Description
In this talk we will share a Python library to obtain and analyze policing data, that was developed in conjunction with community activists, data scientists, social scientists and the Small Town Police Accountability (SToPA) Research Lab. We will showcase components of the SToPA library which use Python tools such as web drivers, optical character recognition, geospatial mapping, machine learning and statistical sampling to better understand the policing landscape. The goal of this work is to present an easily replicable framework for analyzing police and community interactions with accessible on-ramps for activists, developers and researchers.