The love of one’s country is a splendid thing. But why should love stop at the border? (Pablo Casals, Spanish cellist)

Some time ago, I discovered Enigma, an amazing open platform that unifies billions of records from thousands of government sources to make the world of public data universally accessible and useful. This is the first experiment I have done using data from Enigma. This is what I did:

1. Create a free account, search and download data. Save the csv file in your working directory. File contains information about all prison facilities in the United States (private and state run) as recorded by the Department of Corrections in each state. Facility types, names, addresses (or lat/long coordinates) ownership names and detailed. In sum, there is information about 1.248 prison facilities.
2. Since most of the prisons of the file do not contain geographical coordinates, I obtain latitude and longitude using geocode function from ggmap package. This step takes some time. I also remove closed facilities. Finally, I obtain a data set with complete information of 953 prison facilities.
3. After cleaning and filling out data, generating the map is very easy using leaflet package for R. I create a column named popup_info pasting name and address to be shown in the popup. Instead using default OpenStreetMap basemap I use a CartoDB one.

In my opinion, resulting map is very appealing with a minimal effort:

This plot could be a good example of visual correlation, because it depends on this. Here you have the code:

library(dplyr)
library(ggmap)
library(leaflet)
setwd("YOUR WORKING DIRECTORY HERE")
prisons = read.csv(file="enigma-enigma.prisons.all-facilities-bd6a927c4024c16d8ba9e21d52292b0f.csv", stringsAsFactors=FALSE)
prisons %>% 
  mutate(address=paste(facility_address1, city, state, zip, "EEUU", sep=", ")) %>%
  select(address) %>% 
  lapply(function(x){geocode(x, output="latlon")})  %>% 
  as.data.frame %>% 
  cbind(prisons) -> prisons
prisons %>%  
  mutate(popup_info=paste(sep = "
", paste0("<b>", facility_name, "</b>"), facility_address1, city, state, zip)) %>% 
  mutate(lon=ifelse(is.na(longitude), address.lon, longitude),
         lat=ifelse(is.na(latitude),  address.lat, latitude)) %>%
  filter(!is.na(lon) & !grepl("CLOSED", facility_name)) -> prisons
leaflet(prisons) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addCircleMarkers(lng = ~lon, 
                   lat = ~lat, 
                   radius = 3, 
                   color = "red",
                   stroke=FALSE,
                   fillOpacity = 0.5,
                   popup = ~popup_info)