'Percent_Change': '10.6%'}, {'Year': 2017, 'Country_Name': 'Argentina', 'Nbr_Cars': '203700', 'Nbr_Commercial_Vehicle': '268458', 'Total': '472158', 'Percent_Change': '-0.13'}, {'Year': 2017, 'Country_Name': 'Australia', 'Nbr_Cars': '88195', 'Nbr_Commercial_Vehicle': '10437', 'Total': '98632', 'Percent_Change': '-38.85'}, {'Year': 2017, 'Country_Name': 'Austria', 'Nbr_Cars': '81000', 'Nbr_Commercial_Vehicle': '18880', 'Total': '99880', 'Percent_Change': '-8.98'}, {'Year': 2017, 'Country_Name': 'Belgium', 'Nbr_Cars': '336000', 'Nbr_Commercial_Vehicle': '43140', 'Total': '379140', 'Percent_Change': '-5.08'}, {'Year': 2017, 'Country_Name': 'Brazil', 'Nbr_Cars': '2269468', 'Nbr_Commercial_Vehicle': '430204', 'Total': '2699672', 'Percent_Change': '25.2'}, {'Year': 2017, 'Country_Name': 'Canada', 'Nbr_Cars': '749458', 'Nbr_Commercial_Vehicle': '1450331', 'Total': '2199789', 'Percent_Change': '-7.21'}, {'Year': 2017, 'Country_Name': 'China', 'Nbr_Cars': '24806687', 'Nbr_Commercial_Vehicle': '4208747', 'Total': '29015434', 'Percent_Change': '3.19'}, {'Year': 2017, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1413881', 'Nbr_Commercial_Vehicle': '6112', 'Total': '1419993', 'Percent_Change': '0'}, {'Year': 2017, 'Country_Name': 'Egypt', 'Nbr_Cars': '9970', 'Nbr_Commercial_Vehicle': '26670', 'Total': '36640', 'Percent_Change': '1.13'}, {'Year': 2017, 'Country_Name': 'Finland', 'Nbr_Cars': '91598', 'Nbr_Commercial_Vehicle': '0', 'Total': '91598', 'Percent_Change': '90.83'}, {'Year': 2017, 'Country_Name': 'France', 'Nbr_Cars': '1748000', 'Nbr_Commercial_Vehicle': '479000', 'Total': '2227000', 'Percent_Change': '6.54'}, {'Year': 2017, 'Country_Name': 'Germany', 'Nbr_Cars': '5645581', 'Nbr_Commercial_Vehicle': '0', 'Total': '5645581', 'Percent_Change': '-1.76'}, {'Year': 2017, 'Country_Name': 'Hungary', 'Nbr_Cars': '502000', 'Nbr_Commercial_Vehicle': '3400', 'Total': '505400', 'Percent_Change': '-4.01'}, {'Year': 2017, 'Country_Name': 'India', 'Nbr_Cars': '3952550', 'Nbr_Commercial_Vehicle': '830346', 'Total': '4782896', 'Percent_Change': '5.83'}, {'Year': 2017, 'Country_Name': 'Indonesia', 'Nbr_Cars': '982356', 'Nbr_Commercial_Vehicle': '234259', 'Total': '1216615', 'Percent_Change': '3.3'}, {'Year': 2017, 'Country_Name': 'Iran', 'Nbr_Cars': '1418550', 'Nbr_Commercial_Vehicle': '96846', 'Total': '1515396', 'Percent_Change': '18.19'}, {'Year': 2017, 'Country_Name': 'Italy', 'Nbr_Cars': '742642', 'Nbr_Commercial_Vehicle': '399568', 'Total': '1142210', 'Percent_Change': '3.53'}, {'Year': 2017, 'Country_Name': 'Japan', 'Nbr_Cars': '8347836', 'Nbr_Commercial_Vehicle': '1345910', 'Total': '9693746', 'Percent_Change': '5.31'}, {'Year': 2017, 'Country_Name': 'Malaysia', 'Nbr_Cars': '424880', 'Nbr_Commercial_Vehicle': '35260', 'Total': '460140', 'Percent_Change': '-15.62'}, {'Year': 2017, 'Country_Name': 'Morocco', 'Nbr_Cars': '341802', 'Nbr_Commercial_Vehicle': '34484', 'Total': '376826', 'Percent_Change': '9'}, {'Year': 2017, 'Country_Name': 'Mexico', 'Nbr_Cars': '1900029', 'Nbr_Commercial_Vehicle': '2168386', 'Total': '4068415', 'Percent_Change': '13'}, {'Year': 2017, 'Country_Name': 'Netherlands', 'Nbr_Cars': '155000', 'Nbr_Commercial_Vehicle': '2280', 'Total': '157280', 'Percent_Change': '74.97'}, {'Year': 2017, 'Country_Name': 'Poland', 'Nbr_Cars': '514700', 'Nbr_Commercial_Vehicle': '175029', 'Total': '689729', 'Percent_Change': '1.16'}, {'Year': 2017, 'Country_Name': 'Portugal', 'Nbr_Cars': '126426', 'Nbr_Commercial_Vehicle': '49118', 'Total': '175544', 'Percent_Change': '22.68'}, {'Year': 2017, 'Country_Name': 'Romania', 'Nbr_Cars': '359240', 'Nbr_Commercial_Vehicle': '10', 'Total': '359250', 'Percent_Change': '-0.02'}, {'Year': 2017, 'Country_Name': 'Russia', 'Nbr_Cars': '1348029', 'Nbr_Commercial_Vehicle': '203264', 'Total': '1551293', 'Percent_Change': '19.01'}, {'Year': 2017, 'Country_Name': 'Serbia', 'Nbr_Cars': '79360', 'Nbr_Commercial_Vehicle': '552', 'Total': '79912', 'Percent_Change': '-0.51'}, {'Year': 2017, 'Country_Name': 'Slovakia', 'Nbr_Cars': '1001520', 'Nbr_Commercial_Vehicle': '0', 'Total': '1001520', 'Percent_Change': '-3.7'}, {'Year': 2017, 'Country_Name': 'Slovenia', 'Nbr_Cars': '189852', 'Nbr_Commercial_Vehicle': '0', 'Total': '189852', 'Percent_Change': '42'}, {'Year': 2017, 'Country_Name': 'South Africa', 'Nbr_Cars': '321358', 'Nbr_Commercial_Vehicle': '268593', 'Total': '589951', 'Percent_Change': '-1.51'}, {'Year': 2017, 'Country_Name': 'South Korea', 'Nbr_Cars': '3735399', 'Nbr_Commercial_Vehicle': '379514', 'Total': '4114913', 'Percent_Change': '-2.69'}, {'Year': 2017, 'Country_Name': 'Spain', 'Nbr_Cars': '2291492', 'Nbr_Commercial_Vehicle': '556843', 'Total': '2848335', 'Percent_Change': '-1.3'}, {'Year': 2017, 'Country_Name': 'Sweden', 'Nbr_Cars': '226000', 'Nbr_Commercial_Vehicle': '0', 'Total': '226000', 'Percent_Change': '10.04'}, {'Year': 2017, 'Country_Name': 'Taiwan', 'Nbr_Cars': '230356', 'Nbr_Commercial_Vehicle': '61207', 'Total': '291563', 'Percent_Change': '-5.8'}, {'Year': 2017, 'Country_Name': 'Thailand', 'Nbr_Cars': '818440', 'Nbr_Commercial_Vehicle': '1170383', 'Total': '1988823', 'Percent_Change': '2.28'}, {'Year': 2017, 'Country_Name': 'Turkey', 'Nbr_Cars': '1142906', 'Nbr_Commercial_Vehicle': '552825', 'Total': '1695731', 'Percent_Change': '14.12'}, {'Year': 2017, 'Country_Name': 'Ukraine', 'Nbr_Cars': '7296', 'Nbr_Commercial_Vehicle': '2246', 'Total': '9542', 'Percent_Change': '81.27'}, {'Year': 2017, 'Country_Name': 'UK', 'Nbr_Cars': '1671166', 'Nbr_Commercial_Vehicle': '78219', 'Total': '1749385', 'Percent_Change': '-3.70'}, {'Year': 2017, 'Country_Name': 'USA', 'Nbr_Cars': '3033216', 'Nbr_Commercial_Vehicle': '8156769', 'Total': '11189985', 'Percent_Change': '-8.13'}, {'Year': 2017, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '140247', 'Nbr_Commercial_Vehicle': '0', 'Total': '140247', 'Percent_Change': '59.10'}, {'Year': 2017, 'Country_Name': 'Others', 'Nbr_Cars': '536725', 'Nbr_Commercial_Vehicle': '221947', 'Total': '758672', 'Percent_Change': '16'}, {'Year': 2018, 'Country_Name': 'Argentina', 'Nbr_Cars': '208573', 'Nbr_Commercial_Vehicle': '258076', 'Total': '466649', 'Percent_Change': '-1.4'}, {'Year': 2018, 'Country_Name': 'Austria', 'Nbr_Cars': '144500', 'Nbr_Commercial_Vehicle': '20400', 'Total': '164900', 'Percent_Change': '69.7'}, {'Year': 2018, 'Country_Name': 'Belgium', 'Nbr_Cars': '265958', 'Nbr_Commercial_Vehicle': '42535', 'Total': '308493', 'Percent_Change': '-18.2'}, {'Year': 2018, 'Country_Name': 'Brazil', 'Nbr_Cars': '2386758', 'Nbr_Commercial_Vehicle': '493051', 'Total': '2879809', 'Percent_Change': '5.2'}, {'Year': 2018, 'Country_Name': 'Canada', 'Nbr_Cars': '655896', 'Nbr_Commercial_Vehicle': '1364944', 'Total': '2020840', 'Percent_Change': '-7.9'}, {'Year': 2018, 'Country_Name': 'China', 'Nbr_Cars': '23529423', 'Nbr_Commercial_Vehicle': '4279773', 'Total': '27809196', 'Percent_Change': '-4.2'}, {'Year': 2018, 'Country_Name': 'Colombia', 'Nbr_Cars': '69000', 'Nbr_Commercial_Vehicle': '3800', 'Total': '72800', 'Percent_Change': '-5.5'}, {'Year': 2018, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1345041', 'Nbr_Commercial_Vehicle': '0', 'Total': '1345041', 'Percent_Change': '3'}, {'Year': 2018, 'Country_Name': 'Egypt', 'Nbr_Cars': '19500', 'Nbr_Commercial_Vehicle': '52100', 'Total': '71600', 'Percent_Change': '95'}, {'Year': 2018, 'Country_Name': 'Finland', 'Nbr_Cars': '112104', 'Nbr_Commercial_Vehicle': '0', 'Total': '112104', 'Percent_Change': '3'}, {'Year': 2018, 'Country_Name': 'France', 'Nbr_Cars': '1763000', 'Nbr_Commercial_Vehicle': '507000', 'Total': '2270000', 'Percent_Change': '2.0'}, {'Year': 2018, 'Country_Name': 'Germany', 'Nbr_Cars': '5120409', 'Nbr_Commercial_Vehicle': '0', 'Total': '5120409', 'Percent_Change': '-9.3'}, {'Year': 2018, 'Country_Name': 'Hungary', 'Nbr_Cars': '430988', 'Nbr_Commercial_Vehicle': '0', 'Total': '430988', 'Percent_Change': '3.0'}, {'Year': 2018, 'Country_Name': 'India', 'Nbr_Cars': '4064774', 'Nbr_Commercial_Vehicle': '1109871', 'Total': '5174645', 'Percent_Change': '8.0'}, {'Year': 2018, 'Country_Name': 'Indonesia', 'Nbr_Cars': '1055774', 'Nbr_Commercial_Vehicle': '287940', 'Total': '1343714', 'Percent_Change': '10.3'}, {'Year': 2018, 'Country_Name': 'Iran', 'Nbr_Cars': '1027313', 'Nbr_Commercial_Vehicle': '68213', 'Total': '1095526', 'Percent_Change': '-40'}, {'Year': 2018, 'Country_Name': 'Italy', 'Nbr_Cars': '670932', 'Nbr_Commercial_Vehicle': '389136', 'Total': '1060068', 'Percent_Change': '-7.2'}, {'Year': 2018, 'Country_Name': 'Japan', 'Nbr_Cars': '8358220', 'Nbr_Commercial_Vehicle': '1370308', 'Total': '9728528', 'Percent_Change': '0.4'}, {'Year': 2018, 'Country_Name': 'Malaysia', 'Nbr_Cars': '522000', 'Nbr_Commercial_Vehicle': '42800', 'Total': '564800', 'Percent_Change': '12.2'}, {'Year': 2018, 'Country_Name': 'Morocco', 'Nbr_Cars': '368601', 'Nbr_Commercial_Vehicle': '33484', 'Total': '402085', 'Percent_Change': '17.6'}, {'Year': 2018, 'Country_Name': 'Mexico', 'Nbr_Cars': '1575808', 'Nbr_Commercial_Vehicle': '2524717', 'Total': '4100525', 'Percent_Change': '0.1'}, {'Year': 2018, 'Country_Name': 'Poland', 'Nbr_Cars': '451600', 'Nbr_Commercial_Vehicle': '208046', 'Total': '659646', 'Percent_Change': '-4.4'}, {'Year': 2018, 'Country_Name': 'Portugal', 'Nbr_Cars': '234151', 'Nbr_Commercial_Vehicle': '60215', 'Total': '294366', 'Percent_Change': '67.7'}, {'Year': 2018, 'Country_Name': 'Romania', 'Nbr_Cars': '476769', 'Nbr_Commercial_Vehicle': '0', 'Total': '476769', 'Percent_Change': '31.1'}, {'Year': 2018, 'Country_Name': 'Russia', 'Nbr_Cars': '1563572', 'Nbr_Commercial_Vehicle': '204102', 'Total': '1767674', 'Percent_Change': '13.9'}, {'Year': 2018, 'Country_Name': 'Serbia', 'Nbr_Cars': '56303', 'Nbr_Commercial_Vehicle': '146', 'Total': '56449', 'Percent_Change': '-28.5'}, {'Year': 2018, 'Country_Name': 'Slovakia', 'Nbr_Cars': '1090000', 'Nbr_Commercial_Vehicle': '0', 'Total': '1090000', 'Percent_Change': '5.6'}, {'Year': 2018, 'Country_Name': 'Slovenia', 'Nbr_Cars': '209378', 'Nbr_Commercial_Vehicle': '0', 'Total': '209378', 