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Black and Latinx individuals are more likely to be arrested from stop and frisk incidents than White individuals. This analysis explores the various factors that lead up to an arrest. This analysis is an exploratory classification model ranking the features that are most important in predicting likelihood of arrest from Stop and Frisk. The analysis was completed entirely in Jupyter Notebooks, with sklearn and matplotlib.pyplot being the most incremental packages for analysis and visualization.

Jupyter Notebook 100.00%
race policing

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