The goal of prisonbrief is to download, clean and return data from the World Prison Brief website. The World Prison Brief is an online database compiled by the Institute for Criminal Policy Research with information on prison systems around the world. Data currently cover 223 jurisdictions and have been collected from public sources. The prisonbrief package provides easy-to-use functions to convert WPB data into a format convenient for statistical analysis.
Installation
The stable version of prisonbrief is available on CRAN. To install it, just type:
install.packages("prisonbrief")You can install the most recent development version of prisonbrief using the devtools package. First, you need to install the devtools package with the following code:
if(!require(devtools)) install.packages("devtools")Then you need to load devtools and install prisonbrief from its GitHub repository:
library(devtools)
devtools::install_github("danilofreire/prisonbrief")If you are using Linux, you may need to type the following command before installing prisonbrief:
sudo apt-get install libudunits2-devUsage
prisonbrief is quite simple to use. The package contains only three functions, all of them starting with wpb, a mnemonic for World Prison Brief.
The first is a convenience function named wpb_list(). It prints a list of available countries to the console.
library(prisonbrief)
wpb_list()
#> # A tibble: 226 x 2
#> country_name country_url
#> <chr> <chr>
#> 1 Afghanistan afghanistan
#> 2 Albania albania
#> 3 Algeria algeria
#> 4 American Samoa (USA) american-samoa-usa
#> 5 Andorra andorra
#> 6 Angola angola
#> 7 Anguilla (United Kingdom) anguilla-united-kingdom
#> 8 Antigua and Barbuda antigua-and-barbuda
#> 9 Argentina argentina
#> 10 Armenia armenia
#> # ... with 216 more rowsThe second function is wpb_table(). This function returns a series of variables about the prison systems of the world, of a particular region, or of a specific country. For instance, the code below downloads prison data for Africa:
africa <- wpb_table(region = "Africa")
names(africa)
#> [1] "country" "prison_population_rate"
#> [3] "prison-population-total" "female-prisoners"
#> [5] "pre-trial-detainees" "foreign-prisoners"
#> [7] "occupancy-level" "iso_a2"
#> [9] "name" "geometry"The region choices are “Africa”, “Asia”, “Caribbean”, “Central America”, “Europe”, “Middle East”, “North America”, “Oceania”, “South America” and “All”.
wpb_table() also provides geometric shapes for maps. For instance, you can download and plot the prison population rate in South America with only a few lines of code:
south_america <- wpb_table(region = "South America")
library(ggplot2)
ggplot(south_america, aes(fill = prison_population_rate)) +
geom_sf() +
scale_fill_distiller(palette = "YlOrRd", trans = "reverse") +
theme_minimal()
The function can also be used to retrieve data for a single country. The data returned are parsed from the single country tables, however, and are not ready for quantitative analysis without further cleaning (removing parentheses etc.). Since some of this information may be relevant, we have chosen to leave it in. Data from regions instead of a single country are fully prepared for automated analysis.
Finally, we have added the wpb_series() function to the package. The function downloads and tidies the tables describing the trends in the prison population total and the prison population rate for every jurisdiction included in the project. Below is an example taken from Germany’s country profile:
You can retrieve the same information with the following code:
germany <- wpb_series(country = "Germany")
germany
#> # A tibble: 8 x 4
#> Country Year `Prison population total` `Prison population rate`
#> <chr> <dbl> <dbl> <dbl>
#> 1 germany 2000 70252 85
#> 2 germany 2002 70977 86
#> 3 germany 2004 79452 96
#> 4 germany 2006 76629 93
#> 5 germany 2008 72259 88
#> 6 germany 2010 69385 85
#> 7 germany 2012 65889 82
#> 8 germany 2014 61872 76wpb_series() can also be combined with wpb_list() to make interesting time series graphs. The code below downloads data for all countries then plots the prison population rate for Brazil, Germany, Russia and the United States:
library(dplyr)
x <- list()
countries <- wpb_list()
for(i in 1:nrow(countries)){
y <- try(wpb_series(country = countries$country_url[i]), silent = FALSE)
if(class(y) != 'try-error'){
x[[i]] <- y
} else{
next
}
}
X <- data.table::rbindlist(x, fill = TRUE) %>%
dplyr::full_join(countries, by = c("Country" = "country_url"))
X %>% dplyr::filter(country_name %in% c("Brazil",
"Germany",
"Russian Federation",
"United States of America")) %>%
ggplot(aes(x = Year, y = `Prison population rate`,
group = country_name, colour = country_name)) +
geom_line() +
theme_minimal()
Contributions
prisonbrief was written by Danilo Freire and Robert Myles McDonnell. Feedback and comments are most welcome. If you have any suggestions on how to improve this package feel free to open an issue on GitHub.
Citation
You can cite the prisonbrief package with:
citation("prisonbrief")
#>
#> To cite 'prisonbrief' in publications, please use:
#>
#> Danilo Freire and Robert Myles McDonnell (2017). prisonbrief:
#> Downloads and Parses World Prison Brief Data. R package version
#> 0.1.0. URL: https://CRAN.R-project.org/package=prisonbrief
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Manual{,
#> title = {{prisonbrief}: Downloads and Parses World Prison Brief Data},
#> author = {Danilo Freire and Robert Myles McDonnell},
#> note = {R package version 0.1.0},
#> year = {2017},
#> url = {https://CRAN.R-project.org/package=prisonbrief},
#> }Please also cite the source as World Prison Brief, Institute for Criminal Policy Research.