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An exploration of a part of the Stanford Open Policing Project dataset and analysis of the impact of gender, hour of day, weather and many other variables on police behavior during traffic stops.

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A case study on police behavior during traffic stops with pandas

In this notebook, we'll walk along a journey exploring part of the Stanford Open Policing Project dataset and analyze the impact of gender, hour of day, weather and many other variables on police behavior during traffic stops. This notebook is aimed for those who wants to gain more practice cleaning messy data, creating visualizations, combining and reshaping datasets, and manipulating time series data with the pandas library.

The original dataset has data collected in 31 US states. For the sake of simplicity, we will use only the data for the Rhode Island state, as it is enough to make our point here. You can download the full dataset for anyone of the 31 states here.

Also, these notes are fully based on the datacamp course: Analyzing Police activity with pandas. I give all credits to the datacamp team.

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An exploration of a part of the Stanford Open Policing Project dataset and analysis of the impact of gender, hour of day, weather and many other variables on police behavior during traffic stops.

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