'Percent_Change': '10.2'}, {'Year': 2018, 'Country_Name': 'South Africa', 'Nbr_Cars': '321097', 'Nbr_Commercial_Vehicle': '289757', 'Total': '610854', 'Percent_Change': '3.5'}, {'Year': 2018, 'Country_Name': 'South Korea', 'Nbr_Cars': '3661730', 'Nbr_Commercial_Vehicle': '367104', 'Total': '4028834', 'Percent_Change': '-2.1'}, {'Year': 2018, 'Country_Name': 'Spain', 'Nbr_Cars': '2267396', 'Nbr_Commercial_Vehicle': '552169', 'Total': '2819565', 'Percent_Change': '-1.0'}, {'Year': 2018, 'Country_Name': 'Taiwan', 'Nbr_Cars': '190052', 'Nbr_Commercial_Vehicle': '63189', 'Total': '253241', 'Percent_Change': '-13.1'}, {'Year': 2018, 'Country_Name': 'Thailand', 'Nbr_Cars': '877015', 'Nbr_Commercial_Vehicle': '1290679', 'Total': '2167694', 'Percent_Change': '9.0'}, {'Year': 2018, 'Country_Name': 'Turkey', 'Nbr_Cars': '1026461', 'Nbr_Commercial_Vehicle': '523689', 'Total': '1550150', 'Percent_Change': '-8.6'}, {'Year': 2018, 'Country_Name': 'Ukraine', 'Nbr_Cars': '5660', 'Nbr_Commercial_Vehicle': '963', 'Total': '6623', 'Percent_Change': '-22.9'}, {'Year': 2018, 'Country_Name': 'UK', 'Nbr_Cars': '1519440', 'Nbr_Commercial_Vehicle': '84888', 'Total': '1604328', 'Percent_Change': '-8.3'}, {'Year': 2018, 'Country_Name': 'USA', 'Nbr_Cars': '2795971', 'Nbr_Commercial_Vehicle': '8518734', 'Total': '11314705', 'Percent_Change': '1.1'}, {'Year': 2018, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '220667', 'Nbr_Commercial_Vehicle': '0', 'Total': '220667', 'Percent_Change': '57.3'}, {'Year': 2018, 'Country_Name': 'Others', 'Nbr_Cars': '341554', 'Nbr_Commercial_Vehicle': '152230', 'Total': '493784', 'Percent_Change': ''}, {'Year': 2018, 'Country_Name': 'Total', 'Nbr_Cars': '70498388', 'Nbr_Commercial_Vehicle': '25136912', 'Total': '95634593', 'Percent_Change': '-1.1'}, {'Year': 2019, 'Country_Name': 'Argentina', 'Nbr_Cars': '108364', 'Nbr_Commercial_Vehicle': '206423', 'Total': '314787', 'Percent_Change': '-32,5'}, {'Year': 2019, 'Country_Name': 'Austria', 'Nbr_Cars': '158 400', 'Nbr_Commercial_Vehicle': '21000', 'Total': '179400', 'Percent_Change': '8,8'}, {'Year': 2019, 'Country_Name': 'Belgium', 'Nbr_Cars': '247020', 'Nbr_Commercial_Vehicle': '38777', 'Total': '285797', 'Percent_Change': '-7,4'}, {'Year': 2019, 'Country_Name': 'Brazil', 'Nbr_Cars': '2448490', 'Nbr_Commercial_Vehicle': '496498', 'Total': '2944988', 'Percent_Change': '2,2'}, {'Year': 2019, 'Country_Name': 'Canada', 'Nbr_Cars': '461370', 'Nbr_Commercial_Vehicle': '1455215', 'Total': '1916585', 'Percent_Change': '-5,4'}, {'Year': 2019, 'Country_Name': 'China', 'Nbr_Cars': '21360193', 'Nbr_Commercial_Vehicle': '4360472', 'Total': '25720665', 'Percent_Change': '-7,5'}, {'Year': 2019, 'Country_Name': 'Czech Rep.', 'Nbr_Cars': '1427563', 'Nbr_Commercial_Vehicle': '6400', 'Total': '1433963', 'Percent_Change': '-0,6'}, {'Year': 2019, 'Country_Name': 'Egypt', 'Nbr_Cars': '18500', 'Nbr_Commercial_Vehicle': '0', 'Total': '18500', 'Percent_Change': '0'}, {'Year': 2019, 'Country_Name': 'Finland', 'Nbr_Cars': '114785', 'Nbr_Commercial_Vehicle': '0', 'Total': '114785', 'Percent_Change': '2,5'}, {'Year': 2019, 'Country_Name': 'France', 'Nbr_Cars': '1675198', 'Nbr_Commercial_Vehicle': '527262', 'Total': '2202460', 'Percent_Change': '-2,9'}, {'Year': 2019, 'Country_Name': 'Germany', 'Nbr_Cars': '4661328', 'Nbr_Commercial_Vehicle': '0', 'Total': '4661328', 'Percent_Change': '-9'}, {'Year': 2019, 'Country_Name': 'Hungary', 'Nbr_Cars': '498158', 'Nbr_Commercial_Vehicle': '0', 'Total': '498158', 'Percent_Change': '7,6'}, {'Year': 2019, 'Country_Name': 'India', 'Nbr_Cars': '3623335', 'Nbr_Commercial_Vehicle': '892682', 'Total': '4516017', 'Percent_Change': '-12,2'}, {'Year': 2019, 'Country_Name': 'Indonesia', 'Nbr_Cars': '1045666', 'Nbr_Commercial_Vehicle': '241182', 'Total': '1286848', 'Percent_Change': '-4,2'}, {'Year': 2019, 'Country_Name': 'Iran', 'Nbr_Cars': '770000', 'Nbr_Commercial_Vehicle': '51060', 'Total': '821060', 'Percent_Change': '-25'}, {'Year': 2019, 'Country_Name': 'Italy', 'Nbr_Cars': '542007', 'Nbr_Commercial_Vehicle': '373298', 'Total': '915305', 'Percent_Change': '-13,8'}, {'Year': 2019, 'Country_Name': 'Japan', 'Nbr_Cars': '8328756', 'Nbr_Commercial_Vehicle': '1355542', 'Total': '9684298', 'Percent_Change': '-0,5'}, {'Year': 2019, 'Country_Name': 'Malaysia', 'Nbr_Cars': '534115', 'Nbr_Commercial_Vehicle': '37517', 'Total': '571632', 'Percent_Change': '1,2'}, {'Year': 2019, 'Country_Name': 'Morocco', 'Nbr_Cars': '360110', 'Nbr_Commercial_Vehicle': '34542', 'Total': '394652', 'Percent_Change': '-1,8'}, {'Year': 2019, 'Country_Name': 'Mexico', 'Nbr_Cars': '1382714', 'Nbr_Commercial_Vehicle': '2604080', 'Total': '3986794', 'Percent_Change': '-2,8'}, {'Year': 2019, 'Country_Name': 'Poland', 'Nbr_Cars': '434700', 'Nbr_Commercial_Vehicle': '215164', 'Total': '649864', 'Percent_Change': '-1,5'}, {'Year': 2019, 'Country_Name': 'Portugal', 'Nbr_Cars': '282142', 'Nbr_Commercial_Vehicle': '63562', 'Total': '345704', 'Percent_Change': '17,4'}, {'Year': 2019, 'Country_Name': 'Romania', 'Nbr_Cars': '490412', 'Nbr_Commercial_Vehicle': '0', 'Total': '490412', 'Percent_Change': '2,9'}, {'Year': 2019, 'Country_Name': 'Russia', 'Nbr_Cars': '1523594', 'Nbr_Commercial_Vehicle': '196190', 'Total': '1719784', 'Percent_Change': '-2,8'}, {'Year': 2019, 'Country_Name': 'Serbia', 'Nbr_Cars': '34985', 'Nbr_Commercial_Vehicle': '130', 'Total': '35115', 'Percent_Change': '-37,8'}, {'Year': 2019, 'Country_Name': 'Slovakia', 'Nbr_Cars': '1100000', 'Nbr_Commercial_Vehicle': '0', 'Total': '1100000', 'Percent_Change': '0,6'}, {'Year': 2019, 'Country_Name': 'Slovenia', 'Nbr_Cars': '199102', 'Nbr_Commercial_Vehicle': '0', 'Total': '199102', 'Percent_Change': '-4,9'}, {'Year': 2019, 'Country_Name': 'South Africa', 'Nbr_Cars': '348665', 'Nbr_Commercial_Vehicle': '283318', 'Total': '631983', 'Percent_Change': '3,5'}, {'Year': 2019, 'Country_Name': 'South Korea', 'Nbr_Cars': '3612587', 'Nbr_Commercial_Vehicle': '338030', 'Total': '3950617', 'Percent_Change': '-1,9'}, {'Year': 2019, 'Country_Name': 'Spain', 'Nbr_Cars': '2248019', 'Nbr_Commercial_Vehicle': '574336', 'Total': '2822355', 'Percent_Change': '0,1'}, {'Year': 2019, 'Country_Name': 'Taiwan', 'Nbr_Cars': '189549', 'Nbr_Commercial_Vehicle': '61755', 'Total': '251304', 'Percent_Change': '-0,8'}, {'Year': 2019, 'Country_Name': 'Thailand', 'Nbr_Cars': '795254', 'Nbr_Commercial_Vehicle': '1218456', 'Total': '2013710', 'Percent_Change': '-7,1'}, {'Year': 2019, 'Country_Name': 'Turkey', 'Nbr_Cars': '982642', 'Nbr_Commercial_Vehicle': '478602', 'Total': '1461244', 'Percent_Change': '-5,7'}, {'Year': 2019, 'Country_Name': 'Ukraine', 'Nbr_Cars': '6254', 'Nbr_Commercial_Vehicle': '1011', 'Total': '7265', 'Percent_Change': '9,7'}, {'Year': 2019, 'Country_Name': 'UK', 'Nbr_Cars': '1303135', 'Nbr_Commercial_Vehicle': '78270', 'Total': '1381405', 'Percent_Change': '-13,9'}, {'Year': 2019, 'Country_Name': 'USA', 'Nbr_Cars': '2512780', 'Nbr_Commercial_Vehicle': '8367239', 'Total': '10880019', 'Percent_Change': '-3,7'}, {'Year': 2019, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '271113', 'Nbr_Commercial_Vehicle': '0', 'Total': '271113', 'Percent_Change': '22,9'}, {'Year': 2019, 'Country_Name': 'Others', 'Nbr_Cars': '1048191', 'Nbr_Commercial_Vehicle': '59652', 'Total': '1108503', 'Percent_Change': ''}, {'Year': 2019, 'Country_Name': 'Total', 'Nbr_Cars': '67149196', 'Nbr_Commercial_Vehicle': '24637665', 'Total': '91786861', 'Percent_Change': '-5,2'}, {'Year': 2020, 'Country_Name': 'Argentina', 'Nbr_Cars': '93001', 'Nbr_Commercial_Vehicle': '164186', 'Total': '257187', 'Percent_Change': '-18%'}, {'Year': 2020, 'Country_Name': 'Austria', 'Nbr_Cars': '104544', 'Nbr_Commercial_Vehicle': '-', 'Total': '104544', 'Percent_Change': '-42%'}, {'Year': 2020, 'Country_Name': 'Belgium', 'Nbr_Cars': '237057', 'Nbr_Commercial_Vehicle': '30403', 'Total': '267460', 'Percent_Change': '-6%'}, {'Year': 2020, 'Country_Name': 'Brazil', 'Nbr_Cars': '1608870', 'Nbr_Commercial_Vehicle': '405185', 'Total': '2014055', 'Percent_Change': '-32%'}, {'Year': 2020, 'Country_Name': 'Canada', 'Nbr_Cars': '327681', 'Nbr_Commercial_Vehicle': '1048942', 'Total': '1376623', 'Percent_Change': '-28%'}, {'Year': 2020, 'Country_Name': 'China', 'Nbr_Cars': '19994081', 'Nbr_Commercial_Vehicle': '5231161', 'Total': '25225242', 'Percent_Change': '-2%'}, {'Year': 2020, 'Country_Name': 'Czech Republic', 'Nbr_Cars': '1152901', 'Nbr_Commercial_Vehicle': '6250', 'Total': '1159151', 'Percent_Change': '-19%'}, {'Year': 2020, 'Country_Name': 'Egypt', 'Nbr_Cars': '23754', 'Nbr_Commercial_Vehicle': '-', 'Total': '23754', 'Percent_Change': '28%'}, {'Year': 2020, 'Country_Name': 'Finland', 'Nbr_Cars': '86270', 'Nbr_Commercial_Vehicle': '-', 'Total': '86270', 'Percent_Change': '-25%'}, {'Year': 2020, 'Country_Name': 'France', 'Nbr_Cars': '927718', 'Nbr_Commercial_Vehicle': '388653', 'Total': '1316371', 'Percent_Change': '-39%'}, {'Year': 2020, 'Country_Name': 'Germany', 'Nbr_Cars': '3515372', 'Nbr_Commercial_Vehicle': '227082', 'Total': '3742454', 'Percent_Change': '-24%'}, {'Year': 2020, 'Country_Name': 'Hungary', 'Nbr_Cars': '406497', 'Nbr_Commercial_Vehicle': '-', 'Total': '406497', 'Percent_Change': '-18%'}, {'Year': 2020, 'Country_Name': 'India', 'Nbr_Cars': '2851268', 'Nbr_Commercial_Vehicle': '543178', 'Total': '3394446', 'Percent_Change': '-25%'}, {'Year': 2020, 'Country_Name': 'Indonesia', 'Nbr_Cars': '551400', 'Nbr_Commercial_Vehicle': '139886', 'Total': '691286', 'Percent_Change': '-46%'}, {'Year': 2020, 'Country_Name': 'Iran', 'Nbr_Cars': '826210', 'Nbr_Commercial_Vehicle': '54787', 'Total': '880997', 'Percent_Change': '7%'}, {'Year': 2020, 'Country_Name': 'Italy', 'Nbr_Cars': '451826', 'Nbr_Commercial_Vehicle': '325339', 'Total': '777165', 'Percent_Change': '-15%'}, {'Year': 2020, 'Country_Name': 'Japan', 'Nbr_Cars': '6960025', 'Nbr_Commercial_Vehicle': '1107532', 'Total': '8067557', 'Percent_Change': '-17%'}, {'Year': 2020, 'Country_Name': 'Kazakhstan', 'Nbr_Cars': '64790', 'Nbr_Commercial_Vehicle': '10041', 'Total': '74831', 