Introduction

The ColombiAPI package provides a unified interface to access open data from the API-Colombia, World Bank API, Nager.Date API, and the REST Countries API, with a focus on Colombia. It allows users to retrieve up-to-date or historical information on topics such as geographic locations, cultural attractions, economic indicators, demographic data, national holidays, and key country-level details.

In addition to API-access functions, the package includes a collection of curated datasets related to Colombia. These datasets cover a wide range of topics including air quality monitoring, education (public schools), business and holiday calendars, agricultural exports (coffee), regulatory information (cannabis licenses), climate data (Medellin rainfall), and urban development (Bogota shopping malls).

ColombiAPI is designed to support users working with data related to Colombia by integrating international RESTful APIs with Colombian-specific APIs and structured, reliable datasets from public, academic, and government sources into a single, easy-to-use R package.

ColombiAPI Functions

The ColombiAPI package provides several core functions to access real-time or historical information about Colombia from public APIs such as API-Colombia, World Bank API, Nager.Date, and the REST Countries API.

Below is a list of the main functions included in the package:

get_colombia_airports(): Get Colombia’s Airports from API Colombia.
get_colombia_attractions(): Get All Touristic Attractions of Colombia from API Colombia.
get_colombia_child_mortality(): Get Colombia’s Under-5 Mortality Rate from World Bank.
get_colombia_cities(): Get All Cities of Colombia from API Colombia.
get_colombia_cpi(): Get Colombia’s Consumer Price Index (2010 = 100) from World Bank.
get_colombia_departments(): Get Colombia’s Departments from API Colombia.
get_colombia_energy_use(): Get Colombia’s Energy Use (kg of oil equivalent per capita) from World Bank.
get_colombia_gdp function(): Get Colombia’s GDP (current US$) from World Bank.
get_colombia_holidays(): Get official public holidays in Colombia for a given year, e.g., get_colombia_holidays(2025).
get_colombia_hospital_beds(): Get Colombia’s Hospital Beds (per 1,000 people) from World Bank.
get_colombia_invasive_species(): Get Invasive Species of Colombia from API Colombia.
get_colombia_life_expectancy(): Get Colombia’s Life Expectancy at Birth (Total, Years) from World Bank.
get_colombia_literacy_rate(): Get Colombia’s Adult Literacy Rate from World Bank.
get_colombia_native_communities(): Get Native Communities of Colombia from API Colombia.
get_colombia_natural_areas(): Get Natural Areas of Colombia from API Colombia.
get_colombia_population(): Get Colombia’s Total Population from World Bank.
get_colombia_presidents(): Get Colombia’s Presidents from API Colombia.
get_colombia_radios(): Get Radios of Colombia from API Colombia.
get_colombia_regions(): Get Colombia’s Regions from API Colombia.
get_colombia_typical_dishes(): Get Typical Dishes of Colombia from API Colombia.
get_colombia_unemployment(): Get Colombia’s Unemployment Rate (Total) from World Bank.
get_country_info_co(): Get Country Information for Colombia from restcountries.
view_datasets_ColombiAPI(): View available curated datasets included in ColombiAPI.

These functions allow users to access high-quality and structured information on Colombia, which can be combined with tools like dplyr and ggplot2 to support a wide range of data analysis, visualization, and research tasks. In the following sections, you’ll find examples on how to work with ColombiAPI in practical scenarios.

Colombia’s GDP (Current US$) from World Bank 2022 - 2017



colombia_gdp <- head(get_colombia_gdp())

print(colombia_gdp)
#> # A tibble: 6 × 5
#>   indicator         country   year         value value_label    
#>   <chr>             <chr>    <int>         <dbl> <chr>          
#> 1 GDP (current US$) Colombia  2022 345632492851. 345,632,492,851
#> 2 GDP (current US$) Colombia  2021 318524633225. 318,524,633,225
#> 3 GDP (current US$) Colombia  2020 270348342541. 270,348,342,541
#> 4 GDP (current US$) Colombia  2019 323031701193. 323,031,701,193
#> 5 GDP (current US$) Colombia  2018 334198218098. 334,198,218,098
#> 6 GDP (current US$) Colombia  2017 311866875157. 311,866,875,157

