In this Data Blog project from Winter 2023, I created and interpreted data visualizations to assess the correlation between a shooter's history of mental illness and the severity of shooting in terms of the total number of victims. Specifically, I made a side-by-side boxplot graph in R, and based on it, I concluded that shooters with a history of mental illness overall tend to target more victims compared to those without mental illness. Also, I found that depression, schizophrenia, and paranoia tend to be the most common mental illnesses among shooters whose histories of mental illnesses are known, and I illustrated this trend in a wordcloud. In order to produce a word cloud of diagnosed mental illnesses, I compiled and cleaned the detailed description of every mass shooter's history of mental illness derived from the Stanford Mass Shootings in America (MSA) database using Python.
My detailed interpretation of these findings can be found in a section of an article published on Medium (https://ucladatares.medium.com/the-rapid-rise-in-mass-shootings-trends-and-analysis-1c3714f47c67).
Stanford MSA data: https://www.kaggle.com/datasets/carlosparadis/stanford-msa?datasetId=2856&select=mass_shooting_events_stanford_msa_release_06142016.csv