'Percent_Change': '51%'}, {'Year': 2020, 'Country_Name': 'Malaysia', 'Nbr_Cars': '457755', 'Nbr_Commercial_Vehicle': '27431', 'Total': '485186', 'Percent_Change': '-15%'}, {'Year': 2020, 'Country_Name': 'Morocco', 'Nbr_Cars': '221299', 'Nbr_Commercial_Vehicle': '27131', 'Total': '248430', 'Percent_Change': '-38%'}, {'Year': 2020, 'Country_Name': 'Mexico', 'Nbr_Cars': '967479', 'Nbr_Commercial_Vehicle': '2209121', 'Total': '3176600', 'Percent_Change': '-21%'}, {'Year': 2020, 'Country_Name': 'Poland', 'Nbr_Cars': '278900', 'Nbr_Commercial_Vehicle': '172482', 'Total': '451382', 'Percent_Change': '-31%'}, {'Year': 2020, 'Country_Name': 'Portugal', 'Nbr_Cars': '211281', 'Nbr_Commercial_Vehicle': '52955', 'Total': '264236', 'Percent_Change': '-24%'}, {'Year': 2020, 'Country_Name': 'Romania', 'Nbr_Cars': '438107', 'Nbr_Commercial_Vehicle': '-', 'Total': '438107', 'Percent_Change': '-11%'}, {'Year': 2020, 'Country_Name': 'Russia', 'Nbr_Cars': '1260517', 'Nbr_Commercial_Vehicle': '174818', 'Total': '1435335', 'Percent_Change': '-17%'}, {'Year': 2020, 'Country_Name': 'Serbia', 'Nbr_Cars': '23272', 'Nbr_Commercial_Vehicle': '103', 'Total': '23375', 'Percent_Change': '-33%'}, {'Year': 2020, 'Country_Name': 'Slovakia', 'Nbr_Cars': '985000', 'Nbr_Commercial_Vehicle': '-', 'Total': '985000', 'Percent_Change': '-11%'}, {'Year': 2020, 'Country_Name': 'Slovenia', 'Nbr_Cars': '141714', 'Nbr_Commercial_Vehicle': '-', 'Total': '141714', 'Percent_Change': '-29%'}, {'Year': 2020, 'Country_Name': 'South Africa', 'Nbr_Cars': '238216', 'Nbr_Commercial_Vehicle': '209002', 'Total': '447218', 'Percent_Change': '-29%'}, {'Year': 2020, 'Country_Name': 'South Korea', 'Nbr_Cars': '3211706', 'Nbr_Commercial_Vehicle': '295068', 'Total': '3506774', 'Percent_Change': '-11%'}, {'Year': 2020, 'Country_Name': 'Spain', 'Nbr_Cars': '1800664', 'Nbr_Commercial_Vehicle': '467521', 'Total': '2268185', 'Percent_Change': '-20%'}, {'Year': 2020, 'Country_Name': 'Taiwan', 'Nbr_Cars': '180967', 'Nbr_Commercial_Vehicle': '64648', 'Total': '245615', 'Percent_Change': '-2%'}, {'Year': 2020, 'Country_Name': 'Thailand', 'Nbr_Cars': '537633', 'Nbr_Commercial_Vehicle': '889441', 'Total': '1427074', 'Percent_Change': '-29%'}, {'Year': 2020, 'Country_Name': 'Turkey', 'Nbr_Cars': '855043', 'Nbr_Commercial_Vehicle': '442835', 'Total': '1297878', 'Percent_Change': '-11%'}, {'Year': 2020, 'Country_Name': 'Ukraine', 'Nbr_Cars': '4202', 'Nbr_Commercial_Vehicle': '750', 'Total': '4952', 'Percent_Change': '-32%'}, {'Year': 2020, 'Country_Name': 'United Kingdom', 'Nbr_Cars': '920928', 'Nbr_Commercial_Vehicle': '66116', 'Total': '987044', 'Percent_Change': '-29%'}, {'Year': 2020, 'Country_Name': 'USA', 'Nbr_Cars': '1926795', 'Nbr_Commercial_Vehicle': '6895604', 'Total': '8822399', 'Percent_Change': '-19%'}, {'Year': 2020, 'Country_Name': 'Uzbekistan', 'Nbr_Cars': '280080', 'Nbr_Commercial_Vehicle': '-', 'Total': '280080', 'Percent_Change': '3%'}, {'Year': 2020, 'Country_Name': 'Others', 'Nbr_Cars': '709633', 'Nbr_Commercial_Vehicle': '109475', 'Total': '819108', 'Percent_Change': ''}, {'Year': 2020, 'Country_Name': 'Total', 'Nbr_Cars': '55834456', 'Nbr_Commercial_Vehicle': '21787126', 'Total': '77621582', 'Percent_Change': '-16%'}, {'Year': 2021, 'Country_Name': 'ARGENTINA', 'Nbr_Cars': '184106', 'Nbr_Commercial_Vehicle': '250647', 'Total': '434753', 'Percent_Change': '69%'}, {'Year': 2021, 'Country_Name': 'AUSTRIA', 'Nbr_Cars': '124700', 'Nbr_Commercial_Vehicle': '12000', 'Total': '136700', 'Percent_Change': '9%'}, {'Year': 2021, 'Country_Name': 'BELGIUM', 'Nbr_Cars': '224180', 'Nbr_Commercial_Vehicle': '36858', 'Total': '261038', 'Percent_Change': '-2%'}, {'Year': 2021, 'Country_Name': 'BRAZIL', 'Nbr_Cars': '1707851', 'Nbr_Commercial_Vehicle': '540402', 'Total': '2248253', 'Percent_Change': '12%'}, {'Year': 2021, 'Country_Name': 'CANADA', 'Nbr_Cars': '288 235', 'Nbr_Commercial_Vehicle': '826767', 'Total': '1115002', 'Percent_Change': '-19%'}, {'Year': 2021, 'Country_Name': 'CHINA', 'Nbr_Cars': '21407962', 'Nbr_Commercial_Vehicle': '4674258', 'Total': '26082220', 'Percent_Change': '3%'}, {'Year': 2021, 'Country_Name': 'CZECH REPUBLIC', 'Nbr_Cars': '1 105 223', 'Nbr_Commercial_Vehicle': '6209', 'Total': '1111432', 'Percent_Change': '-4%'}, {'Year': 2021, 'Country_Name': 'EGYPT', 'Nbr_Cars': '23754', 'Nbr_Commercial_Vehicle': '', 'Total': '23754', 'Percent_Change': '0%'}, {'Year': 2021, 'Country_Name': 'FINLAND', 'Nbr_Cars': '93172', 'Nbr_Commercial_Vehicle': '', 'Total': '93172', 'Percent_Change': '8%'}, {'Year': 2021, 'Country_Name': 'FRANCE', 'Nbr_Cars': '917907', 'Nbr_Commercial_Vehicle': '433401', 'Total': '1351308', 'Percent_Change': '3%'}, {'Year': 2021, 'Country_Name': 'GERMANY', 'Nbr_Cars': '3096165', 'Nbr_Commercial_Vehicle': '212527', 'Total': '3308692', 'Percent_Change': '-12%'}, {'Year': 2021, 'Country_Name': 'HUNGARY', 'Nbr_Cars': '394302', 'Nbr_Commercial_Vehicle': '', 'Total': '394302', 'Percent_Change': '-3%'}, {'Year': 2021, 'Country_Name': 'INDIA', 'Nbr_Cars': '3631095', 'Nbr_Commercial_Vehicle': '768017', 'Total': '4399112', 'Percent_Change': '30%'}, {'Year': 2021, 'Country_Name': 'INDONESIA', 'Nbr_Cars': '889756', 'Nbr_Commercial_Vehicle': '232211', 'Total': '1121967', 'Percent_Change': '63%'}, {'Year': 2021, 'Country_Name': 'ITALY', 'Nbr_Cars': '442432', 'Nbr_Commercial_Vehicle': '353424', 'Total': '795856', 'Percent_Change': '2%'}, {'Year': 2021, 'Country_Name': 'JAPAN', 'Nbr_Cars': '6619242', 'Nbr_Commercial_Vehicle': '1227713', 'Total': '7846955', 'Percent_Change': '-3%'}, {'Year': 2021, 'Country_Name': 'KAZAKHSTAN', 'Nbr_Cars': '80679', 'Nbr_Commercial_Vehicle': '11738', 'Total': '92417', 'Percent_Change': '24%'}, {'Year': 2021, 'Country_Name': 'MALAYSIA', 'Nbr_Cars': '446431', 'Nbr_Commercial_Vehicle': '35220', 'Total': '481651', 'Percent_Change': '-1%'}, {'Year': 2021, 'Country_Name': 'MOROCCO', 'Nbr_Cars': '338339', 'Nbr_Commercial_Vehicle': '64668', 'Total': '403007', 'Percent_Change': '23%'}, {'Year': 2021, 'Country_Name': 'MEXICO', 'Nbr_Cars': '708242', 'Nbr_Commercial_Vehicle': '2437411', 'Total': '3145653', 'Percent_Change': '-1%'}, {'Year': 2021, 'Country_Name': 'POLAND', 'Nbr_Cars': '260800', 'Nbr_Commercial_Vehicle': '178621', 'Total': '439421', 'Percent_Change': '-3%'}, {'Year': 2021, 'Country_Name': 'PORTUGAL', 'Nbr_Cars': '229221', 'Nbr_Commercial_Vehicle': '60733', 'Total': '289954', 'Percent_Change': '10%'}, {'Year': 2021, 'Country_Name': 'ROMANIA', 'Nbr_Cars': '420755', 'Nbr_Commercial_Vehicle': '', 'Total': '420755', 'Percent_Change': '-4%'}, {'Year': 2021, 'Country_Name': 'RUSSIA', 'Nbr_Cars': '1352740', 'Nbr_Commercial_Vehicle': '213577', 'Total': '1566317', 'Percent_Change': '9%'}, {'Year': 2021, 'Country_Name': 'SERBIA', 'Nbr_Cars': '21109', 'Nbr_Commercial_Vehicle': '154', 'Total': '21263', 'Percent_Change': '-9%'}, {'Year': 2021, 'Country_Name': 'SLOVAKIA', 'Nbr_Cars': '1000000', 'Nbr_Commercial_Vehicle': '', 'Total': '1000000', 'Percent_Change': '1%'}, {'Year': 2021, 'Country_Name': 'SLOVENIA', 'Nbr_Cars': '95797', 'Nbr_Commercial_Vehicle': '', 'Total': '95797', 'Percent_Change': '-32%'}, {'Year': 2021, 'Country_Name': 'SOUTH AFRICA', 'Nbr_Cars': '239267', 'Nbr_Commercial_Vehicle': '259820', 'Total': '499087', 'Percent_Change': '12%'}, {'Year': 2021, 'Country_Name': 'SOUTH KOREA', 'Nbr_Cars': '3162727', 'Nbr_Commercial_Vehicle': '299677', 'Total': '3462404', 'Percent_Change': '-1%'}, {'Year': 2021, 'Country_Name': 'SPAIN', 'Nbr_Cars': '1662174', 'Nbr_Commercial_Vehicle': '435959', 'Total': '2098133', 'Percent_Change': '-8%'}, {'Year': 2021, 'Country_Name': 'TAIWAN', 'Nbr_Cars': '196749', 'Nbr_Commercial_Vehicle': '68571', 'Total': '265320', 'Percent_Change': '8%'}, {'Year': 2021, 'Country_Name': 'THAILAND', 'Nbr_Cars': '594690', 'Nbr_Commercial_Vehicle': '1091015', 'Total': '1685705', 'Percent_Change': '18%'}, {'Year': 2021, 'Country_Name': 'TURKEY', 'Nbr_Cars': '782835', 'Nbr_Commercial_Vehicle': '493305', 'Total': '1276140', 'Percent_Change': '-2%'}, {'Year': 2021, 'Country_Name': 'UKRAINE', 'Nbr_Cars': '7342', 'Nbr_Commercial_Vehicle': '811', 'Total': '8153', 'Percent_Change': '65%'}, {'Year': 2021, 'Country_Name': 'UNITED KINGDOM', 'Nbr_Cars': '859575', 'Nbr_Commercial_Vehicle': '72913', 'Total': '932488', 'Percent_Change': '-6%'}, {'Year': 2021, 'Country_Name': 'USA', 'Nbr_Cars': '1563060', 'Nbr_Commercial_Vehicle': '7604154', 'Total': '9167214', 'Percent_Change': '4%'}, {'Year': 2021, 'Country_Name': 'UZBEKISTAN', 'Nbr_Cars': '236 667', 'Nbr_Commercial_Vehicle': '4982', 'Total': '241649', 'Percent_Change': '-15%'}, {'Year': 2021, 'Country_Name': 'OTHERS', 'Nbr_Cars': '1645014', 'Nbr_Commercial_Vehicle': '183930', 'Total': '1828944', 'Percent_Change': ''}, {'Year': 2021, 'Country_Name': 'TOTAL', 'Nbr_Cars': '57054295', 'Nbr_Commercial_Vehicle': '23091693', 'Total': '80145988', 'Percent_Change': '3%'}, {'Year': 2022, 'Country_Name': 'ARGENTINA', 'Nbr_Cars': '257505', 'Nbr_Commercial_Vehicle': '279388', 'Total': '536893', 'Percent_Change': '24%'}, {'Year': 2022, 'Country_Name': 'AUSTRIA', 'Nbr_Cars': '107500', 'Nbr_Commercial_Vehicle': '0', 'Total': '107500', 'Percent_Change': '-21%'}, {'Year': 2022, 'Country_Name': 'BELGIUM', 'Nbr_Cars': '232100', 'Nbr_Commercial_Vehicle': '44454', 'Total': '276554', 'Percent_Change': '6%'}, {'Year': 2022, 'Country_Name': 'BRAZIL', 'Nbr_Cars': '1824833', 'Nbr_Commercial_Vehicle': '544936', 'Total': '2369769', 'Percent_Change': '5%'}, {'Year': 2022, 'Country_Name': 'CANADA', 'Nbr_Cars': '289371', 'Nbr_Commercial_Vehicle': '939364', 'Total': '1228735', 'Percent_Change': '10%'}, {'Year': 2022, 'Country_Name': 'CHINA', 'Nbr_Cars': '23836083', 'Nbr_Commercial_Vehicle': '3184532', 'Total': '27020615', 'Percent_Change': '3%'}, {'Year': 2022, 'Country_Name': 'CZECH REPUBLIC', 'Nbr_Cars': '1217787', 'Nbr_Commercial_Vehicle': '6669', 'Total': '1224456', 'Percent_Change': '10%'}, {'Year': 2022, 'Country_Name': 'FINLAND', 'Nbr_Cars': '73044', 'Nbr_Commercial_Vehicle': '0', 'Total': '73044', 'Percent_Change': '-15%'}, {'Year': 2022, 'Country_Name': 