Colombia’s Life Expectancy at Birth from World Bank 2022 - 2017


colombia_life_expectancy <- head(get_colombia_life_expectancy())

print(colombia_life_expectancy)
#> # A tibble: 6 × 4
#>   indicator                               country   year value
#>   <chr>                                   <chr>    <int> <dbl>
#> 1 Life expectancy at birth, total (years) Colombia  2022  76.5
#> 2 Life expectancy at birth, total (years) Colombia  2021  72.7
#> 3 Life expectancy at birth, total (years) Colombia  2020  74.8
#> 4 Life expectancy at birth, total (years) Colombia  2019  76.8
#> 5 Life expectancy at birth, total (years) Colombia  2018  76.6
#> 6 Life expectancy at birth, total (years) Colombia  2017  76.4

Colombia’s Total Population from World Bank 2022 - 2017


colombia_population <- head(get_colombia_population())

print(colombia_population)
#> # A tibble: 6 × 5
#>   indicator         country   year    value value_label
#>   <chr>             <chr>    <int>    <int> <chr>      
#> 1 Population, total Colombia  2022 51737944 51,737,944 
#> 2 Population, total Colombia  2021 51188173 51,188,173 
#> 3 Population, total Colombia  2020 50629997 50,629,997 
#> 4 Population, total Colombia  2019 49907985 49,907,985 
#> 5 Population, total Colombia  2018 49024465 49,024,465 
#> 6 Population, total Colombia  2017 48131078 48,131,078

Monthly Average Rainfall in Medellin


Medellin_rain_tbl_df %>%
  group_by(month) %>%
  summarise(mean_rainfall = mean(rainfall, na.rm = TRUE), .groups = "drop") %>%
  ggplot(aes(x = month, y = mean_rainfall)) +
  geom_line(size = 1, color = "steelblue") +
  geom_point(size = 2, color = "darkred") +
  labs(
    title = "Climatological Monthly Average Rainfall in Medellin",
    subtitle = "Each point represents the long-term mean rainfall for that month, averaged across all years",
    x = "Month",
    y = "Mean Rainfall (mm)"
  ) +
  theme_minimal()

Dataset Suffixes

Each dataset in ColombiAPI is labeled with a suffix to indicate its type and structure:

_df: A standard data frame.
_tbl_df: A tibble, a modern version of a data frame with better formatting and functionality.
_Date: An object of type Date.

Datasets Included in ColombiAPI

In addition to API functions, ColombiAPI includes several preloaded datasets that provide valuable insights into various aspects of Colombia:

Bogota_airstations_df: A data frame containing coordinates of air quality monitoring stations in Bogota.
Bogota_business_Date: A Date object listing official business dates in Bogota.
Colombia_coffee_tbl_df: A tibble with details of Colombian coffee export and import for the year 2016.

Viewing All Available Datasets

The ColombiAPI package includes a built-in function, view_datasets_ColombiAPI(), which allows users to view a comprehensive list of all datasets available in the package directly from the console:


view_datasets_ColombiAPI()
#> Datasets available in the 'ColombiAPI' package:
#> [1] "Bogota_airstations_df"       "Bogota_business_Date"       
#> [3] "Bogota_holidays_Date"        "Bogota_malls_tbl_df"        
#> [5] "Cannabis_Licenses_tbl_df"    "Colombia_coffee_tbl_df"     
#> [7] "Medellin_rain_tbl_df"        "Tulua_Public_Schools_tbl_df"

Conclusion

The ColombiAPI package provides a unified and powerful interface for accessing both real-time data through public APIs and a collection of curated datasets about Colombia. By integrating multiple data sources — including API-Colombia for geography, culture, tourism, and government information, the World Bank API for economic and demographic indicators, Nager.Date for official holidays, and the REST Countries API for general country details — the package allows users to explore Colombia from multiple perspectives in a structured and consistent way.

In addition to API-driven data, ColombiAPI offers preloaded open datasets related to Colombia, such as Bogotá air stations, public schools, business and holiday dates, coffee exports, cannabis licenses, Medellin rainfall, and malls in Bogota. This dual approach of combining live API data with curated datasets empowers users to analyze Colombia’s social, economic, environmental, and cultural landscape in greater depth.

Designed to support reproducible research, education, policy analysis, and data journalism, ColombiAPI makes it possible to seamlessly integrate Colombian data into the R ecosystem, ensuring accessibility, reliability, and clarity for a wide range of applications.

ColombiAPI: Access Colombian Data via APIs and Curated Datasets