I developed a web application for visualizing and analyzing crime data in Philadelphia. The goal of the application is to provide a user-friendly interface for exploring crime patterns and trends in the city, and to give recruiters an understanding of my technical skills.
The data for the project was sourced from the Philadelphia Police Department and included information on over 2 million crimes reported in the city between 2021 and 2022. I used Python to clean and process the data, which was provided in the form of CSV files.
Those CSV files were then converted into GeoJSON files in order for the the data to be more easiliy accessible by the application. GeoJSON mapped the data by location. This allowed me to create interactive crime maps that display information on the number and type of crimes in each neighborhood.
The front-end of the application was built using Javascript, specifically LeafletJS, an open-source JavaScript library for creating maps. With LeafletJS, I was able to create an intuitive and interactive user interface that allows users to pan, zoom, and filter the data on the crime maps. I also implemented support of multiple data sets that provides multiple dimension to look at the crime data on top of different districts in Philadelphia.
This application will be further developed in the future to also includes several other visualization tools and statistics to help users understand the data. Users can view crime statistics for different neighborhoods, view time-series plots of crime rates, and compare crime rates across different time periods.
Overall, this project demonstrates my skills in data processing, web development, and visualization. I was able to take a large and complex data set and turn it into a valuable resource for understanding crime patterns and trends in Philadelphia. I believe that my web application would be an invaluable tool for anyone interested in the relationship between crime and poverty in their city.
Application: http://phillycrime.nehla.codes