'FRANCE', 'Nbr_Cars': '1010466', 'Nbr_Commercial_Vehicle': '372707', 'Total': '1383173', 'Percent_Change': '2%'}, {'Year': 2022, 'Country_Name': 'GERMANY', 'Nbr_Cars': '3480357', 'Nbr_Commercial_Vehicle': '197463', 'Total': '3677820', 'Percent_Change': '11%'}, {'Year': 2022, 'Country_Name': 'HUNGARY', 'Nbr_Cars': '441729', 'Nbr_Commercial_Vehicle': '0', 'Total': '441729', 'Percent_Change': '6%'}, {'Year': 2022, 'Country_Name': 'INDIA', 'Nbr_Cars': '4439039', 'Nbr_Commercial_Vehicle': '1017818', 'Total': '5456857', 'Percent_Change': '24%'}, {'Year': 2022, 'Country_Name': 'INDONESIA', 'Nbr_Cars': '1214250', 'Nbr_Commercial_Vehicle': '255896', 'Total': '1470146', 'Percent_Change': '31%'}, {'Year': 2022, 'Country_Name': 'ITALY', 'Nbr_Cars': '473194', 'Nbr_Commercial_Vehicle': '323200', 'Total': '796394', 'Percent_Change': '0%'}, {'Year': 2022, 'Country_Name': 'JAPAN', 'Nbr_Cars': '6566356', 'Nbr_Commercial_Vehicle': '1269163', 'Total': '7835519', 'Percent_Change': '0%'}, {'Year': 2022, 'Country_Name': 'KAZAKHSTAN', 'Nbr_Cars': '103345', 'Nbr_Commercial_Vehicle': '9195', 'Total': '112540', 'Percent_Change': '22%'}, {'Year': 2022, 'Country_Name': 'MALAYSIA', 'Nbr_Cars': '650190', 'Nbr_Commercial_Vehicle': '52085', 'Total': '702275', 'Percent_Change': '46%'}, {'Year': 2022, 'Country_Name': 'MOROCCO', 'Nbr_Cars': '404742', 'Nbr_Commercial_Vehicle': '60122', 'Total': '464864', 'Percent_Change': '15%'}, {'Year': 2022, 'Country_Name': 'MEXICO', 'Nbr_Cars': '658001', 'Nbr_Commercial_Vehicle': '2851071', 'Total': '3509072', 'Percent_Change': '10%'}, {'Year': 2022, 'Country_Name': 'POLAND', 'Nbr_Cars': '255100', 'Nbr_Commercial_Vehicle': '228740', 'Total': '483840', 'Percent_Change': '10%'}, {'Year': 2022, 'Country_Name': 'PORTUGAL', 'Nbr_Cars': '256018', 'Nbr_Commercial_Vehicle': '66386', 'Total': '322404', 'Percent_Change': '11%'}, {'Year': 2022, 'Country_Name': 'ROMANIA', 'Nbr_Cars': '509465', 'Nbr_Commercial_Vehicle': '0', 'Total': '509465', 'Percent_Change': '21%'}, {'Year': 2022, 'Country_Name': 'RUSSIA', 'Nbr_Cars': '448897', 'Nbr_Commercial_Vehicle': '159563', 'Total': '608460', 'Percent_Change': '-61%'}, {'Year': 2022, 'Country_Name': 'SERBIA', 'Nbr_Cars': '4358', 'Nbr_Commercial_Vehicle': '140', 'Total': '4498', 'Percent_Change': '-79%'}, {'Year': 2022, 'Country_Name': 'SLOVAKIA', 'Nbr_Cars': '1000000', 'Nbr_Commercial_Vehicle': '0', 'Total': '1000000', 'Percent_Change': '-3%'}, {'Year': 2022, 'Country_Name': 'SLOVENIA', 'Nbr_Cars': '68130', 'Nbr_Commercial_Vehicle': '0', 'Total': '68130', 'Percent_Change': '-29%'}, {'Year': 2022, 'Country_Name': 'SOUTH AFRICA', 'Nbr_Cars': '309423', 'Nbr_Commercial_Vehicle': '246466', 'Total': '555889', 'Percent_Change': '11%'}, {'Year': 2022, 'Country_Name': 'SOUTH KOREA', 'Nbr_Cars': '3438355', 'Nbr_Commercial_Vehicle': '318694', 'Total': '3757049', 'Percent_Change': '9%'}, {'Year': 2022, 'Country_Name': 'SPAIN', 'Nbr_Cars': '1785432', 'Nbr_Commercial_Vehicle': '434030', 'Total': '2219462', 'Percent_Change': '6%'}, {'Year': 2022, 'Country_Name': 'TAIWAN', 'Nbr_Cars': '191409', 'Nbr_Commercial_Vehicle': '69854', 'Total': '261263', 'Percent_Change': '-2%'}, {'Year': 2022, 'Country_Name': 'THAILAND', 'Nbr_Cars': '594057', 'Nbr_Commercial_Vehicle': '1289458', 'Total': '1883515', 'Percent_Change': '12%'}, {'Year': 2022, 'Country_Name': 'TURKEY', 'Nbr_Cars': '810889', 'Nbr_Commercial_Vehicle': '541759', 'Total': '1352648', 'Percent_Change': '6%'}, {'Year': 2022, 'Country_Name': 'UKRAINE', 'Nbr_Cars': '1490', 'Nbr_Commercial_Vehicle': '0', 'Total': '1490', 'Percent_Change': '-82%'}, {'Year': 2022, 'Country_Name': 'UNITED KINGDOM', 'Nbr_Cars': '775014', 'Nbr_Commercial_Vehicle': '101600', 'Total': '876614', 'Percent_Change': '-6%'}, {'Year': 2022, 'Country_Name': 'USA', 'Nbr_Cars': '1751736', 'Nbr_Commercial_Vehicle': '8308603', 'Total': '10060339', 'Percent_Change': '10%'}, {'Year': 2022, 'Country_Name': 'UZBEKISTAN', 'Nbr_Cars': '328118', 'Nbr_Commercial_Vehicle': '5451', 'Total': '333569', 'Percent_Change': '38%'}, {'Year': 2022, 'Country_Name': 'OTHERS', 'Nbr_Cars': '1790867', 'Nbr_Commercial_Vehicle': '239271', 'Total': '2030138', 'Percent_Change': ''}, {'Year': 2022, 'Country_Name': 'TOTAL', 'Nbr_Cars': '61598650', 'Nbr_Commercial_Vehicle': '23418078', 'Total': '85016728', 'Percent_Change': '6%'}, {'Year': 2023, 'Country_Name': 'ARGENTINA', 'Nbr_Cars': '304 783', 'Nbr_Commercial_Vehicle': '305 942', 'Total': '610 725', 'Percent_Change': '14%'}, {'Year': 2023, 'Country_Name': 'AUSTRIA', 'Nbr_Cars': '102 291', 'Nbr_Commercial_Vehicle': '11 900', 'Total': '114 191', 'Percent_Change': '-6%'}, {'Year': 2023, 'Country_Name': 'BELGIUM', 'Nbr_Cars': '285 159', 'Nbr_Commercial_Vehicle': '46 944', 'Total': '332 103', 'Percent_Change': '16%'}, {'Year': 2023, 'Country_Name': 'BRAZIL', 'Nbr_Cars': '1 781 612', 'Nbr_Commercial_Vehicle': '543 226', 'Total': '2 324 838', 'Percent_Change': '-2%'}, {'Year': 2023, 'Country_Name': 'CANADA', 'Nbr_Cars': '376 888', 'Nbr_Commercial_Vehicle': '1 176 138', 'Total': '1 553 026', 'Percent_Change': '26%'}, {'Year': 2023, 'Country_Name': 'CHINA', 'Nbr_Cars': '26 123 757', 'Nbr_Commercial_Vehicle': '4 037 209', 'Total': '30 160 966', 'Percent_Change': '12%'}, {'Year': 2023, 'Country_Name': 'CZECH REPUBLIC', 'Nbr_Cars': '1 397 816', 'Nbr_Commercial_Vehicle': '6 685', 'Total': '1 404 501', 'Percent_Change': '15%'}, {'Year': 2023, 'Country_Name': 'FINLAND', 'Nbr_Cars': '30 191', 'Nbr_Commercial_Vehicle': '', 'Total': '30 191', 'Percent_Change': '-59%'}, {'Year': 2023, 'Country_Name': 'FRANCE', 'Nbr_Cars': '1 026 690', 'Nbr_Commercial_Vehicle': '478 386', 'Total': '1 505 076', 'Percent_Change': '9%'}, {'Year': 2023, 'Country_Name': 'GERMANY', 'Nbr_Cars': '4 109 371', 'Nbr_Commercial_Vehicle': '', 'Total': '4 109 371', 'Percent_Change': '18%'}, {'Year': 2023, 'Country_Name': 'HUNGARY', 'Nbr_Cars': '507 225', 'Nbr_Commercial_Vehicle': '', 'Total': '507 225', 'Percent_Change': '15%'}, {'Year': 2023, 'Country_Name': 'INDIA', 'Nbr_Cars': '4 783 628', 'Nbr_Commercial_Vehicle': '1 067 879', 'Total': '5 851 507', 'Percent_Change': '7%'}, {'Year': 2023, 'Country_Name': 'INDONESIA', 'Nbr_Cars': '1 180 355', 'Nbr_Commercial_Vehicle': '215 362', 'Total': '1 395 717', 'Percent_Change': '-5%'}, {'Year': 2023, 'Country_Name': 'ITALY', 'Nbr_Cars': '541 953', 'Nbr_Commercial_Vehicle': '338 132', 'Total': '880 085', 'Percent_Change': '11%'}, {'Year': 2023, 'Country_Name': 'JAPAN', 'Nbr_Cars': '7 765 428', 'Nbr_Commercial_Vehicle': '1 232 012', 'Total': '8 997 440', 'Percent_Change': '15%'}, {'Year': 2023, 'Country_Name': 'KAZAKHSTAN', 'Nbr_Cars': '134 054', 'Nbr_Commercial_Vehicle': '12 935', 'Total': '146 989', 'Percent_Change': '30%'}, {'Year': 2023, 'Country_Name': 'MALAYSIA', 'Nbr_Cars': '724 891', 'Nbr_Commercial_Vehicle': '49 709', 'Total': '774 600', 'Percent_Change': '10%'}, {'Year': 2023, 'Country_Name': 'MOROCCO', 'Nbr_Cars': '471 950', 'Nbr_Commercial_Vehicle': '63 875', 'Total': '535 825', 'Percent_Change': '15%'}, {'Year': 2023, 'Country_Name': 'MEXICO', 'Nbr_Cars': '903 753', 'Nbr_Commercial_Vehicle': '3 098 294', 'Total': '4 002 047', 'Percent_Change': '14%'}, {'Year': 2023, 'Country_Name': 'POLAND', 'Nbr_Cars': '299 300', 'Nbr_Commercial_Vehicle': '313 582', 'Total': '612 882', 'Percent_Change': '27%'}, {'Year': 2023, 'Country_Name': 'PORTUGAL', 'Nbr_Cars': '243 201', 'Nbr_Commercial_Vehicle': '75 030', 'Total': '318 231', 'Percent_Change': '-1%'}, {'Year': 2023, 'Country_Name': 'ROMANIA', 'Nbr_Cars': '513 050', 'Nbr_Commercial_Vehicle': '', 'Total': '513 050', 'Percent_Change': '1%'}, {'Year': 2023, 'Country_Name': 'RUSSIA', 'Nbr_Cars': '526 439', 'Nbr_Commercial_Vehicle': '203 425', 'Total': '729 864', 'Percent_Change': '20%'}, {'Year': 2023, 'Country_Name': 'SLOVAKIA', 'Nbr_Cars': '1 080 000', 'Nbr_Commercial_Vehicle': '', 'Total': '1 080 000', 'Percent_Change': '10%'}, {'Year': 2023, 'Country_Name': 'SLOVENIA', 'Nbr_Cars': '60 881', 'Nbr_Commercial_Vehicle': '', 'Total': '60 881', 'Percent_Change': '-11%'}, {'Year': 2023, 'Country_Name': 'SOUTH AFRICA', 'Nbr_Cars': '336 980', 'Nbr_Commercial_Vehicle': '296 357', 'Total': '633 337', 'Percent_Change': '14%'}, {'Year': 2023, 'Country_Name': 'SOUTH KOREA', 'Nbr_Cars': '3 908 747', 'Nbr_Commercial_Vehicle': '334 850', 'Total': '4 243 597', 'Percent_Change': '13%'}, {'Year': 2023, 'Country_Name': 'SPAIN', 'Nbr_Cars': '1 907 050', 'Nbr_Commercial_Vehicle': '544 171', 'Total': '2 451 221', 'Percent_Change': '10%'}, {'Year': 2023, 'Country_Name': 'TAIWAN', 'Nbr_Cars': '221 329', 'Nbr_Commercial_Vehicle': '64 633', 'Total': '285 962', 'Percent_Change': '10%'}, {'Year': 2023, 'Country_Name': 'THAILAND', 'Nbr_Cars': '580 857', 'Nbr_Commercial_Vehicle': '1 260 806', 'Total': '1 841 663', 'Percent_Change': '-2%'}, {'Year': 2023, 'Country_Name': 'TURKEY', 'Nbr_Cars': '952 667', 'Nbr_Commercial_Vehicle': '515 726', 'Total': '1 468 393', 'Percent_Change': '9%'}, {'Year': 2023, 'Country_Name': 'UKRAINE', 'Nbr_Cars': '1 993', 'Nbr_Commercial_Vehicle': '', 'Total': '1 993', 'Percent_Change': '34%'}, {'Year': 2023, 'Country_Name': 'UNITED KINGDOM', 'Nbr_Cars': '905 117', 'Nbr_Commercial_Vehicle': '120 357', 'Total': '1 025 474', 'Percent_Change': '17%'}, {'Year': 2023, 'Country_Name': 'USA', 'Nbr_Cars': '1 745 171', 'Nbr_Commercial_Vehicle': '8 866 384', 'Total': '10 611 555', 'Percent_Change': '6%'}, {'Year': 2023, 'Country_Name': 'UZBEKISTAN', 'Nbr_Cars': '421 414', 'Nbr_Commercial_Vehicle': '4 462', 'Total': '425 876', 'Percent_Change': '25%'}, {'Year': 2023, 'Country_Name': 'OTHERS', 'Nbr_Cars': '877 579', 'Nbr_Commercial_Vehicle': '1 128 618', 'Total': '2 006 197', 'Percent_Change': ''}, {'Year': 2023, 'Country_Name': 'TOTAL', 'Nbr_Cars': '67 133 570', 'Nbr_Commercial_Vehicle': '26 413 029', 'Total': '93 546 599', 'Percent_Change': '10%'}, {'Year': 2023, 'Country_Name': '', 'Nbr_Cars': '', 'Nbr_Commercial_Vehicle': '', 'Total': '', 'Percent_Change': ''}, {'Year': 2023, 'Country_Name': '', 'Nbr_Cars': '', 'Nbr_Commercial_Vehicle': '', 'Total': '', 'Percent_Change': ''}]

