Client for World Banks's 'Indicators' and 'Poverty and Inequality Platform (PIP)' APIs.

worldbank

Overview

worlbank provides a simple interface to the following World Bank APIs:

• Indicators API v2
• Poverty and Inequality Platform (PIP) API.
• Finances One API

The main difference to other packages is that it’s a modern implementation using the httr2 package and supports all available endpoints and parameters.

The worldbank package provides a set of functions to interact with various endpoints of the World Bank Indicators API. Each function is designed to retrieve specific types of data, making it easier to access and analyze World Bank datasets. Below is an overview of the available endpoints and their corresponding functions in the package:

• Languages (wb_language): Retrieves a list of all languages supported by the World Bank API. Useful for obtaining language-specific data.
• Lending Types (wb_lending_type): Fetches information about different lending types as recognized by the World Bank.
• Income Levels (wb_income_level): Allows users to access data about various income levels defined by the World Bank.
• Sources (wb_source): Provides details about the different data sources available within the World Bank’s datasets.
• Topics (wb_topic): Lists all topics covered by the World Bank API, helping users to narrow down their data search to specific areas of interest.
• Regions (wb_region): Offers information on different geographical regions as categorized by the World Bank.
• Countries (wb_country): Enables access to detailed data about individual countries, including socio-economic and developmental indicators.
• Country Indicators (wb_country_indicator): Specific to retrieving indicators for a particular country or countries, allowing for more targeted data analysis.
• Indicators (wb_indicator): This endpoint gives users access to a wide array of indicators used by the World Bank in its data analysis and reports.

Installation

You can install the released version of worldbank from CRAN with:

install.packages("worldbank")

And the development version from GitHub with:

# install.packages("pak")
pak::pak("m-muecke/worldbank")

Usage

worldbank functions are prefixed with wb_ and follow the naming convention of the World Bank API v2.

library(worldbank)

# filter by specific country
wb_country(c("US", "DE"))
#>   country_id country_code  country_name region_id region_code
#> 1        DEU           DE       Germany       ECS          Z7
#> 2        USA           US United States       NAC          XU
#>            region_value admin_region_id admin_region_code admin_region_value
#> 1 Europe & Central Asia            <NA>              <NA>               <NA>
#> 2         North America            <NA>              <NA>               <NA>
#>   income_level_id income_level_code income_level_value lending_type_id
#> 1             HIC                XD        High income             LNX
#> 2             HIC                XD        High income             LNX
#>   lending_type_code lending_type_value    capital_city longitude latitude
#> 1                XX     Not classified          Berlin   13.4115  52.5235
#> 2                XX     Not classified Washington D.C.  -77.0320  38.8895

# or fetch all (default)
country <- wb_country()
str(country)
#> 'data.frame':    296 obs. of  18 variables:
#>  $ country_id        : chr  "ABW" "AFE" "AFG" "AFR" ...
#>  $ country_code      : chr  "AW" "ZH" "AF" "A9" ...
#>  $ country_name      : chr  "Aruba" "Africa Eastern and Southern" "Afghanista"..
#>  $ region_id         : chr  "LCN" "NA" "SAS" "NA" ...
#>  $ region_code       : chr  "ZJ" "NA" "8S" "NA" ...
#>  $ region_value      : chr  "Latin America & Caribbean" "Aggregates" "South A"..
#>  $ admin_region_id   : chr  NA NA "SAS" NA ...
#>  $ admin_region_code : chr  NA NA "8S" NA ...
#>  $ admin_region_value: chr  NA NA "South Asia" NA ...
#>  $ income_level_id   : chr  "HIC" "NA" "LIC" "NA" ...
#>  $ income_level_code : chr  "XD" "NA" "XM" "NA" ...
#>  $ income_level_value: chr  "High income" "Aggregates" "Low income" "Aggregat"..
#>  $ lending_type_id   : chr  "LNX" NA "IDX" NA ...
#>  $ lending_type_code : chr  "XX" NA "XI" NA ...
#>  $ lending_type_value: chr  "Not classified" "Aggregates" "IDA" "Aggregates" ...
#>  $ capital_city      : chr  "Oranjestad" NA "Kabul" NA ...
#>  $ longitude         : num  -70 NA 69.2 NA NA ...
#>  $ latitude          : num  12.5 NA 34.5 NA NA ...


# search for specific indicator
ind <- wb_indicator()
ind <- subset(
  ind,
  grepl("GDP", id, fixed = TRUE) & source_value == "World Development Indicators"
)
str(ind)
#> 'data.frame':    37 obs. of  9 variables:
#>  $ id                 : chr  "EG.GDP.PUSE.KO.PP" "EG.GDP.PUSE.KO.PP.KD" "EN.G"..
#>  $ name               : chr  "GDP per unit of energy use (PPP $ per kg of oil"..
#>  $ unit               : chr  NA NA NA NA ...
#>  $ source_id          : chr  "2" "2" "2" "2" ...
#>  $ source_value       : chr  "World Development Indicators" "World Developmen"..
#>  $ source_note        : chr  "GDP per unit of energy use is the PPP GDP per k"..
#>  $ source_organization: chr  "IEA Statistics © OECD/IEA 2014 (https://www.iea"..
#>  $ topic_id           : chr  "5" "5" "6" "6" ...
#>  $ topic_value        : chr  "Energy & Mining" "Energy & Mining" "Environment"..

# fetch indicator data for specific or all countries (default)
gdp <- wb_country_indicator("NY.GDP.MKTP.CD", c("US", "DE", "FR", "CH", "JP"))
str(gdp)
#> 'data.frame':    320 obs. of  10 variables:
#>  $ date          : int  2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 ...
#>  $ indicator_id  : chr  "NY.GDP.MKTP.CD" "NY.GDP.MKTP.CD" "NY.GDP.MKTP.CD" "N"..
#>  $ indicator_name: chr  "GDP (current US$)" "GDP (current US$)" "GDP (current"..
#>  $ country_id    : chr  "CH" "CH" "CH" "CH" ...
#>  $ country_name  : chr  "Switzerland" "Switzerland" "Switzerland" "Switzerlan"..
#>  $ country_code  : chr  "CHE" "CHE" "CHE" "CHE" ...
#>  $ value         : num  8.85e+11 8.18e+11 8.13e+11 7.42e+11 7.21e+11 ...
#>  $ unit          : chr  NA NA NA NA ...
#>  $ obs_status    : chr  NA NA NA NA ...
#>  $ decimal       : int  0 0 0 0 0 0 0 0 0 0 ...

Related work

• wbstats: R package for searching and downloading data from the World Bank API
• WDI: R package to download World Bank data
• pipr: R client for the PIP Worldbank API.