Package: worldbankdatatransform
World Bank Data Query ToolMulti .csv FilesTransform World Bank Data IndicatorOne Variable Panel DataMultiVariable Time Series DataMultiVariable Cross Section DataMultiVariable Panel Data(New!)Requirementspython 3.xxpandas 1.4.2How to Installpip install worldbankdatatransformHow to Usefrom worldbankdatatransform import get_filename_dict, WorldBankDataTransformdownload csv files that you want at data.worldbank.org/indicator and
you csv files must stored in a folder with appropriate filename, i.e inflation.csv, constant-gdp.csvyour_path = 'your csv folder path' ## i.e D:/world-bank/data
filename = get_filename_dict(path=your_path)

# Create an object
wb_files = WorldBankDataTransform(filename=filename, path=your_path)One Variable Panel DataTransform world bank csv files intoyearcountry_1country_2...country_nfor example:G4_countries = ['United Kingdom', 'France', 'Germany', 'Italy']
inflation = "inflation" # csv file name of the variable you want, without '.csv'

G4_countries_inflation = wb_files.onevar_panel_data(key_name=inflation, 
                                                    country_list=G4_countries,
                                                    start_year = None,
                                                    end_year = None,
                                                    save_file=False,
                                                    path=None,
                                                    filename_save=None)G4_countries_inflationis a pandas DataFrameMultivariable Time Series DataTransform world bank csv files into specific country's multivariable:yearvariable_1variable_2...variable_ncountry = "Vanuatu"
vanuatu_time_series = wb_files.multivar_time_series(country=country,
                                                    start_year = None,
                                                    end_year = None
                                                    save_file=False,
                                                    path=None,
                                                    filename_save=None)vanuatu_time_seriesis a pandas DataFrameMultivariable Cross Section DataTransform world bank csv files into specific year multivariable of countries:countryvariable_1variable_2...variable_nworld_in_2019 = wb_files.multivar_cross_section(year=2019, 
                                                country_list=None, 
                                                save_file=False,
                                                path=None,
                                                filename_save=None)you can also specify country list included in the DataFrame
i.e
asean_5 = ['Indonesia', 'Malaysia', 'Singapore', 'Thailand', 'Philippines']
and store intocountry_listparameterMultivariable Panel DataTransform world bank csv files into specific year multivariable of countries:countryyearvariable_1variable_2....variable_nall_countries_panel_data = wb_files.multivar_panel_data(country_list=None,
                                                        start_year = None,
                                                        end_year = None,
                                                        save_file=False,
                                                        path=None,
                                                        filename_save=None)How to Save into csv FilesSet thesave_file=True,path='your save file folder path',filename_save='your_data_filename.csv'