Recherche des continents¶

Problématique : le site sur lequel nous sommes tombés permet de récupérer les données en scrappant, ou en téléchargeant le format CSV. Les CSV permettent de connaitre les continents. Mais la mise en page change souvent. Or pour notre analyse, et présenter sous forme de carte, nous aimerions afficher également les continents.

Après des recherches, nous avons trouvés des modules Python dédiés afin de trouver le continent d'un pays donné :

  • AWOC
  • PyCountry Convert

Après plusieurs tests, nous avons préféré le deuxième module, il y avait moins de problème sur notre fichier CSV.

Pycontry Convert : Exemple¶

In [5]:
def get_continent(country_alpha2):
    try:
        continent_code = pc.country_alpha2_to_continent_code(country_alpha2)
        continent_name = pc.convert_continent_code_to_continent_name(continent_code)
        return continent_name
    except ValueError:
        return None

country_alpha2 = "US"  # Code ISO 3166-1 alpha-2 des États-Unis
continent = get_continent(country_alpha2)

if continent:
    print(f"Le continent de {country_alpha2} est {continent}.")
else:
    print(f"Impossible de déterminer le continent pour {country_alpha2}.")

Le continent de US est North America.

Amélioration du dataset¶

In [6]:
df = pd.read_csv(f"datasets/world_car_production_{begin_year}_{end_year}.csv", delimiter=";")

df.head()
Out[6]:
Year Country_Name Nbr_Cars Nbr_Commercial_Vehicle Total Percent_Change
0 2000 Argentina 238,921 100,711 339,632 11.4%
1 2000 Australia 323,649 23,473 347,122 14.6%
2 2000 Austria 115,979 25,047 141,026 1.2%
3 2000 Belgium 912,233 121,061 1,033,294 1.6%
4 2000 Brazil 1,351,998 329,519 1,681,517 24.5%

Pour chaque année Year, on trouve la liste des principaux pays Country_Name producteurs, avec :

  • Le nombre de voitures particulières Nbr_Cars
  • Le nombre de voitures commerciales Nbr_Commercial_Vehicle
  • Le total des 2 Total
  • Le pourcentage d'évolution par rapport à l'année précédente Percent_Change
In [7]:
df.columns
Out[7]:
Index(['Year', 'Country_Name', 'Nbr_Cars', 'Nbr_Commercial_Vehicle', 'Total',
       'Percent_Change'],
      dtype='object')

Rajout des continents¶

Afin de réaliser notre storytelling, nous souhaitons faire une étude par pays, mais également pas continent et dans le monde. Il faut alors ajouter une colonne continent pour nos données

Certains pays posent problème car il ne sont pas formatés correctement pour pycountry_convert. Nous remplaçons alors leur nom par un format adéquat.

In [8]:
# Correct format for Czech Republic
df['Country_Name'] = df['Country_Name'].replace('Czech Rep.', 'Czechia')

# Correct format for United Kingdom
df['Country_Name'] = df['Country_Name'].replace('UK', 'United Kingdom')

Cette fonction permet de récupérer le con d'un continent via le code pays. Elle permet également d'ommetre les lignes Total, Supplementary et Others, qui ne sont pas des pays.

In [9]:
def get_continent_name(row):
    """
      Get the continent code for a dataframe's row
    """
    try:
        if type(row.Country_Name) == float:
            return

        if row.Country_Name.lower() == 'total':
            return 'Entire World'

        if row.Country_Name.lower() == 'supplementary':
            row.Country_Name = 'Others'

        if row.Country_Name.lower() == 'others':
            return 'Other'

        country_alpha2 = pc.country_name_to_country_alpha2(row.Country_Name.title() if row.Country_Name != 'USA' else row.Country_Name, cn_name_format="default")
        # print(row.Country_Name)
        continent_code = pc.country_alpha2_to_continent_code(country_alpha2)
        continent_name = pc.convert_continent_code_to_continent_name(continent_code)

        return continent_name

    except (ValueError, KeyError, TypeError) as e:
        print(f"Erreur lors de la conversion pour {row.Country_Name}: {e}")
        return None

Application de la fonction à chaque ligne du dataframe

In [10]:
df['Continent'] = df.apply(get_continent_name, axis=1)

c:\Users\Luc\Projets\Ynov\analyse_auto\env\Lib\site-packages\pycountry\db.py:51: UserWarning: Country's official_name not found. Country name provided instead.
  warnings.warn(warning_message, UserWarning)
c:\Users\Luc\Projets\Ynov\analyse_auto\env\Lib\site-packages\pycountry\db.py:51: UserWarning: Country's common_name not found. Country name provided instead.
  warnings.warn(warning_message, UserWarning)

Ainsi, une nouvelle colonne Continent a été créée

In [11]:
df.head()
Out[11]:
Year Country_Name Nbr_Cars Nbr_Commercial_Vehicle Total Percent_Change Continent
0 2000 Argentina 238,921 100,711 339,632 11.4% South America
1 2000 Australia 323,649 23,473 347,122 14.6% Oceania
2 2000 Austria 115,979 25,047 141,026 1.2% Europe
3 2000 Belgium 912,233 121,061 1,033,294 1.6% Europe
4 2000 Brazil 1,351,998 329,519 1,681,517 24.5% South America

Gestion des types¶

Afin de pouvoir faire une analyse correcte, il faut que les colonnes soient correctement typées.

In [12]:
df.dtypes
Out[12]:
Year                       int64
Country_Name              object
Nbr_Cars                  object
Nbr_Commercial_Vehicle    object
Total                     object
Percent_Change            object
Continent                 object
dtype: object

Convertir la colonne Year en DateTime

In [13]:
df['Year'] = pd.to_datetime(df['Year'], format='%Y')
In [14]:
df.head(1)
Out[14]:
Year Country_Name Nbr_Cars Nbr_Commercial_Vehicle Total Percent_Change Continent
0 2000-01-01 Argentina 238,921 100,711 339,632 11.4% South America

Supprimer les lignes ayant des valeurs nulles dans le dataframe

In [15]:
df = df.dropna(subset=['Country_Name'])

Mettre les colonne Nbr_Cars, Nbr_Commercial_Vehicle et Total en format numérique.

In [16]:
df.dtypes
Out[16]:
Year                      datetime64[ns]
Country_Name                      object
Nbr_Cars                          object
Nbr_Commercial_Vehicle            object
Total                             object
Percent_Change                    object
Continent                         object
dtype: object

Enlever les virgules des entiers¶

Nous décidons d'enlever les virgules pour le moment, pour pouvoir mettre ces valeurs en tant qu'entiers sur les applications que nous utiliserons ou non, comme PowerBI, qui n'accepte pas les entiers qui sont de la forme 2,555,555. Nous allons les mettre de la forme 2555555 et tester également de la forme 2.555.555.

In [17]:
dot_to_delete_cols = ['Nbr_Cars', 'Nbr_Commercial_Vehicle',	'Total']

for col in dot_to_delete_cols:
    df[col] = df[col].replace(',', '', regex=True)
    df[col] = df[col].replace(' ', '', regex=True)
In [18]:
df.head(1)
Out[18]:
Year Country_Name Nbr_Cars Nbr_Commercial_Vehicle Total Percent_Change Continent
0 2000-01-01 Argentina 238921 100711 339632 11.4% South America

Mettre des points pour les pourcentages¶

Nous avons également remarqué que la colonnes Percent_Change avait des erreurs.

Pour être au bon format, il faut remplacer les , par des ., et les %% par %.

In [19]:
dot_to_point_col = ['Percent_Change']

for col in dot_to_point_col:
    df[col] = df[col].replace(',', '.', regex=True)
    df[col] = df[col].replace('%%', '%', regex=True)

Mettre le nom des pays en capitales¶

Afin que les pays soient tous écrits de la même manière

In [20]:
df['Country_Name'] = df['Country_Name'].str.capitalize()

Enlever les lignes "total"¶

Enlever les lignes totales pour qu'elles ne soient pas prises en comptes lors des visuels (exmeple: USA = 5000; France = 4000; Total = 9000).

