Comparable Cross-City Analysis
Get harmonized, standardized fields across cities for direct comparison and analysis.
R Package for Civic Data
tidycops provides a consistent R interface for downloading and comparing public police incident data. Rather than navigating different data portals and APIs for each city, use the same functions to pull incidents data across multiple cities with harmonized, comparable fields.
Purpose
Make it easier to work with and compare public police incident data across multiple US cities without navigating different portals and APIs.
About tidycops
tidycops is an R package designed to make it easier to work with and compare public police incident data across multiple US cities. Instead of navigating different data portals and APIs for each city—some use Socrata, others ESRI or CKAN—you can use the same R functions to pull incident data consistently.
The package provides comparable, harmonized fields across cities for direct comparison, while also giving you access to all source-specific fields when you need the complete picture. With flexible queries, a simple interface, and support for 25+ cities, tidycops makes cross-city police data analysis practical and accessible.
Key Features
Get harmonized, standardized fields across cities for direct comparison and analysis.
Access all source-specific fields when you need the complete picture and context.
Filter by date range, neighborhood, and more with a simple, consistent interface.
Use the same R functions regardless of which city or data source you're working with.
Supported Cities
Get Started
tidycops is available on GitHub with full documentation, vignettes on geometry workflows and cross-city comparisons, and an issue tracker for bugs and feature requests.
This package has been a labor of love and we'd love feedback from folks who use R regularly. If you're interested in testing the package with your own research, requesting additional cities or data fields, reporting bugs, or suggesting improvements—please try it out and share your thoughts!
We tried, where we could, to bridge gaps in data sources across years. Test all the things and suggest all the features. If you see your city in the list above and want to give it a go, please do and tell us why it works or what needs improvement.