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You can install the latest release version from CRAN with
install.packages("wbstats")or
The latest development version from github with
remotes::install_github("pachadotdev/wbstats")library(wbstats)
# Population for every country from 1960 until present
d <- wb_data("SP.POP.TOTL")
head(d)
#> # A tibble: 6 × 9
#> iso2c iso3c country date SP.POP.TOTL unit obs_status footnote last_updated
#> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <date>
#> 1 AF AFG Afghanis… 2024 42647492 <NA> <NA> <NA> 2025-07-01
#> 2 AF AFG Afghanis… 2023 41454761 <NA> <NA> <NA> 2025-07-01
#> 3 AF AFG Afghanis… 2022 40578842 <NA> <NA> <NA> 2025-07-01
#> 4 AF AFG Afghanis… 2021 40000412 <NA> <NA> <NA> 2025-07-01
#> 5 AF AFG Afghanis… 2020 39068979 <NA> <NA> <NA> 2025-07-01
#> 6 AF AFG Afghanis… 2019 37856121 <NA> <NA> <NA> 2025-07-01The current World Bank API does not provide summaries of data
availability. I added the wb_country_coverage() function to
supply that, which reads pre-computed summaries from GitHub.
d <- wb_country_coverage("gross domestic product", c("Mexico", "Chile"), 2010, 2020)
d
# iso2c iso3c country pct_complete from to nobs indicator
# <char> <char> <char> <num> <int> <int> <int> <char>
# 1: CL CHL Chile 56.5 1960 2100 52 CC.EG.INTS.KW
# 2: MX MEX Mexico 56.5 1960 2100 52 CC.EG.INTS.KW
# 3: CL CHL Chile 34.8 1960 2025 23 EG.EGY.PRIM.PP.KD
# 4: MX MEX Mexico 34.8 1960 2025 23 EG.EGY.PRIM.PP.KD
# 5: CL CHL Chile 53.0 1960 2025 35 EG.GDP.PUSE.KO.PP
# ---
# 82: MX MEX Mexico 54.5 1960 2025 36 PA.NUS.PRVT.PP
# 83: CL CHL Chile 53.0 1960 2025 35 SL.GDP.PCAP.EM.KD
# 84: MX MEX Mexico 53.0 1960 2025 35 SL.GDP.PCAP.EM.KD
# 85: CL CHL Chile 100.0 2004 2023 20 SPI.D5.2.5.HOUS
# 86: MX MEX Mexico 40.0 2004 2023 8 SPI.D5.2.5.HOUS
# countries with less than 15% coverage for any variable
d[pct_complete < 15, ]
# iso2c iso3c country pct_complete from to nobs indicator
# <char> <char> <char> <num> <int> <int> <int> <char>
# 1: MX MEX Mexico 12.9 1960 2100 13 UIS.XUNIT.GDPCAP.02.FSGOVwbstatslibrary(wbstats)
library(data.table)
library(tinyplot)
my_indicators <- c(
life_exp = "SP.DYN.LE00.IN",
gdp_capita ="NY.GDP.PCAP.CD",
pop = "SP.POP.TOTL"
)
d <- wb_data(my_indicators, start_date = 2016)
d <- merge(d, wb_countries(), "iso3c")
d <- na.omit(d)
png(file="man/figures/readme-gdppc-vs-lifexp.png", width = 900, height = 600)
tinyplot(
life_exp ~ gdp_capita | region,
data = d,
cex = d$pop,
pch = 19,
alpha = 0.7,
palette = "tableau",
log = "x",
xaxl = "$",
main = "An Example of Hans Rosling's Gapminder using wbstats",
xlab = "GDP per Capita (log scale)",
ylab = "Life Expectancy at Birth",
cap = "Source: World Bank"
)
dev.off()
What worked for me to query the data was to use the
format and per_page arguments. You do
not need this to work with the package.
Endpoints used for the package data:
Parts of this API endpoints description comes from
https://dlthub.com/context/source/world-bank-indicators-api and other
were just testing things like “language” and “languages” tp update
wbstats. I did not create this package, I just assumed its
maintenance as it is a very valuable resoure.
| Resource | Endpoint | Method | Description |
|---|---|---|---|
| indicators | /v2/indicator | GET | Access to nearly 28,000 series indicators |
| countries | /v2/country/all | GET | All countries |
| country_indicator | /v2/country/{country_id}/indicator/{indicator_id} | GET | Specific indicator for a country |
| sources | /v2/source | GET | All data sources |
| source_indicators | /v2/source/{source_id}/indicators | GET | Indicators for a specific source |
| topics | /v2/topics | GET | Metadata about indicator topics |
| regions | /v2/country/all | GET | All regions |
| income_levels | /v2/country/income_levels | GET | All income levels |
| lending_types | /v2/country/lending_types | GET | All lending types |
| languages | /v2/country/languages | GET | All languages |
I added this sub-section because I did not find much information in the official documentation.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.