Lors des visuels, la valeur va prende 18000, car elle va aussi compter le total.

A partir de 2015, des lignes permettant de voir le Total apparaissent, et faussent donc les données.

Remplacer les valeurs nulles, ou autre que des chiffres par 0¶

In [21]:
columns = ['Nbr_Cars', 'Nbr_Commercial_Vehicle', 'Total', 'Percent_Change']
In [22]:
for col in columns:
    df[col] = df[col].replace({'-': 0, 'N.A.': 0}).fillna(0)

Mettre les colonne Nbr_Cars, Nbr_Commercial_Vehicle et Total en format numérique.

In [23]:
df['Nbr_Cars'] = pd.to_numeric(df['Nbr_Cars'])
df['Nbr_Commercial_Vehicle'] = pd.to_numeric(df['Nbr_Commercial_Vehicle'])
df['Total'] = pd.to_numeric(df['Total'])

Rajouter des '%' pour chaque valeur de la colonne de pourcentage d'évolution¶

Car certaines valeurs de cette colonnes n'ont pas ce symbole

In [24]:
def add_percent(value):
    if isinstance(value, str) and not value.endswith('%'):
        return value + '%'
    elif isinstance(value, (int, float)):
        return str(value) + '%'
    else:
        return value

df['Percent_Change'] = df['Percent_Change'].apply(add_percent)

Statistiques¶

Créer un fonction qui prend en paramètre une date (format YYYY-MM-DD), un pays ou un continent. Et affiche la repartition des types de véhicules sur le total

In [25]:
def plot_data(row):
    labels = ['Voitures', 'Véhicules commerciaux']
    sizes = [row['Car_Percentage'], row['Commercial_Vehicle_Percentage']]
    colors = ['#ff9999','#66b3ff']
    explode = (0.1, 0)  # "explode" la première tranche (Voitures)

    # Tracer le camembert
    plt.figure(figsize=(3, 3))
    plt.pie(sizes, explode=explode, labels=labels, colors=colors,
            shadow=True, startangle=140)
    plt.title(f"Répartition des types de véhicules en {row['Year']} pour {row['Country_Name']}")
    plt.show()

def get_place_list(df):
    return df['Country_Name'].unique(), df['Continent'].unique()

def repartition_vehicles(date, place):
    filtered_df = df[df['Year'] == date]
    countries, continents = get_place_list(df=df)

    if place in countries:
        filtered_df = filtered_df[filtered_df['Country_Name'] == place]
    elif place in continents:
        filtered_df = filtered_df[filtered_df['Continent'] == place]

    if filtered_df.empty:
        print("Aucune donnée trouvée pour les critères spécifiés.")
        return

    # Calculer la répartition des types de véhicules
    filtered_df['Car_Percentage'] = (filtered_df['Nbr_Cars'] / filtered_df['Total']) * 100
    filtered_df['Commercial_Vehicle_Percentage'] = (filtered_df['Nbr_Commercial_Vehicle'] / filtered_df['Total']) * 100

    # print(filtered_df)

    # Afficher les résultats
    for index, row in filtered_df.iterrows():
        # print(row)
        print(f"Pour {row['Country_Name']} en {row['Year']}:")
        print(f"  - Pourcentage de voitures : {row['Car_Percentage']:.2f}%")
        print(f"  - Pourcentage de véhicules commerciaux : {row['Commercial_Vehicle_Percentage']:.2f}%\n")
        plot_data(row)

repartition_vehicles("2000-01-01", place="Brazil")
# repartition_vehicles("2020-01-01", place="France")

Pour Brazil en 2000-01-01 00:00:00:
  - Pourcentage de voitures : 80.40%
  - Pourcentage de véhicules commerciaux : 19.60%
In [27]:
def plot_vehicle_evolution(country=None, continent=None):
    filtered_df = df.copy()

    if country:
        filtered_df = filtered_df[filtered_df['Country_Name'] == country]
    elif continent:
        filtered_df = filtered_df[filtered_df['Continent'] == continent]
        # filtered_df = filtered_df.groupby('Year').agg({
        #             'Nbr_Cars': 'sum',
        #             'Nbr_Commercial_Vehicle': 'sum'
        #         }).reset_index()
    if filtered_df.empty:
        print("Aucune donnée trouvée pour les critères spécifiés.")
        return

    # print(filtered_df)

    plt.figure(figsize=(10, 6))

    plt.plot(filtered_df['Year'], filtered_df['Nbr_Cars'], marker='o', label='Particuliers')
    plt.plot(filtered_df['Year'], filtered_df['Nbr_Commercial_Vehicle'], marker='o', label='Commerciaux')

    plt.xlabel('Année')
    plt.ylabel('Nombre de véhicules')
    plt.title(f"Évolution du nombre de véhicules {'pour ' + country if country else 'en ' + continent}")
    plt.legend()
    plt.grid(True)

    plt.show()

plot_vehicle_evolution(country="Usa")

Exporter DataFrame nettoyé en CSV¶

In [28]:
filename_to_save = f'datasets/world_car_production_{begin_year}-{end_year}_cleaned.csv'
df.to_csv(filename_to_save, index=False, sep=';')

PBI : Fichier > Options et paramètres > Options > Fonctionnalités en préversion > Intéractions sur l'objet => ACTIVER

Prévisions production¶

In [29]:
df_production = pd.read_csv('datasets/world_car_production_2000-2023_cleaned.csv', sep=';')
In [30]:
df_production.dtypes
Out[30]:
Year                      object
Country_Name              object
Nbr_Cars                   int64
Nbr_Commercial_Vehicle     int64
Total                      int64
Percent_Change            object
Continent                 object
dtype: object
In [31]:
df_production['Year'] = pd.to_datetime(df_production['Year'])
In [ ]:
# df_production['Year'] = df_production['Year'].dt.year
In [32]:
df_production.dtypes
Out[32]:
Year                      datetime64[ns]
Country_Name                      object
Nbr_Cars                           int64
Nbr_Commercial_Vehicle             int64
Total                              int64
Percent_Change                    object
Continent                         object
dtype: object
In [33]:
len(df_production['Country_Name'].unique())
Out[33]:
46
In [34]:
warnings.filterwarnings('ignore')

def sarima_forecast(country_name, data):
    print(country_name)
    """
    This function makes a forecast for a given country using the SARIMA model.

    Args:
        country_name: The name of the country to forecast for.
        data: The Pandas dataframe containing the population data.

    Returns:
        A tuple containing the SARIMA model, the predicted values, and the confidence intervals.
    """
    # Filter the data for the given country.
    df_out = data[data['Country_Name'] == country_name].copy()
    df_out.set_index('Year', inplace=True)

    # print(df_out)

    # Train the SARIMA model.
    model = SARIMAX(df_out['Total'], order=(2, 1, 2), seasonal_order=(1, 0, 1, 12))
    results = model.fit()

    # Make predictions.
    forecast_horizon = 10
    forecast = results.get_forecast(steps=forecast_horizon)
    predictions = forecast.predicted_mean
    conf_int = forecast.conf_int()

    return model, predictions, conf_int, df_out

countries = df_production['Country_Name'].unique()
# countries = ['France']
# countries = ['Afghanistan', 'Africa (UN)', 'Albania', 'Algeria',
#        'American Samoa', 'Andorra', 'Angola']

predictions_list = []

for country in countries:
    # try:
    country_data = df_production[df_production['Country_Name'] == country]
    country_data['Year'] = pd.to_datetime(country_data['Year'], format='%Y')
    # print(country)
    model, predictions, conf_int, df_out = sarima_forecast(country, country_data)
    predictions.index = pd.date_range(start=df_out.index[-1] + pd.offsets.YearEnd(1), periods=10, freq='Y')
    conf_int.index = predictions.index

    # Create a new dataframe with the predictions and confidence intervals
    predictions_df = pd.DataFrame({
        'Country_Name': country,
        'Year': predictions.index,
        'Total': predictions.values,
        'Lower CI': conf_int.iloc[:, 0].values,
        'Upper CI': conf_int.iloc[:, 1].values
    })

    # Add the predictions dataframe to the list
    predictions_list.append(predictions_df)

    # except ValueError as e:
      # print(f"Skipping country {country} due to error: {e}")

df_production_with_all_predictions = pd.concat([df_production] + predictions_list, ignore_index=True)

Argentina
Australia
Austria
Belgium
Brazil
Canada
China
Czechia
Egypt
Finland
France
Germany
Hungary
India
Indonesia
Iran
Italy
Japan
Malaysia
Mexico
Netherlands
Poland
Portugal
Romania
Russia
Serbia
Slovakia
Slovenia
South africa
South korea
Spain
Sweden
Taiwan
Thailand
Turkey
Ukraine
United kingdom
Usa
Uzbekistan
Others
Supplementary
Total
Morocco
Colombia
Czech republic
Kazakhstan
In [35]:
df_production_with_all_predictions[df_production_with_all_predictions['Country_Name'] == 'France']
Out[35]:
Year Country_Name Nbr_Cars Nbr_Commercial_Vehicle Total Percent_Change Continent Lower CI Upper CI
10 2000-01-01 France 2879810.0 468551.0 3.348361e+06 5.3% Europe NaN NaN
50 2001-01-01 France 3181549.0 446869.0 3.628418e+06 8.4% Europe NaN NaN
90 2002-01-01 France 3292797.0 309073.0 3.601870e+06 -0.7% Europe NaN NaN
130 2003-01-01 France 3220329.0 399737.0 3.620066e+06 0.5% Europe NaN NaN
170 2004-01-01 France 3227416.0 438574.0 3.665990e+06 1.3% Europe NaN NaN
210 2005-01-01 France 3112961.0 436047.0 3.549008e+06 -3.2% Europe NaN NaN
250 2006-01-01 France 2723196.0 446023.0 3.169219e+06 -10.7% Europe NaN NaN
290 2007-01-01 France 2550869.0 464985.0 3.015854e+06 -4.8% Europe NaN NaN
330 2008-01-01 France 2145935.0 423043.0 2.568978e+06 -14.8% Europe NaN NaN
370 2009-01-01 France 1819497.0 228196.0 2.047693e+06 -20.3% Europe NaN NaN
410 2010-01-01 France 1924171.0 305250.0 2.229421e+06 8.9% Europe NaN NaN
450 2011-01-01 France 1931030.0 311898.0 2.242928e+06 0.6% Europe NaN NaN
490 2012-01-01 France 1682814.0 284951.0 1.967765e+06 -12.3% Europe NaN NaN
530 2013-01-01 France 1458220.0 282000.0 1.740220e+06 -11.6% Europe NaN NaN
570 2014-01-01 France 1499464.0 322000.0 1.821464e+06 4.7% Europe NaN NaN
610 2015-01-01 France 1553800.0 416200.0 1.970000e+06 8.2% Europe NaN NaN
651 2016-01-01 France 1626000.0 456000.0 2.082000e+06 5.6% Europe NaN NaN
691 2017-01-01 France 1748000.0 479000.0 2.227000e+06 6.54% Europe NaN NaN
732 2018-01-01 France 1763000.0 507000.0 2.270000e+06 2.0% Europe NaN NaN
771 2019-01-01 France 1675198.0 527262.0 2.202460e+06 -2.9% Europe NaN NaN
810 2020-01-01 France 927718.0 388653.0 1.316371e+06 -39% Europe NaN NaN
850 2021-01-01 France 917907.0 433401.0 1.351308e+06 3% Europe NaN NaN
888 2022-01-01 France 1010466.0 372707.0 1.383173e+06 2% Europe NaN NaN
926 2023-01-01 France 1026690.0 478386.0 1.505076e+06 9% Europe NaN NaN
1055 2023-12-31 France NaN NaN 1.647193e+06 NaN NaN 1.084779e+06 2.209608e+06
1056 2024-12-31 France NaN NaN 1.666992e+06 NaN NaN 8.270410e+05 2.506943e+06
1057 2025-12-31 France NaN NaN 1.662683e+06 NaN NaN 6.187287e+05 2.706636e+06
1058 2026-12-31 France NaN NaN 1.656163e+06 NaN NaN 4.407225e+05 2.871603e+06
1059 2027-12-31 France NaN NaN 1.652398e+06 NaN NaN 2.868650e+05 3.017931e+06
1060 2028-12-31 France NaN NaN 1.641368e+06 NaN NaN 1.406354e+05 3.142101e+06
1061 2029-12-31 France NaN NaN 1.626116e+06 NaN NaN 1.393879e+03 3.250838e+06
1062 2030-12-31 France NaN NaN 1.624021e+06 NaN NaN -1.158787e+05 3.363920e+06
1063 2031-12-31 France NaN NaN 1.651089e+06 NaN NaN -1.968233e+05 3.499001e+06
1064 2032-12-31 France NaN NaN 1.630952e+06 NaN NaN -3.189994e+05 3.580903e+06
In [36]:
df_production_with_all_predictions.to_csv('previsions/previsions_world_car_production.csv', index=False)
In [37]:
df_production_with_all_predictions['Year'] = pd.to_datetime(df_production_with_all_predictions['Year'], errors='coerce', format="%Y")

df_production_with_all_predictions['Year'] = df_production_with_all_predictions['Year'].dt.year

france_data = df_production_with_all_predictions[df_production_with_all_predictions['Country_Name'] == 'Argentina']

plt.figure(figsize=(12, 6))

plt.plot(france_data['Year'], france_data['Total'], label='Actual Total')

predicted_data = france_data[france_data['Lower CI'].notnull()]
plt.plot(predicted_data['Year'], predicted_data['Total'], label='Predicted Total', color='red')

plt.fill_between(predicted_data['Year'], predicted_data['Lower CI'], predicted_data['Upper CI'], color='green', alpha=0.3, label='Confidence Interval')

plt.title('Total Car Production in France with SARIMA Predictions')
plt.xlabel('Year')
plt.ylabel('Total Production')
plt.legend()
plt.show()

Evolution des ventes de véhicules¶

pays, où on a trouvé les données ?

