The goal of worldbank is to provide a simple interface to the World Bank API v2. The main difference to other packages is that it’s a modern implementation using the httr2 package without any other dependencies.
The worldbank package provides a set of functions to
interact with various endpoints of the World Bank 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:
wb_language): Retrieves a
list of all languages supported by the World Bank API. Useful for
obtaining language-specific data.wb_lending_type):
Fetches information about different lending types as recognized by the
World Bank.wb_income_level):
Allows users to access data about various income levels defined by the
World Bank.wb_source): Provides details
about the different data sources available within the World Bank’s
datasets.wb_topic): Lists all topics
covered by the World Bank API, helping users to narrow down their data
search to specific areas of interest.wb_region): Offers
information on different geographical regions as categorized by the
World Bank.wb_country): Enables access
to detailed data about individual countries, including socio-economic
and developmental indicators.wb_country_indicator): Specific to retrieving indicators
for a particular country or countries, allowing for more targeted data
analysis.wb_indicator): This
endpoint gives users access to a wide array of indicators used by the
World Bank in its data analysis and reports.You can install the development version of worldbank from GitHub with:
# install.packages("pak")
pak::pak("m-muecke/worldbank")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"))
#> # A tibble: 2 × 18
#> country_id country_code country_name region_id region_code region_value
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 DEU DE Germany ECS Z7 Europe & Central …
#> 2 USA US United States NAC XU North America
#> # ℹ 12 more variables: admin_region_id <chr>, admin_region_code <chr>,
#> # admin_region_value <chr>, income_level_id <chr>, income_level_code <chr>,
#> # income_level_value <chr>, lending_type_id <chr>, lending_type_code <chr>,
#> # lending_type_value <chr>, capital_city <chr>, longitude <dbl>,
#> # latitude <dbl>
# or fetch all (default)
wb_country()
#> # A tibble: 296 × 18
#> country_id country_code country_name region_id region_code region_value
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 ABW AW Aruba LCN ZJ Latin Ameri…
#> 2 AFE ZH Africa Eastern and… NA NA Aggregates
#> 3 AFG AF Afghanistan SAS 8S South Asia
#> 4 AFR A9 Africa NA NA Aggregates
#> 5 AFW ZI Africa Western and… NA NA Aggregates
#> # ℹ 291 more rows
#> # ℹ 12 more variables: admin_region_id <chr>, admin_region_code <chr>,
#> # admin_region_value <chr>, income_level_id <chr>, income_level_code <chr>,
#> # income_level_value <chr>, lending_type_id <chr>, lending_type_code <chr>,
#> # lending_type_value <chr>, capital_city <chr>, longitude <dbl>,
#> # latitude <dbl>
# search for specific indicator
ind <- wb_indicator()
ind <- subset(
ind, grepl("GDP", id, fixed = TRUE) & source_value == "World Development Indicators"
)
ind
#> # A tibble: 35 × 9
#> id name unit source_id source_value source_note source_organization
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 EG.GDP.PUS… GDP … <NA> 2 World Devel… GDP per un… IEA Statistics © O…
#> 2 EG.GDP.PUS… GDP … <NA> 2 World Devel… GDP per un… IEA Statistics © O…
#> 3 ER.GDP.FWT… Wate… <NA> 2 World Devel… Water prod… Food and Agricultu…
#> 4 NY.GDP.COA… Coal… <NA> 2 World Devel… Coal rents… World Bank staff e…
#> 5 NY.GDP.DEF… Infl… <NA> 2 World Devel… Inflation … World Bank nationa…
#> # ℹ 30 more rows
#> # ℹ 2 more variables: topic_id <chr>, topic_value <chr>
# fetch indicator data for specific or all countries (default)
gdp <- wb_country_indicator("NY.GDP.MKTP.CD", c("US", "DE", "FR", "CH", "JP"))
gdp
#> # A tibble: 295 × 10
#> date indicator_id indicator_name country_id country_name country_code value
#> <int> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 2022 NY.GDP.MKTP… GDP (current … CH Switzerland CHE 8.18e11
#> 2 2021 NY.GDP.MKTP… GDP (current … CH Switzerland CHE 8.13e11
#> 3 2020 NY.GDP.MKTP… GDP (current … CH Switzerland CHE 7.42e11
#> 4 2019 NY.GDP.MKTP… GDP (current … CH Switzerland CHE 7.21e11
#> 5 2018 NY.GDP.MKTP… GDP (current … CH Switzerland CHE 7.26e11
#> # ℹ 290 more rows
#> # ℹ 3 more variables: unit <chr>, obs_status <chr>, decimal <int>