wbwdi 1.0.1

Seamless Access to World Bank World Development Indicators with Polars

py-wbwdi

wbwdi is a Polars-based Python library to access and analyze the World Bank’s World Development Indicators (WDI) using the corresponding API. WDI provides more than 24,000 country or region-level indicators for various contexts. wbwdi enables users to download, process and work with WDI series across multiple entities and time periods.

This library is a product of Christoph Scheuch and not sponsored by or affiliated with the World Bank in any way. For an R implementation, please consider the r-wbwdi package. For packages with a shared design philosophy, check out the econdataverse.

Installation

You can install the release version from PyPI:

pip install wbwdi

If you want to use the package with pandas, then install with the corresponding dependencies:

pip install wbwdi[pandas]

You also need to set the configuration to pandas (see below).

You can install the development version from GitHub:

pip install "git+https://github.com/tidy-intelligence/py-wbwdi"

Usage

The main function wdi_get() provides an interface to download multiple WDI series for multiple entities and specific date ranges.

import wbwdi as wb

wb.wdi_get(
  entities=["MEX", "CAN", "USA"], 
  indicators=["NY.GDP.PCAP.KD", "SP.POP.TOTL"],
  start_year=2020, 
  end_year=2024
)

You can also download these indicators for all entities and available dates:

wb.wdi_get(
  entities="all", 
  indicators=["NY.GDP.PCAP.KD", "SP.POP.TOTL"]
)

Some indicators are also available on a monthly basis, e.g.:

wb.wdi_get(
  entities="AUT", 
  indicators="DPANUSSPB",         
  start_year=2012, 
  end_year=2015, 
  frequency="month"
)

Similarly, there are also some indicators available on a quarterly frequency, e.g.:

wb.wdi_get(
  entities="NGA", 
  indicators= "DT.DOD.DECT.CD.TL.US",
  start_year=2012, 
  end_year=2015, 
  frequency="quarter"
)

You can get a list of all indicators supported by the WDI API via:

wb.wdi_get_indicators()

You can get a list of all supported entities via:

wb.wdi_get_entities()

You can also get the list of supported indicators and entities in another language, but note that not everything seems to be translated into other languages:

wb.wdi_get_indicators(language="es")
wb.wdi_get_entities(language="zh")

Check out the following function for a list of supported languages:

wb.wdi_get_languages()

In addition, you can list supported regions, sources, topics and lending types, respectively:

wb.wdi_get_regions()
wb.wdi_get_sources()
wb.wdi_get_topics()
wb.wdi_get_lending_types()

If you want to search for specific keywords among indicators or other data sources, you can use the Positron data explorer. Alternatively, this package comes with a helper function:

indicators=wb.wdi_get_indicators()

wb.wdi_search(
  indicators,
  keywords=["inequality", "gender"],
  columns=["indicator_name"]
)

If you want to data as a pandas or arrow data frame instead of polars, you can change the corresponding configuration:

wb.wdi_set_format("pandas")  

wb.wdi_get(
  entities=["MEX", "CAN", "USA"], 
  indicators=["NY.GDP.PCAP.KD", "SP.POP.TOTL"],
  start_year=2020, 
  end_year=2024
)

Relation to Existing Python Libraries

There are already great libraries that allow you to interact with the World Bank WDI API. The two main reasons why this library exists are: (i) to have an implementation based on Polars rather than pandas, and (ii) to have an interface consistent with the econdataverse.

• world-bank-data
• wbpy
• wbdata
• pandas_datareader