In [38]:
df_car_sales = pd.read_csv('datasets/car_country_sales.csv')

df_car_sales.columns = ['Year', 'Sales', 'Country']

df_car_sales['Sales'] = df_car_sales['Sales'].replace(',', '', regex=True)
df_car_sales['Sales'] = df_car_sales['Sales'].replace('\.', '', regex=True)
df_car_sales['Sales'] = df_car_sales['Sales'].replace(' ', '', regex=True)
df_car_sales['Sales'] = pd.to_numeric(df_car_sales['Sales'])

df_car_sales_japan = df_car_sales[df_car_sales['Country'] == 'Japan']
df_car_sales_usa = df_car_sales[df_car_sales['Country'] == 'US']
df_car_sales_france = df_car_sales[df_car_sales['Country'] == 'France']
df_car_sales_sweden = df_car_sales[df_car_sales['Country'] == 'Sweden']

plt.plot(df_car_sales_japan['Year'], df_car_sales_japan['Sales'])
plt.title('Evolution des ventes de voitures au Japon')
plt.xlabel('Années')
plt.ylabel('Ventes des voitures')
plt.show()
In [39]:
df_car_sales.describe()
Out[39]:
Year Sales
count 71.000000 7.000000e+01
mean 2013.619718 3.125155e+06
std 5.161302 2.382378e+06
min 2005.000000 2.134080e+05
25% 2009.000000 6.667948e+05
50% 2014.000000 2.259500e+06
75% 2018.000000 4.569820e+06
max 2022.000000 7.762000e+06
In [40]:
df_sales_to_analyze = df_car_sales[['Country', 'Year', 'Sales']]
df_sales_to_analyze.head()
Out[40]:
Country Year Sales
0 Japan 2006 4612318.0
1 Japan 2007 4325508.0
2 Japan 2008 4184266.0
3 Japan 2009 3905310.0
4 Japan 2010 4203181.0
In [41]:
import warnings
warnings.filterwarnings('ignore')

def sarima_forecast(country_name, data):
    print(country_name)
    """
    This function makes a forecast for a given country using the SARIMA model.

    Args:
        country_name: The name of the country to forecast for.
        data: The Pandas dataframe containing the population data.

    Returns:
        A tuple containing the SARIMA model, the predicted values, and the confidence intervals.
    """
    # Filter the data for the given country.
    df_out = data[data['Country'] == country_name].copy()
    df_out.set_index('Year', inplace=True)

    # Train the SARIMA model.
    model = SARIMAX(df_out['Sales'], order=(2, 1, 2), seasonal_order=(1, 0, 1, 12))
    results = model.fit()

    # Make predictions.
    forecast_horizon = 10
    forecast = results.get_forecast(steps=forecast_horizon)
    predictions = forecast.predicted_mean
    conf_int = forecast.conf_int()

    return model, predictions, conf_int, df_out

countries = df_sales_to_analyze['Country'].unique()

predictions_list = []

for country in countries:
    try:
      df_sales_to_analyze['Year'] = pd.to_datetime(df_sales_to_analyze['Year'], format='%Y')
      # df_sales_to_analyze.set_index('Year', inplace=True)  # Set 'Year' as index
      model, predictions, conf_int, df_out = sarima_forecast(country, df_sales_to_analyze)
      # start_date = df.index[-1] + pd.offsets.YearBegin(-1)
      # predictions.index = pd.date_range(start=start_date, periods=10, freq='Y')
      predictions.index = pd.date_range(start=df_out.index[-1] + pd.offsets.YearEnd(1), periods=10, freq='Y')
      conf_int.index = predictions.index

      # Create a new dataframe with the predictions and confidence intervals
      predictions_df = pd.DataFrame({
          'Country': country,
          'Year': predictions.index,
          'Sales': predictions.values,
          'Lower CI': conf_int.iloc[:, 0].values,
          'Upper CI': conf_int.iloc[:, 1].values
      })

      # Add the predictions dataframe to the list
      predictions_list.append(predictions_df)

    except ValueError as e:
      print(f"Skipping country {country} due to error: {e}")

df_sales_with_all_predictions = pd.concat([df_sales_to_analyze] + predictions_list, ignore_index=True)

Japan
US
Sweden
France
In [42]:
df_sales_with_all_predictions[df_sales_with_all_predictions['Country'] == 'Sweden']
Out[42]:
Country Year Sales Lower CI Upper CI
35 Sweden 2005-01-01 274301.000000 NaN NaN
36 Sweden 2006-01-01 282766.000000 NaN NaN
37 Sweden 2007-01-01 306799.000000 NaN NaN
38 Sweden 2008-01-01 253982.000000 NaN NaN
39 Sweden 2009-01-01 213408.000000 NaN NaN
40 Sweden 2010-01-01 289684.000000 NaN NaN
41 Sweden 2011-01-01 304984.000000 NaN NaN
42 Sweden 2012-01-01 279899.000000 NaN NaN
43 Sweden 2013-01-01 268599.000000 NaN NaN
44 Sweden 2014-01-01 303948.000000 NaN NaN
45 Sweden 2015-01-01 345108.000000 NaN NaN
46 Sweden 2016-01-01 372318.000000 NaN NaN
47 Sweden 2017-01-01 379393.000000 NaN NaN
48 Sweden 2018-01-01 353729.000000 NaN NaN
49 Sweden 2019-01-01 356036.000000 NaN NaN
50 Sweden 2020-01-01 292024.000000 NaN NaN
51 Sweden 2021-01-01 301006.000000 NaN NaN
52 Sweden 2022-01-01 288087.000000 NaN NaN
91 Sweden 2022-12-31 297391.336159 237042.886500 357739.785817
92 Sweden 2023-12-31 299030.428730 207796.897651 390263.959809
93 Sweden 2024-12-31 292611.335230 169430.869224 415791.801236
94 Sweden 2025-12-31 293424.790023 148916.107063 437933.472983
95 Sweden 2026-12-31 298877.041202 139689.610926 458064.471478
96 Sweden 2027-12-31 299579.534333 124568.907969 474590.160698
97 Sweden 2028-12-31 288030.529084 96481.848188 479579.209980
98 Sweden 2029-12-31 286621.270674 81560.465350 491682.075998
99 Sweden 2030-12-31 288007.799317 71217.432258 504798.166376
100 Sweden 2031-12-31 286707.446074 57684.733202 515730.158945
In [43]:
df_sales_with_all_predictions.to_csv('previsions/previsions_car_sales.csv', index=False)

Analyses population¶

Import¶

In [44]:
df_population = pd.read_csv('datasets/population_1950_2021.csv')
df_population.head()
Out[44]:
Country name Year Population Population of children under the age of 1 Population of children under the age of 5 Population of children under the age of 15 Population under the age of 25 Population aged 15 to 64 years Population older than 15 years Population older than 18 years ... population__all__50_54__records population__all__55_59__records population__all__60_64__records population__all__65_69__records population__all__70_74__records population__all__75_79__records population__all__80_84__records population__all__85_89__records population__all__90_94__records population__all__95_99__records
0 Afghanistan 1950 7480464 301735.0 1248282 3068855 4494349 4198587 4411609 3946595 ... 255563 211607 161196 110709 64310 28381 8153 1346 115 8
1 Afghanistan 1951 7571542 299368.0 1246857 3105444 4552138 4250002 4466098 3993640 ... 256915 211966 161821 111465 65210 29148 8672 1483 109 9
2 Afghanistan 1952 7667534 305393.0 1248220 3145070 4613604 4303436 4522464 4041439 ... 258952 211946 162710 112142 66123 29903 9137 1584 129 10
3 Afghanistan 1953 7764549 311574.0 1254725 3186382 4676232 4356242 4578167 4088379 ... 261238 211731 163777 112800 67058 30647 9561 1693 155 11
4 Afghanistan 1954 7864289 317584.0 1267817 3231060 4741371 4408474 4633229 4136116 ... 263301 211816 164736 113474 67953 31345 9963 1830 179 11

5 rows × 40 columns

Nous créons un nouveau dataframe qui ne prend que les valeurs depuis 1999.

In [45]:
df_pop_99_21 = df_population.query('Year < 1950 or Year > 1998')
df_pop_99_21.head()
Out[45]:
Country name Year Population Population of children under the age of 1 Population of children under the age of 5 Population of children under the age of 15 Population under the age of 25 Population aged 15 to 64 years Population older than 15 years Population older than 18 years ... population__all__50_54__records population__all__55_59__records population__all__60_64__records population__all__65_69__records population__all__70_74__records population__all__75_79__records population__all__80_84__records population__all__85_89__records population__all__90_94__records population__all__95_99__records
49 Afghanistan 1999 19262854 895539.0 4005677 9538093 13136494 9284534 9724752 8519511 ... 484402 376737 288028 203661 130178 68573 28101 8086 1462 157
50 Afghanistan 2000 19542986 898809.0 4044487 9716430 13343836 9380030 9826547 8606509 ... 479745 381796 289607 205466 132016 70149 28863 8349 1511 163
51 Afghanistan 2001 19688634 894038.0 4046425 9817924 13458009 9420852 9870699 8634748 ... 469125 385166 288932 206038 132808 71270 29450 8560 1553 168
52 Afghanistan 2002 21000258 941149.0 4280854 10488288 14365919 10031304 10511959 9179506 ... 488363 411182 305420 219365 141488 76759 31864 9300 1699 180
53 Afghanistan 2003 22645136 999679.0 4574403 11313832 15499313 10811842 11331293 9877464 ... 517425 441537 327432 236283 152473 83529 34874 10217 1878 197

5 rows × 40 columns

In [46]:
df_pop_99_21.reset_index(drop=True, inplace=True)

Prévisions¶

Conversion de la colonne Year en DateTime

In [47]:
df_pop_99_21['Year'] = pd.to_datetime(df_pop_99_21['Year'], format='%Y')
df_pop_99_21.head()
Out[47]:
Country name Year Population Population of children under the age of 1 Population of children under the age of 5 Population of children under the age of 15 Population under the age of 25 Population aged 15 to 64 years Population older than 15 years Population older than 18 years ... population__all__50_54__records population__all__55_59__records population__all__60_64__records population__all__65_69__records population__all__70_74__records population__all__75_79__records population__all__80_84__records population__all__85_89__records population__all__90_94__records population__all__95_99__records
0 Afghanistan 1999-01-01 19262854 895539.0 4005677 9538093 13136494 9284534 9724752 8519511 ... 484402 376737 288028 203661 130178 68573 28101 8086 1462 157
1 Afghanistan 2000-01-01 19542986 898809.0 4044487 9716430 13343836 9380030 9826547 8606509 ... 479745 381796 289607 205466 132016 70149 28863 8349 1511 163
2 Afghanistan 2001-01-01 19688634 894038.0 4046425 9817924 13458009 9420852 9870699 8634748 ... 469125 385166 288932 206038 132808 71270 29450 8560 1553 168
3 Afghanistan 2002-01-01 21000258 941149.0 4280854 10488288 14365919 10031304 10511959 9179506 ... 488363 411182 305420 219365 141488 76759 31864 9300 1699 180
4 Afghanistan 2003-01-01 22645136 999679.0 4574403 11313832 15499313 10811842 11331293 9877464 ... 517425 441537 327432 236283 152473 83529 34874 10217 1878 197

5 rows × 40 columns

Nous ne nous interessons qu'à trois colonne pour cette analyse globale :

  • Country name
  • Year
  • Population

Pour la prévision, il va falloir créer un dataframe par pays contenant seulement ces trois colonne

In [48]:
df_pop_to_analyze = df_pop_99_21[['Country name', 'Year', 'Population']]
df_pop_to_analyze.head()
Out[48]:
Country name Year Population
0 Afghanistan 1999-01-01 19262854
1 Afghanistan 2000-01-01 19542986
2 Afghanistan 2001-01-01 19688634
3 Afghanistan 2002-01-01 21000258
4 Afghanistan 2003-01-01 22645136

Voici un exemple de la courbe de tendance d'évolution de la population, pour un pays donné

In [49]:
def get_country_data(data, country_name):
    """
    This function takes a country name and returns the rows of the dataframe corresponding to that country.

    Args:
        df_to_analyze: The Pandas dataframe to analyze.
        country_name: The name of the country to filter by.

