Getting Started with CepalStatR
Henry Osorto
Source:vignettes/getting-started.Rmd
getting-started.RmdOverview
CepalStatR provides functions to access, explore, and
visualize data from the statistical data portal of the Economic
Commission for Latin America and the Caribbean. The package is designed
to support reproducible workflows in R by retrieving metadata and
indicator data through a public statistical API.
Exploring available indicators
The function call.indicators() retrieves the
hierarchical structure of available indicators.
indicators <- call.indicators(progress = FALSE)
head(indicators)
#> Area Dimension Subdimension
#> 1 Demographic and social Demographic Population
#> 2 Demographic and social Demographic Population
#> 3 Demographic and social Demographic Population
#> 4 Demographic and social Demographic Population
#> 5 Demographic and social Demographic Population
#> 6 Demographic and social Demographic Fertility
#> Group Sub Group Level 1
#> 1 Total population, by sex <NA>
#> 2 Population, by age group, by sex <NA>
#> 3 Demographic dependency ratio, by dependent groups and sex <NA>
#> 4 Structure of the total population by sex and age group <NA>
#> 5 Annual growth rate of the total population, by age group <NA>
#> 6 Crude birth rate <NA>
#> Sub Group Level 2 Indicator Name
#> 1 <NA> Total population, by sex
#> 2 <NA> Population, by age group, by sex
#> 3 <NA> Demographic dependency ratio, by dependent groups and sex
#> 4 <NA> Structure of the total population by sex and age group
#> 5 <NA> Annual growth rate of the total population, by age group
#> 6 <NA> Crude birth rate
#> Indicator ID
#> 1 4788
#> 2 4789
#> 3 4792
#> 4 4793
#> 5 4795
#> 6 4787The returned data frame includes information about thematic areas, dimensions, subdimensions, groups, indicator names, and indicator identifiers.
Listing available countries
The function countries() returns the countries available
in the statistical dimensions used by the API.
Retrieving indicator data
The main data retrieval function is call.data(). Users
provide an indicator identifier and obtain an analysis-ready data
frame.
population <- call.data(id.indicator = 1, progress = FALSE)
head(population)
#> # A tibble: 6 × 15
#> Value Sex Country Years indicator_meta_name unit definition data_features
#> <dbl> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 31216. Both … Argent… 1987 Total population, … Thou… "<p align… Annual estim…
#> 2 33568. Both … Argent… 1992 Total population, … Thou… "<p align… Annual estim…
#> 3 34489. Both … Argent… 1994 Total population, … Thou… "<p align… Annual estim…
#> 4 37480. Both … Argent… 2001 Total population, … Thou… "<p align… Annual estim…
#> 5 38278. Both … Argent… 2003 Total population, … Thou… "<p align… Annual estim…
#> 6 40684. Both … Argent… 2009 Total population, … Thou… "<p align… Annual estim…
#> # ℹ 7 more variables: calculation_methodology <chr>, comments <chr>,
#> # theme <chr>, area_meta <chr>, last_update <chr>, indicator_id <dbl>,
#> # indicator_name <chr>Interactive tools
CepalStatR also includes interactive tools to explore
the indicator catalogue.
These functions return HTML-based outputs that are useful for exploring metadata and thematic hierarchies.
Visualization examples
The package includes functions for common visual outputs, such as population pyramids and rankings for indicators related to sustainable development goals.
pyramids(country = "Honduras", years = c(1, 5, 10, 15), progress = FALSE)
ranking.sdg(id.indicator = 3682, progress = FALSE)When saving output files, use tempdir() in examples and
reproducible scripts.
ranking.sdg(id.indicator = 3682, save = TRUE, file = file.path(tempdir(), "ranking_sdg.png"), progress = FALSE)