Functions for MexicoDataAPI

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

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

• get_country_info_mx(): Get Key Country Information about Mexico from the REST Countries API

• get_mexico_cpi(): Get Mexico’s Consumer Price Index (2010 = 100) from World Bank

• get_mexico_gdp(): Get Mexico’s GDP (Current US$) from World Bank

• get_mexico_holidays(): Get official public holidays in Mexico for a given year, e.g., get_mexico_holidays(2025).

• get_mexico_life_expectancy(): Get Mexico’s Life Expectancy from World Bank

• get_mexico_literacy_rate(): Get Mexico’s Literacy Rate (Age 15+) from World Bank

• get_mexico_population(): Get Mexico’s Population (Total) from World Bank

• get_mexico_unemployment(): Get Mexico’s Unemployment Rate (%) from World Bank

• view_datasets_MexicoDataAPI(): Lists all curated datasets included in the MexicoDataAPI package

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

 
 
mexico_gdp <- head(get_mexico_gdp())
 
 print(mexico_gdp)
 #> # A tibble: 6 ×ばつ 5
 #> indicator country year value value_label 
 #> <chr> <chr> <int> <dbl> <chr> 
 #> 1 GDP (current US$) Mexico 2022 1.47e12 1,466,464,899,304
 #> 2 GDP (current US$) Mexico 2021 1.32e12 1,316,569,466,735
 #> 3 GDP (current US$) Mexico 2020 1.12e12 1,121,064,767,402
 #> 4 GDP (current US$) Mexico 2019 1.30e12 1,304,106,203,902
 #> 5 GDP (current US$) Mexico 2018 1.26e12 1,256,300,182,776
 #> 6 GDP (current US$) Mexico 2017 1.19e12 1,190,721,475,906

 
life_expectancy <- head(get_mexico_life_expectancy())
 
 print(life_expectancy)
 #> # A tibble: 6 ×ばつ 4
 #> indicator country year value
 #> <chr> <chr> <int> <dbl>
 #> 1 Life expectancy at birth, total (years) Mexico 2022 74.0
 #> 2 Life expectancy at birth, total (years) Mexico 2021 69.8
 #> 3 Life expectancy at birth, total (years) Mexico 2020 70.4
 #> 4 Life expectancy at birth, total (years) Mexico 2019 74.5
 #> 5 Life expectancy at birth, total (years) Mexico 2018 74.3
 #> 6 Life expectancy at birth, total (years) Mexico 2017 74.3

 
mexico_population <- head(get_mexico_population())
 
 print(mexico_population)
 #> # A tibble: 6 ×ばつ 5
 #> indicator country year value value_label
 #> <chr> <chr> <int> <int> <chr> 
 #> 1 Population, total Mexico 2022 128613117 128,613,117
 #> 2 Population, total Mexico 2021 127648148 127,648,148
 #> 3 Population, total Mexico 2020 126799054 126,799,054
 #> 4 Population, total Mexico 2019 125762982 125,762,982
 #> 5 Population, total Mexico 2018 124573711 124,573,711
 #> 6 Population, total Mexico 2017 123400057 123,400,057

 
 
 # Summary of average income by education level
avg_income_by_education <- mex_income_2008_tbl_df %>%
 group_by(education) %>%
 summarise(avg_income = mean(income, na.rm = TRUE)) %>%
 arrange(desc(avg_income))
 
 # Plot
 ggplot(avg_income_by_education, aes(x = reorder(education, avg_income), y = avg_income)) +
 geom_col(fill = "#0072B2") +
 coord_flip() +
 labs(
 title = "Average Household Income by Education Level (2008)",
 x = "Education Level",
 y = "Average Income (MXN)"
 ) +
 theme_minimal()

Dataset Suffixes

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

• _df: A standard data frame.

• _tbl_df: A tibble data frame object.

• _chr: A character object.

Datasets Included in MexicoDataAPI

In addition to API access functions, MexicoDataAPI provides several preloaded datasets related to Mexico’s environment, demographics, and public data. Here are some featured examples:

• mexico_elections_df: Data frame containing a subset of the 2012 Mexico Elections Panel Study.

• mex_income_2016_tbl_df: Tibble containing household-level income data and associated demographic characteristics from the 2016 ENIGH (Household Income and Expenditure Survey).

• mexico_abb_chr: Character vector containing the official two- or three-letter postal abbreviations for the 32 federal entities of Mexico.

Conclusion

The MexicoDataAPI package provides a comprehensive interface to access open data about Mexico through RESTful APIs and curated datasets. It includes functions to retrieve real-time information from the World Bank API, REST Countries API, and Nager.Date API, covering topics such as population, GDP, CPI, life expectancy, literacy, unemployment, general country-level indicators, and official public holidays. In addition, the package offers curated datasets related to air quality monitoring stations, pollution zones, state-level income surveys for 2008 and 2016, postal abbreviations, election studies, and ecological data from the Chiapas dry forests. Together, these resources support research, teaching, and analysis focused on Mexico’s economic, environmental, and sociopolitical landscape.