    Returns:
        A Pandas dataframe containing the data for the specified country.
    """
    data = data[data['Country name'] == country_name]
    plt.plot(data['Year'], data['Population'])
    plt.title(f'Population Trend for {country_name}')
    plt.xlabel('Year')
    plt.ylabel('Population')
    plt.show()

    return data[data['Country name'] == country_name]

country_data = get_country_data(df_pop_to_analyze, 'France')
country_data
Out[49]:
Country name Year Population
1725 France 1999-01-01 58352210
1726 France 2000-01-01 58665456
1727 France 2001-01-01 59014776
1728 France 2002-01-01 59372784
1729 France 2003-01-01 59728260
1730 France 2004-01-01 60108436
1731 France 2005-01-01 60510080
1732 France 2006-01-01 60919150
1733 France 2007-01-01 61329380
1734 France 2008-01-01 61721004
1735 France 2009-01-01 62093300
1736 France 2010-01-01 62444570
1737 France 2011-01-01 62775270
1738 France 2012-01-01 63071412
1739 France 2013-01-01 63335180
1740 France 2014-01-01 63588496
1741 France 2015-01-01 63809770
1742 France 2016-01-01 63989320
1743 France 2017-01-01 64144092
1744 France 2018-01-01 64277812
1745 France 2019-01-01 64399760
1746 France 2020-01-01 64480052
1747 France 2021-01-01 64531450
In [50]:
import warnings
warnings.filterwarnings('ignore')

def sarima_forecast(country_name, data):
    print(country_name)
    """
    This function makes a forecast for a given country using the SARIMA model.

    Args:
        country_name: The name of the country to forecast for.
        data: The Pandas dataframe containing the population data.

    Returns:
        A tuple containing the SARIMA model, the predicted values, and the confidence intervals.
    """
    df_out = data[data['Country name'] == country_name].copy()
    df_out.set_index('Year', inplace=True)

    model = SARIMAX(df_out['Population'], order=(2, 1, 2), seasonal_order=(1, 0, 1, 12))
    results = model.fit()

    forecast_horizon = 10
    forecast = results.get_forecast(steps=forecast_horizon)
    predictions = forecast.predicted_mean
    conf_int = forecast.conf_int()

    return model, predictions, conf_int, df_out

countries = df_pop_to_analyze['Country name'].unique()

predictions_list = []

for country in countries:
    try:
      model, predictions, conf_int, df_out = sarima_forecast(country, df_pop_to_analyze)
      predictions.index = pd.date_range(start=df_out.index[-1] + pd.offsets.YearEnd(1), periods=10, freq='Y')
      conf_int.index = predictions.index

      predictions_df = pd.DataFrame({
          'Country name': country,
          'Year': predictions.index,
          'Population': predictions.values,
          'Lower CI': conf_int.iloc[:, 0].values,
          'Upper CI': conf_int.iloc[:, 1].values
      })

      predictions_list.append(predictions_df)

    except ValueError as e:
      print(f"Skipping country {country} due to error: {e}")

df_with_all_predictions = pd.concat([df_pop_to_analyze] + predictions_list, ignore_index=True)

country_name = 'France'
country_data = df_with_all_predictions[df_with_all_predictions['Country name'] == country_name]

plt.figure(figsize=(10, 6))
plt.plot(country_data['Year'], country_data['Population'], label='Actual')
plt.plot(predictions.index, predictions, label='Predicted', color='red')
plt.fill_between(predictions.index, conf_int.iloc[:, 0], conf_int.iloc[:, 1], color='green', alpha=0.3, label='Confidence Interval')
plt.title(f'SARIMA Forecast for {country_name}')
plt.xlabel('Year')
plt.ylabel('Population')
plt.legend()
plt.show()

df_with_all_predictions

Afghanistan
Africa (UN)
Albania
Algeria
American Samoa
Andorra
Angola
Anguilla
Antigua and Barbuda
Argentina
Armenia
Skipping country Armenia due to error: LU decomposition error.
Aruba
Asia (UN)
Australia
Austria
Azerbaijan
Bahamas
Bahrain
Bangladesh
Barbados
Belarus
Belgium
Skipping country Belgium due to error: LU decomposition error.
Belize
Benin
Bermuda
Bhutan
Bolivia
Bonaire Sint Eustatius and Saba
Bosnia and Herzegovina
Botswana
Brazil
Skipping country Brazil due to error: LU decomposition error.
British Virgin Islands
Brunei
Bulgaria
Burkina Faso
Burundi
Skipping country Burundi due to error: LU decomposition error.
Cambodia
Skipping country Cambodia due to error: LU decomposition error.
Cameroon
Canada
Cape Verde
Cayman Islands
Central African Republic
Chad
Chile
China
Colombia
Skipping country Colombia due to error: LU decomposition error.
Comoros
Congo
Cook Islands
Costa Rica
Cote d'Ivoire
Croatia
Cuba
Curacao
Cyprus
Czechia
Democratic Republic of Congo
Denmark
Djibouti
Dominica
Dominican Republic
East Timor
Skipping country East Timor due to error: LU decomposition error.
Ecuador
Egypt
El Salvador
Equatorial Guinea
Eritrea
Estonia
Eswatini
Ethiopia
Europe (UN)
Falkland Islands
Faroe Islands
Fiji
Finland
France
French Guiana
French Polynesia
Gabon
Gambia
Skipping country Gambia due to error: LU decomposition error.
Georgia
Germany
Ghana
Gibraltar
Greece
Greenland
Grenada
Guadeloupe
Guam
Guatemala
Guernsey
Guinea
Guinea-Bissau
Skipping country Guinea-Bissau due to error: LU decomposition error.
Guyana
Haiti
High-income countries
Honduras
Skipping country Honduras due to error: LU decomposition error.
Hong Kong
Hungary
Iceland
India
Indonesia
Iran
Skipping country Iran due to error: LU decomposition error.
Iraq
Ireland
Isle of Man
Israel
Italy
Skipping country Italy due to error: LU decomposition error.
Jamaica
Japan
Jersey
Skipping country Jersey due to error: LU decomposition error.
Jordan
Kazakhstan
Kenya
Kiribati
Kosovo
Kuwait
Kyrgyzstan
Land-locked developing countries (LLDC)
Laos
Latin America and the Caribbean (UN)
Skipping country Latin America and the Caribbean (UN) due to error: LU decomposition error.
Latvia
Least developed countries
Lebanon
Lesotho
Less developed regions
Less developed regions, excluding China
Less developed regions, excluding least developed countries
Liberia
Libya
Liechtenstein
Lithuania
Skipping country Lithuania due to error: LU decomposition error.
Low-income countries
Lower-middle-income countries
Luxembourg
Macao
Madagascar
Malawi
Malaysia
Maldives
Skipping country Maldives due to error: LU decomposition error.
Mali
Malta
Marshall Islands
Martinique
Mauritania
Mauritius
Mayotte
Mexico
Micronesia (country)
Moldova
Monaco
Mongolia
Montenegro
Montserrat
More developed regions
Morocco
Skipping country Morocco due to error: LU decomposition error.
Mozambique
Myanmar
Namibia
Nauru
Nepal
Netherlands
New Caledonia
New Zealand
Nicaragua
Niger
Skipping country Niger due to error: LU decomposition error.
Nigeria
Niue
North Korea
North Macedonia
Northern America (UN)
Northern Mariana Islands
Norway
Skipping country Norway due to error: LU decomposition error.
Oceania (UN)
Oman
Pakistan
Palau
Palestine
Panama
Papua New Guinea
Paraguay
Peru
Philippines
Poland
Portugal
Puerto Rico
Qatar
Reunion
Romania
Russia
Rwanda
Saint Barthelemy
Saint Helena
Saint Kitts and Nevis
Saint Lucia
Saint Martin (French part)
Saint Pierre and Miquelon
Saint Vincent and the Grenadines
Samoa
Skipping country Samoa due to error: LU decomposition error.
San Marino
Sao Tome and Principe
Saudi Arabia
Skipping country Saudi Arabia due to error: LU decomposition error.
Senegal
Serbia
Seychelles
Sierra Leone
Singapore
Sint Maarten (Dutch part)
Slovakia
Slovenia
Small island developing states (SIDS)
Solomon Islands
Somalia
South Africa
South Korea
South Sudan
Spain
Sri Lanka
Sudan
Suriname
Sweden
Switzerland
Syria
Taiwan
Tajikistan
Tanzania
Thailand
Togo
Tokelau
Tonga
Trinidad and Tobago
Tunisia
Turkey
Turkmenistan
Turks and Caicos Islands
Tuvalu
Uganda
Ukraine
Skipping country Ukraine due to error: LU decomposition error.
United Arab Emirates
United Kingdom
United States
United States Virgin Islands
Upper-middle-income countries
Uruguay
Uzbekistan
Vanuatu
Venezuela
Vietnam
Wallis and Futuna
Western Sahara
World
Yemen
Zambia
Zimbabwe
Out[50]:
Country name Year Population Lower CI Upper CI
0 Afghanistan 1999-01-01 1.926285e+07 NaN NaN
1 Afghanistan 2000-01-01 1.954299e+07 NaN NaN
2 Afghanistan 2001-01-01 1.968863e+07 NaN NaN
3 Afghanistan 2002-01-01 2.100026e+07 NaN NaN
4 Afghanistan 2003-01-01 2.264514e+07 NaN NaN
... ... ... ... ... ...
8157 Zimbabwe 2026-12-31 1.715302e+07 1.707486e+07 1.723119e+07
8158 Zimbabwe 2027-12-31 1.734672e+07 1.726181e+07 1.743163e+07
8159 Zimbabwe 2028-12-31 1.754344e+07 1.745215e+07 1.763473e+07
8160 Zimbabwe 2029-12-31 1.773711e+07 1.763974e+07 1.783448e+07
8161 Zimbabwe 2030-12-31 1.793376e+07 1.783056e+07 1.803695e+07

8162 rows × 5 columns

conf_int représente l'intervalle de confiance des prévisions

In [51]:
conf_int
Out[51]:
lower Population upper Population
2021-12-31 1.615634e+07 1.621832e+07
2022-12-31 1.632806e+07 1.641622e+07
2023-12-31 1.651158e+07 1.662021e+07
2024-12-31 1.669954e+07 1.682572e+07
2025-12-31 1.688538e+07 1.702728e+07
2026-12-31 1.707486e+07 1.723119e+07
2027-12-31 1.726181e+07 1.743163e+07
2028-12-31 1.745215e+07 1.763473e+07
2029-12-31 1.763974e+07 1.783448e+07
2030-12-31 1.783056e+07 1.803695e+07

Voici les données pour la France, de 1999 jusqu'aux prévisions, en 2030

In [52]:
df_with_all_predictions[df_with_all_predictions['Country name'] == 'France']
Out[52]:
Country name Year Population Lower CI Upper CI
1725 France 1999-01-01 5.835221e+07 NaN NaN
1726 France 2000-01-01 5.866546e+07 NaN NaN
1727 France 2001-01-01 5.901478e+07 NaN NaN
1728 France 2002-01-01 5.937278e+07 NaN NaN
1729 France 2003-01-01 5.972826e+07 NaN NaN
1730 France 2004-01-01 6.010844e+07 NaN NaN
1731 France 2005-01-01 6.051008e+07 NaN NaN
1732 France 2006-01-01 6.091915e+07 NaN NaN
1733 France 2007-01-01 6.132938e+07 NaN NaN
1734 France 2008-01-01 6.172100e+07 NaN NaN
1735 France 2009-01-01 6.209330e+07 NaN NaN
1736 France 2010-01-01 6.244457e+07 NaN NaN
1737 France 2011-01-01 6.277527e+07 NaN NaN
1738 France 2012-01-01 6.307141e+07 NaN NaN
1739 France 2013-01-01 6.333518e+07 NaN NaN
1740 France 2014-01-01 6.358850e+07 NaN NaN
1741 France 2015-01-01 6.380977e+07 NaN NaN
1742 France 2016-01-01 6.398932e+07 NaN NaN
1743 France 2017-01-01 6.414409e+07 NaN NaN
1744 France 2018-01-01 6.427781e+07 NaN NaN
1745 France 2019-01-01 6.439976e+07 NaN NaN
1746 France 2020-01-01 6.448005e+07 NaN NaN
1747 France 2021-01-01 6.453145e+07 NaN NaN
6522 France 2021-12-31 6.464665e+07 6.462805e+07 6.466524e+07
6523 France 2022-12-31 6.472089e+07 6.469454e+07 6.474724e+07
6524 France 2023-12-31 6.481895e+07 6.478659e+07 6.485131e+07
6525 France 2024-12-31 6.490951e+07 6.487203e+07 6.494698e+07
6526 France 2025-12-31 6.499320e+07 6.495116e+07 6.503523e+07
6527 France 2026-12-31 6.507054e+07 6.502434e+07 6.511674e+07
6528 France 2027-12-31 6.514200e+07 6.509194e+07 6.519207e+07
6529 France 2028-12-31 6.520805e+07 6.515435e+07 6.526175e+07
6530 France 2029-12-31 6.526910e+07 6.521196e+07 6.532623e+07
6531 France 2030-12-31 6.532553e+07 6.526512e+07 6.538595e+07

Graphique de prévisions pour un pays donné¶

In [53]:
country_name = 'Reunion'

country_data = df_with_all_predictions[df_with_all_predictions['Country name'] == country_name]

plt.figure(figsize=(10, 6))
plt.plot(country_data['Year'], country_data['Population'], label='Actual')
plt.plot(country_data.Year[country_data.Year.dt.year > 2021], country_data.Population[country_data.Year.dt.year > 2021], label='Predicted', color='red')

plt.fill_between(country_data.Year, country_data['Lower CI'], country_data['Upper CI'], color='green', alpha=0.3, label='Confidence Interval')

plt.title(f'SARIMA Forecast for {country_name}')
plt.xlabel('Year')
plt.ylabel('Population')
plt.legend()

plt.show()

Export des prévisions¶

In [54]:
df_with_all_predictions.to_csv('previsions/previsions_population_1999_2021.csv', index=False)