Papka, Michael E.
B.S. (Bachelor of Science)
Department of Computer Science
The purpose of this honors capstone project was to create data visualizations of the Chicago Safe Passage program using the programming language Python. The goal was to provide data visualizations geared towards researching the impact of Chicago’s Safe Passage program on crime along safe passage routes, and school attendance records. The programming language Python was used to construct all of the data visualizations. Seven schools within Chicago were chosen for analyzation and visualization creation. The process of visualization creation consisted of gathering raw data on safe passage zones, crimes, and school attendance records. After data was collected, Python was used to clean, organize, and plot the data. Safe passage zones, school location, and crimes committed within those zones were plotted in one visualization. Additionally, a bar graph of school attendance percentiles was created. This was done for the years 2013 through 2018. All of these visualizations were then grouped together to create one visualization per school. The visualizations created allow the viewer to interpret the results, and decide if the Safe Passage Program has been effective in lowering crime around schools, and/or boosting attendance for participating schools.
Finnigan, Kelly A., "Chicago Safe Passage Data Visualization Using Python" (2019). Honors Capstones. 285.
KFinniganCPSSafePassageDataVisualizationUsingPython.pdf (1972 kB)
Visualizations produced by program written in Python. (1.926Mb)
Northern Illinois University
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