Using `wbwdi` to access World Development Indicators
Source:vignettes/using-wbwdi.Rmd
using-wbwdi.RmdThe wbwdi package provides a modern and flexible
interface for accessing the World Bank’s World
Development Indicators (WDI). With wbwdi, you can
download data for multiple indicators and geographies in a single
function call, benefit from progress bars, and receive the output in a
tidy data format, making it ideal for further analysis with other data
sources.
Listing Supported Indicators
The wbwdi package allows you to retrieve a full list of
all supported indicators from the World Bank Indicators
API. Each indicator is accompanied by metadata such as its unit of
measurement, source, and associated topics.
wdi_get_indicators()
#> # A tibble: 24,602 × 7
#> indicator_id indicator_name source_id source_name source_note
#> <chr> <chr> <int> <chr> <chr>
#> 1 1.0.HCount.1.90usd Poverty Headcount ($1… 37 LAC Equity… "The pover…
#> 2 1.0.HCount.2.5usd Poverty Headcount ($2… 37 LAC Equity… "The pover…
#> 3 1.0.HCount.Mid10to50 Middle Class ($10-50 … 37 LAC Equity… "The pover…
#> 4 1.0.HCount.Ofcl Official Moderate Pov… 37 LAC Equity… "The pover…
#> 5 1.0.HCount.Poor4uds Poverty Headcount ($4… 37 LAC Equity… "The pover…
#> 6 1.0.HCount.Vul4to10 Vulnerable ($4-10 a d… 37 LAC Equity… "The pover…
#> 7 1.0.PGap.1.90usd Poverty Gap ($1.90 a … 37 LAC Equity… "The pover…
#> 8 1.0.PGap.2.5usd Poverty Gap ($2.50 a … 37 LAC Equity… "The pover…
#> 9 1.0.PGap.Poor4uds Poverty Gap ($4 a day) 37 LAC Equity… "The pover…
#> 10 1.0.PSev.1.90usd Poverty Severity ($1.… 37 LAC Equity… "The pover…
#> # ℹ 24,592 more rows
#> # ℹ 2 more variables: source_organization <chr>, topics <list>You can also get the list of supported indicators in a different language. For example, to retrieve the indicators in Spanish:
wdi_get_indicators(language = "es")
#> # A tibble: 24,602 × 7
#> indicator_id indicator_name source_id source_name source_note
#> <chr> <chr> <int> <chr> <chr>
#> 1 1.0.HCount.1.90usd "Tasa de Incidencia d… 37 "" "Tasa de I…
#> 2 1.0.HCount.2.5usd "Tasa de Incidencia d… 37 "" "Tasa de I…
#> 3 1.0.HCount.Mid10to50 "Tasa de Incidencia d… 37 "" "Tasa de I…
#> 4 1.0.HCount.Ofcl "Tasa Oficial de la P… 37 "" "Tasa de I…
#> 5 1.0.HCount.Poor4uds "Tasa de Incidencia d… 37 "" "Tasa de I…
#> 6 1.0.HCount.Vul4to10 "Tasa de incidencia d… 37 "" "Tasa de I…
#> 7 1.0.PGap.1.90usd "Brecha de Pobreza ($… 37 "" "La Brecha…
#> 8 1.0.PGap.2.5usd "Brecha de Pobreza ($… 37 "" "La Brecha…
#> 9 1.0.PGap.Poor4uds "Brecha de Pobreza ($… 37 "" "La Brecha…
#> 10 1.0.PSev.1.90usd "Severidad de la Pobr… 37 "" "El índice…
#> # ℹ 24,592 more rows
#> # ℹ 2 more variables: source_organization <chr>, topics <list>To get the list of languages supported by the API, call:
wdi_get_languages()
#> # A tibble: 23 × 3
#> language_code language_name native_form
#> <chr> <chr> <chr>
#> 1 en English English
#> 2 es Spanish Español
#> 3 fr French Français
#> 4 ar Arabic عربي
#> 5 zh Chinese 中文
#> 6 bg Bulgarian Български
#> 7 de German Deutsch
#> 8 hi Hindi हिंदी
#> 9 id Indonesian Bahasa indonesia
#> 10 ja Japanese 日本語
#> # ℹ 13 more rowsNote that not all indicators and their columns might be translated into all languages.
