MyNixOS website logo
Description

Client for the 'World Bank' APIs.

Download and search data from the 'World Bank' APIs, including the 'Indicators' API, the 'Poverty and Inequality Platform (PIP)' API, the 'Finances One' API, and the 'Projects' API. See <https://datahelpdesk.worldbank.org/knowledgebase/articles/889386-developer-information-overview> for further details.

worldbank

R-CMD-check CRANstatus R-universeversion

Overview

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

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

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" "MEA" "NA" ...
#>  $ region_code       : chr  "ZJ" "NA" "ZQ" "NA" ...
#>  $ region_value      : chr  "Latin America & Caribbean" "Aggregates" "Middle "..
#>  $ admin_region_id   : chr  NA NA "MNA" NA ...
#>  $ admin_region_code : chr  NA NA "XQ" NA ...
#>  $ admin_region_value: chr  NA NA "Middle East, North Africa, Afghanistan & P"..
#>  $ 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          : int  2 2 2 2 2 2 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 Energy Statistics Data Browser, Internation"..
#>  $ topic_id           : int  5 5 6 6 6 6 3 7 3 7 ...
#>  $ topic_value        : chr  "Energy & Mining" "Energy & Mining" "Environment"..

# fetch indicator data for specific or all countries (default)
gdp <- wb_data("NY.GDP.MKTP.CD", c("US", "DE", "FR", "CH", "JP"))
str(gdp)
#> 'data.frame':    325 obs. of  10 variables:
#>  $ date          : int  2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 ...
#>  $ 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  9.37e+11 8.94e+11 8.29e+11 8.15e+11 7.42e+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 ...

# plot the indicator data
library(ggplot2)

subset(gdp, date >= 1980) |>
  ggplot(aes(x = date, y = value, color = country_name)) +
  geom_line() +
  theme_minimal() +
  theme(
    legend.title = element_blank(),
    legend.position = "bottom",
    plot.title = element_text(face = "bold"),
    panel.grid.major.y = element_line(color = "black", linewidth = 0.2),
    panel.grid.major.x = element_blank(),
    panel.grid.minor = element_blank(),
    axis.text = element_text(color = "black"),
    axis.title = element_blank()
  ) +
  scale_y_continuous(
    labels = scales::label_currency(scale_cut = scales::cut_short_scale())
  ) +
  labs(title = "GDP in Current U.S. Dollars", color = "Country")

Related work

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

Version

0.8.0

License

Unknown

Platforms (78)

    Darwin
    FreeBSD
    Genode
    GHCJS
    Linux
    MMIXware
    NetBSD
    none
    OpenBSD
    Redox
    Solaris
    uefi
    WASI
    Windows
Show all
  • aarch64-darwin
  • aarch64-freebsd
  • aarch64-genode
  • aarch64-linux
  • aarch64-netbsd
  • aarch64-none
  • aarch64-uefi
  • aarch64-windows
  • aarch64_be-none
  • arm-none
  • armv5tel-linux
  • armv6l-linux
  • armv6l-netbsd
  • armv6l-none
  • armv7a-linux
  • armv7a-netbsd
  • armv7l-linux
  • armv7l-netbsd
  • avr-none
  • i686-cygwin
  • i686-freebsd
  • i686-genode
  • i686-linux
  • i686-netbsd
  • i686-none
  • i686-openbsd
  • i686-windows
  • javascript-ghcjs
  • loongarch64-linux
  • m68k-linux
  • m68k-netbsd
  • m68k-none
  • microblaze-linux
  • microblaze-none
  • microblazeel-linux
  • microblazeel-none
  • mips-linux
  • mips-none
  • mips64-linux
  • mips64-none
  • mips64el-linux
  • mipsel-linux
  • mipsel-netbsd
  • mmix-mmixware
  • msp430-none
  • or1k-none
  • powerpc-linux
  • powerpc-netbsd
  • powerpc-none
  • powerpc64-linux
  • powerpc64le-linux
  • powerpcle-none
  • riscv32-linux
  • riscv32-netbsd
  • riscv32-none
  • riscv64-linux
  • riscv64-netbsd
  • riscv64-none
  • rx-none
  • s390-linux
  • s390-none
  • s390x-linux
  • s390x-none
  • vc4-none
  • wasm32-wasi
  • wasm64-wasi
  • x86_64-cygwin
  • x86_64-darwin
  • x86_64-freebsd
  • x86_64-genode
  • x86_64-linux
  • x86_64-netbsd
  • x86_64-none
  • x86_64-openbsd
  • x86_64-redox
  • x86_64-solaris
  • x86_64-uefi
  • x86_64-windows