In this project, I've applied my knowledge of Python and foundations of pandas by answering interesting questions using the Stanford Open Policing Project dataset and the Weather dataset. Note that the project only covers Rhode Island as the district of police activity. I answered main questions such as:

1. Does gender really affect who is frisked during a search?
2. Does gender really affect whose vehicle is searched?
3. Which gender performs a lot of violations?
4. What is the likelihood of getting arrested at a certain time of the day? Whether drug stops are on the rise? For how long you're stopped for a violation?
5. Does the impact of weather really determine a change in police activity during traffic stops?

In trying to answer such questions, I performed cleaning messy data, creating visualizations, combining and reshaping datasets, and manipulating time series data.