wbdata

import wbdata import datetime # Define the date range from 2000 to 2010 data_date = datetime.datetime(2000, 1, 1), datetime.datetime(2010, 1, 1) # Define countries using their ISO2 codes countries = ["FR", "DE", "IT"] # Define indicators with human-readable aliases indicators = {"NY.GDP.PCAP.CD": "GDP per Capita", "SP.POP.TOTL": "Total Population"} # Get data as a Pandas DataFrame df = wbdata.get_dataframe(indicators, country=countries, data_date=data_date) print("\n--- Sample Data (GDP per Capita, Total Population) ---") print(df.head()) # Get information about a specific indicator print("\n--- Indicator Info for GDP per Capita ---") indicators_info = wbdata.get_indicator("NY.GDP.PCAP.CD") for key, value in indicators_info.items(): print(f"{key}: {value}") # Search for indicators containing 'population' print("\n--- Search Results for 'population' ---") population_indicators = wbdata.search_indicator("population") # In an interactive shell or notebook, printing the list directly would show a table print(f"Found {len(population_indicators)} indicators matching 'population'. Showing first 3:\n{population_indicators[:3]}")