worldbankdatatransform 0.0.2

Transform data.worldbank.org/indicator csv files into one variable panel data, multivariable time series data, multivariable cross section data, or multivariable panel data.

World Bank Data Query Tool

• Multi .csv Files
• Transform World Bank Data Indicator
  • One Variable Panel Data
  • MultiVariable Time Series Data
  • MultiVariable Cross Section Data
  • MultiVariable Panel Data (New!)

Requirements

• python 3.xx
• pandas 1.4.2

How to Install

pip install worldbankdatatransform

How to Use

from worldbankdatatransform import get_filename_dict, WorldBankDataTransform

download 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.csv

your_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 Data

Transform world bank csv files into

year	country_1	country_2	...	country_n

for 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_inflation is a pandas DataFrame

Multivariable Time Series Data

Transform world bank csv files into specific country's multivariable:

year	variable_1	variable_2	...	variable_n

country = "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_series is a pandas DataFrame

Multivariable Cross Section Data

Transform world bank csv files into specific year multivariable of countries:

country	variable_1	variable_2	...	variable_n

world_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 into country_list parameter

Multivariable Panel Data

Transform world bank csv files into specific year multivariable of countries:

country	year	variable_1	variable_2	....	variable_n

all_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 Files

Set the save_file=True, path='your save file folder path', filename_save='your_data_filename.csv'