Listing Supported Geographies
You can retrieve a list of all geographies supported by the World Bank API along with metadata such as region, administrative region, income level, and lending type. Note that a geography might be a country or a region, hence the more general table name.
wdi_get_geographies()
#> # A tibble: 296 × 19
#> geography_id geography_iso2code geography_type capital_city geography_name
#> <chr> <chr> <chr> <chr> <chr>
#> 1 ABW AW Country Oranjestad Aruba
#> 2 AFE ZH Region NA Africa Easter…
#> 3 AFG AF Country Kabul Afghanistan
#> 4 AFR A9 Region NA Africa
#> 5 AFW ZI Region NA Africa Wester…
#> 6 AGO AO Country Luanda Angola
#> 7 ALB AL Country Tirane Albania
#> 8 AND AD Country Andorra la Vel… Andorra
#> 9 ARB 1A Region NA Arab World
#> 10 ARE AE Country Abu Dhabi United Arab E…
#> # ℹ 286 more rows
#> # ℹ 14 more variables: region_id <chr>, region_iso2code <chr>,
#> # region_name <chr>, admin_region_id <chr>, admin_region_iso2code <chr>,
#> # admin_region_name <chr>, income_level_id <chr>,
#> # income_level_iso2code <chr>, income_level_name <chr>,
#> # lending_type_id <chr>, lending_type_iso2code <chr>,
#> # lending_type_name <chr>, longitude <dbl>, latitude <dbl>This information can also be requested in other languages. For example, to view the supported geographies in Chinese:
wdi_get_geographies(language = "zh")
#> # A tibble: 296 × 19
#> geography_id geography_iso2code geography_type capital_city geography_name
#> <chr> <chr> <chr> <chr> <chr>
#> 1 ABW AW Country 奥拉涅斯塔德 阿鲁巴
#> 2 AFE ZH Country NA NA
#> 3 AFG AF Country 喀布尔 阿富汗
#> 4 AFR A9 Country NA NA
#> 5 AFW ZI Country NA NA
#> 6 AGO AO Country 罗安达 安哥拉
#> 7 ALB AL Country 地拉那 阿尔巴尼亚
#> 8 AND AD Country 安道尔城 安道尔共和国
#> 9 ARB 1A Country NA 阿拉伯联盟国家
#> 10 ARE AE Country 阿布扎比 阿拉伯联合酋长国
#> # ℹ 286 more rows
#> # ℹ 14 more variables: region_id <chr>, region_iso2code <chr>,
#> # region_name <chr>, admin_region_id <chr>, admin_region_iso2code <chr>,
#> # admin_region_name <chr>, income_level_id <chr>,
#> # income_level_iso2code <chr>, income_level_name <chr>,
#> # lending_type_id <chr>, lending_type_iso2code <chr>,
#> # lending_type_name <chr>, longitude <dbl>, latitude <dbl>Downloading Indicator Data
With wbwdi, you can download indicator data for multiple
geographies and indicators in a single function call. The function
returns a tidy data frame with country, indicator, date, and value
columns.
For example, to download GDP per capita and total population for Mexico, Canada, and the United States:
wdi_get(
geographies = c("MX", "CA", "US"),
indicators = c("NY.GDP.PCAP.KD", "SP.POP.TOTL")
)
#> # A tibble: 384 × 4
#> geography_id indicator_id year value
#> <chr> <chr> <int> <dbl>
#> 1 CAN NY.GDP.PCAP.KD 1960 15432.
#> 2 MEX NY.GDP.PCAP.KD 1960 4146.
#> 3 USA NY.GDP.PCAP.KD 1960 18992.
#> 4 CAN NY.GDP.PCAP.KD 1961 15606.
#> 5 MEX NY.GDP.PCAP.KD 1961 4219.
#> 6 USA NY.GDP.PCAP.KD 1961 19109.
#> 7 CAN NY.GDP.PCAP.KD 1962 16456.
#> 8 MEX NY.GDP.PCAP.KD 1962 4276.
#> 9 USA NY.GDP.PCAP.KD 1962 19965.
#> 10 CAN NY.GDP.PCAP.KD 1963 17008.
