Gives convenient access to publicly available police-recorded open crime data from large cities in the United States that are included in the Crime Open Database < https://osf.io/zyaqn/>.
The goal of crimedata is to access police-recorded crime data from large US cities using the Open Crime Database (CODE), a service that provides these data in a convenient format for analysis. All the data are available to use for free as long as you acknowledge the source of the data.
The function get_crime_data() returns a tidy
data tibble
of crime data with each row representing a single crime. The data provided for
each offense includes the offense type, approximate offense location and
date/time. More fields are available for some records, depending on what data
have been released by each city. For most cities, data are available from 2010
onwards, with some available back to 2007. Use list_crime_data() to see which
years are available for which cities.
More detail about what data are available, how they were constructed and the meanings of the different categories can be found on the CODE project website. Further detail is available in a pre-print data paper.
You can install crimedata from github with:
# install.packages("devtools")devtools::install_github("mpjashby/crimedata")
Data can be downloaded by year and by city. By default (i.e. if no arguments are specified) a 1% sample of data for all cities for the most recent available year is returned.
library(crimedata)crime_data <- get_crime_data()
The data are in a tidy format, so can be quickly manipulated using dplyr verbs. For example, to analyse two years of personal robberies in Chicago and Detroit, you can run:
chicago_robberies <- get_crime_data(years = 2009:2010,cities = c("Chicago", "Detroit"),type = "core") %>%filter(offense_type == "personal robbery")
The package includes two datasets. homicides15 contains records of 1,922
recorded homicides in nine US cities in 2015. nycvehiclethefts contains
records of 35,746 thefts of motor vehicles in New York City from 2014 to 2017.
These may be particularly useful for teaching purposes.
NEWS.md file to track changes to the package.