The winners of the American Statistical Association Police Data Challenge have been announced. The ASA teamed up with the Police Data Initiative, which provides open data from local law enforcement agencies in the US, to create a competition for high school and college students to analyze crime data from Baltimore, Seattle and Cincinnati. In this post, we take a look at the winners of the visualization category.
The winners of the Best Visualization for college students were Julia Nguyen, Katherine Qian, Youbeen Shim, Catherine Sun from University of Virginia. Their entry included several visualizations of crime data in Baltimore, including the crime density map shown below. The team used R for all of the data cleaning, manipulation, and visualizations. The tidyverse suite of packages was used for data pipelining (including stringr and lubridate for merging data on latitude/longitude and date), and the ggmap package for visualization.
The winners of the Best Visualization for high school students were Alex Lapuente, Ana Kenefick and Sara Kenefick from Charlotte Latin School (Charlotte, N.C.). They used Microsoft Excel to look at overall trends Seattle crime data, the impact of employment and poverty on crime, and this visualization of the frequency of traffic-related incidents (note the "pedestrian violation" segment — I can attest from experience that jaywalking is strictly enforced in Seattle!):
For more on the Police Data Challenge and the winners in the Overall and Best Use of External Data categories, follow the link below.
This is Statistics: Police Data Challenge: Congratulations to our Winners!