Author: Henry Osorto

# Getting Started with CepalStatR

#### Henry Osorto

# Overview

`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.

# Loading the package

    library(CepalStatR)

# 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         4787

The 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.

    head(countries(language.en = TRUE))
    #>             Countries
    #> 1            Anguilla
    #> 2 Antigua and Barbuda
    #> 3           Argentina
    #> 4               Aruba
    #> 5             Bahamas
    #> 6            Barbados

# 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.

    viewer.indicators()
    topic_map()

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)

# Reproducibility notes

The package retrieves data from a public API. Therefore, results may depend on internet connectivity and the availability of the external service at runtime. Functions include progress messages and basic error handling to support reproducible workflows.