R Interface to the US Census Bureau International Data Base API

Use R to make requests to the US Census Bureau's International Data Base API. Results are returned as R data frames. For more information about the IDB API, visit < http://www.census.gov/data/developers/data-sets/international-database.html>.


An R interface to the US Census Bureau International Data Base API

This R package enables users to fetch international demographic indicators from the US Census Bureau's International Data Base API and return R data frames. Total population data are available from 1950-2050 (projected); age-group subsets and other demographic indicators are available for varying periods by country.

Install from CRAN with:

install.packages('idbr')

Or get the development version from GitHub:

library(devtools)
install_github('walkerke/idbr')

Information about how to use the package is found below; more examples of how to use the package, such as animated GIF and interactive Plotly visualizations, are also found at the following blog posts:

To get started, load idbr and set your Census API key with the idb_api_key() function. An API key can be obtained from the US Census Bureau at http://api.census.gov/data/key_signup.html.

library(idbr)
 
idb_api_key('Your API key goes here')

There are two main functions in the idbr package: idb1() and idb5(). idb1() grants access to the single-year-of-age dataset, which returns population counts by single-year age bands, subsetted optionally by sex and age range. This dataset is well-suited for analyses and visualizations of the age composition of countries, such as population pyramids:

library(dplyr)
library(ggplot2)
library(ggthemes)
 
# Supply the FIPS country code and year for which you'd like to request data, optionally by sex
male <- idb1('CH', 2016, sex = 'male') %>%
  mutate(POP = POP * -1,
         SEX = 'Male')
 
female <- idb1('CH', 2016, sex = 'female') %>%
  mutate(SEX = 'Female')
 
china <- rbind(male, female) 
 
# Build the visualization
 
ggplot(china, aes(x = AGE, y = POP, fill = SEX, width = 1)) +
  coord_flip() +
  annotate('text', x = 95, y = 6500000, 
           label = 'Data source: US Census Bureau \nIDB via the idbr R package', 
           size = 3.5, hjust = 0) + 
  geom_bar(data = subset(china, SEX == "Female"), stat = "identity") +
  geom_bar(data = subset(china, SEX == "Male"), stat = "identity") +
  scale_y_continuous(breaks = seq(-10000000, 10000000, 5000000),
                     labels = paste0(as.character(c(seq(10, 0, -5), c(5, 10))), "m")) +
  theme_economist(base_size = 14) + 
  scale_fill_economist() + 
  ggtitle('Population structure of China, 2016') + 
  ylab('Population') + 
  xlab('Age') + 
  theme(legend.position = "bottom", 
        legend.title = element_blank()) + 
  guides(fill = guide_legend(reverse = TRUE))
 

The idb5() function grants access to the five-year-age-band dataset, which includes a wide range of fertility, mortality, and migration indicators along with overall population counts. In turn, it can be used to inform analyses of how demographic indicators vary by country over time, among many other use cases.

library(countrycode)
 
ssrs <- countrycode(c('Russia', 'Ukraine', 'Belarus'), 'country.name', 'fips104')
 
# Fetch data for 'E0', which represents life expectancy at birth
ssr_df <- idb5(ssrs, 1989:2015, variables = 'E0', country_name = TRUE)
 
ggplot(ssr_df, aes(x = time, y = E0, color = NAME)) + 
  geom_line(size = 1) + 
  theme_economist(base_size = 14) + 
  scale_color_economist() + 
  ylab('Life expectancy at birth') + 
  xlab('Year') + 
  theme(legend.title = element_blank(), 
        legend.position = "bottom") + 
  annotate('text', x = 2010, y = 64.5, 
          label = 'Data source: US Census Bureau IDB \nvia the idbr R package', 
          size = 3.5)

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Reference manual

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install.packages("idbr")

0.2 by Kyle Walker, a year ago


Browse source code at https://github.com/cran/idbr


Authors: Kyle Walker [aut, cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports jsonlite, dplyr, httr, countrycode

Suggests tidyr, plotly


See at CRAN