#> # ℹ 374 more rowsIf you need the same indicators for all geographies, you can pass
"all" as the geographies parameter:
wdi_get(
geographies = "all",
indicators = c("NY.GDP.PCAP.KD", "SP.POP.TOTL")
)
#> # A tibble: 34,048 × 4
#> geography_id indicator_id year value
#> <chr> <chr> <int> <dbl>
#> 1 AFE NY.GDP.PCAP.KD 1960 1172.
#> 2 AFW NY.GDP.PCAP.KD 1960 1111.
#> 3 ARB NY.GDP.PCAP.KD 1960 NA
#> 4 CSS NY.GDP.PCAP.KD 1960 4422.
#> 5 CEB NY.GDP.PCAP.KD 1960 NA
#> 6 EAR NY.GDP.PCAP.KD 1960 1062.
#> 7 EAS NY.GDP.PCAP.KD 1960 1144.
#> 8 EAP NY.GDP.PCAP.KD 1960 323.
#> 9 TEA NY.GDP.PCAP.KD 1960 327.
#> 10 EMU NY.GDP.PCAP.KD 1960 9943.
#> # ℹ 34,038 more rowsIf you want to retrieve the indicators in a wide format, you can use the corresponding parameter.
wdi_get(
geographies = "US",
indicators = c("NY.GDP.PCAP.KD", "SP.POP.TOTL"),
format = "wide"
)
#> # A tibble: 64 × 4
#> geography_id year NY.GDP.PCAP.KD SP.POP.TOTL
#> <chr> <int> <dbl> <dbl>
#> 1 USA 1960 18992. 180671000
#> 2 USA 1961 19109. 183691000
#> 3 USA 1962 19965. 186538000
#> 4 USA 1963 20546. 189242000
#> 5 USA 1964 21438. 191889000
#> 6 USA 1965 22526. 194303000
#> 7 USA 1966 23715. 196560000
#> 8 USA 1967 24045. 198712000
#> 9 USA 1968 24948. 200706000
#> 10 USA 1969 25472. 202677000
#> # ℹ 54 more rowsOther Helper Functions
You can fetch a list of all supported regions, sources, topics and lending types, respectively, using the corresponding helper function:
If you want to search for specific keywords among indicators or other data sources, you can use the built-in RStudio data frame viewing functionality or the Positron Data Explorer. Alternatively, this package comes with a helper function:
indicators <- wdi_get_indicators()
wdi_search(
indicators,
keywords = c("inequality", "gender"),
columns = c("indicator_name")
)
#> # A tibble: 466 × 7
#> indicator_id indicator_name source_id source_name source_note
#> <chr> <chr> <int> <chr> <chr>
#> 1 2.3_GIR.GPI "Gender parity index … 34 Global Par… "Ratio of …
#> 2 2.6_PCR.GPI "Gender parity index … 34 Global Par… "Ratio of …
#> 3 BI.EMP.PWRK.PB.FE.ZS "Public sector employ… 64 Worldwide … NA
#> 4 BI.EMP.PWRK.PB.MA.ZS "Public sector employ… 64 Worldwide … NA
#> 5 BI.EMP.TOTL.PB.FE.ZS "Public sector employ… 64 Worldwide … NA
#> 6 BI.EMP.TOTL.PB.MA.ZS "Public sector employ… 64 Worldwide … NA
#> 7 BI.WAG.PREM.PB.FE "Public sector wage p… 64 Worldwide … NA
#> 8 BI.WAG.PREM.PB.FM "P-Value: Public sect… 64 Worldwide … NA
#> 9 BI.WAG.PREM.PB.FM.CA "P-Value: Gender wage… 64 Worldwide … NA
#> 10 BI.WAG.PREM.PB.FM.ED "P-Value: Gender wage… 64 Worldwide … NA
#> # ℹ 456 more rows
#> # ℹ 2 more variables: source_organization <chr>, topics <list>Conclusion
The wbwdi package is designed to simplify the process of
accessing and analyzing World Bank data and combining it with other data
sources. By offering features like multi-indicator downloads, progress
bars, and flexible language support, wbwdi is a robust tool
for users who need access to World Development Indicators in a tidy
format.
If you encounter any errors or have suggestions for improvements, please consider opening an issue in the package repository on GitHub.