SCL Data - Data Ecosystem Working Group
Important: This package is in Beta - expect changes and updates
Library to access standardized SCLdata indicators on topics such as poverty, inequality, health, labor market, gender and diversity, education and migration for the 26 countries of the region.
This tool was developed to facilitate the consultation of the region's indicators, providing a unified source of data on different topics that can be easily used to generate comparative analyses or studies on the region.This will boost knowledge about the region, facilitating decision making with a reliable and comparable source of information for the countries of Latin America and the Caribbean.
For the moment this package is only available from github.
R (>= 3.3) rlang (1.0.6) purrr(0.3.5)
To install the development version:
install.packages("devtools")
devtools::install_github("EL-BID/idbsocialdataR")
# Optional dependency for some functions
install.packages("sf")With this function you can download any indicator from the SCLdata collections. You can browse this dictionary to see what is available.
idbsocialdataR::search_indicator(search='pobreza')# A tibble: 8 x 6
indicator description_en description_es valuetype label_en label_es
<chr> <chr> <chr> <chr> <chr> <chr>
1 pobreza "Percentage of the population whose income ~ Porcentage de~ pct Poverty~ Pobreza~
2 pobreza_PHC "Percentage of the population with incomes ~ Porcentage de~ pct Poverty~ Pobreza~
3 pobreza31 "\nPercentage of the population with income~ Porcentage de~ pct Extreme~ Pobreza~
4 pobreza31_PHC "\nPercentage of the population with income~ Porcentage de~ pct Extreme~ Pobreza~data <- idbsocialdataR:::query_indicator(indicator='pobreza',
countries='COL,ECU,BRA,URY',
categories='area',
latest=FALSE)# A tibble: 5 x 23
iddate year month idgeo isoalpha3 source indicator area value se cv sample theme_es theme_en
<chr> <dbl> <lgl> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
1 year 2006 NA count… BRA BRA-PN… pobreza rural 62.0 0.206 0.333 64606 ingreso income
2 year 2006 NA count… BRA BRA-PN… pobreza urban 30.9 0.0875 0.283 332088 ingreso income
3 year 2012 NA count… BRA BRA-PN… pobreza rural 46.1 0 0 51214 ingreso income
4 year 2012 NA count… BRA BRA-PN… pobreza urban 17.9 0 0 297772 ingreso income
5 year 2015 NA count… BRA BRA-PN… pobreza rural 43.0 0 0 51544 ingreso income
# … with 9 more variables: source_en <chr>, source_es <chr>, country_name_en <chr>,
# country_name_es <chr>, valuetype <chr>, label_en <chr>, label_es <chr>, description_en <chr>,
# description_es <chr>dictionary <- idbsocialdataR:::query_dictionary() %>% select(collection, indicator, label_es)
# A tibble: 757 x 3
collection indicator label_es
<chr> <chr> <chr>
1 Household Socio-Economic Surve… urbano_ci "Porcentaje dela población que reside en zonas urban…
2 Household Socio-Economic Surve… unip_ch "Porcentaje de hogares unipersonales "
3 Household Socio-Economic Surve… union_ci "Porcentaje de personas en unión formal o informal"
4 Household Socio-Economic Surve… tamh_ch "Tamaño promedio del hogar"
5 Household Socio-Economic Surve… rural_ci "Porcentaje de la población que reside en zonas rura…countries <- idbsocialdataR:::get_countries()
sources <- idbsocialdataR:::get_sources()
themes <- idbsocialdataR:::get_themes()Optional dependency "sf" must be installed to use this function.
idbsocialdataR:::get_map(level = '1', isoalpha3 = 'COL') %>%
ggplot(aes(fill = isoalpha3)) +
geom_sf(size = 0.25)
You can always build your own graphs but sometimes it is useful to have some quick-plots.
idbsocialdataR:::idbsocial_plot('pobreza',type='line', countries='All' ,yearstart = 2000, yearend = 2020, categories='All')
idbsocialdataR:::idbsocial_plot('pobreza',type='bar', countries='MEX,ARG' ,yearstart = 2000, yearend = 2020)
Optional dependency "sf" must be installed to use this function.
idbsocialdataR:::idbsocial_choropleth('pobreza', year = 2020, isoalpha3='All')
The IDB is not responsible, under any circumstance, for damage or compensation, moral or patrimonial; direct or indirect; accessory or special; or by way of consequence, foreseen or unforeseen, that could arise:
I. Under any concept of intellectual property, negligence or detriment of another part theory; I ii. Following the use of the Digital Tool, including, but not limited to defects in the Digital Tool, or the loss or inaccuracy of data of any kind. The foregoing includes expenses or damages associated with communication failures and / or malfunctions of computers, linked to the use of the Digital Tool.