At the outset of my work with the two CSV files, ‘fatal-police-shootings-data’ and ‘fatal-police-shootings-agencies,’ I commenced by importing them into Jupyter Notebook. Here’s a concise overview of the initial tasks and obstacles I faced:
ID: Each fatal police shooting incident is assigned a unique ID, ranging from 3 to 8696, indicating 8002 distinct incidents in the dataset without missing or duplicate IDs.
Date: The dataset covers incidents from January 2, 2015, to December 1, 2022, with the mean date around January 12, 2019. About 25% of incidents occurred before January 18, 2017, and 75% before January 21, 2021.
Age: Victim ages range from 2 to 92 years old, with an average age of 37.209. Approximately 25% of victims are 27 or younger, and 75% are 45 or younger. The standard deviation is around 12.979, indicating age variability.
Longitude: Longitude coordinates vary from about -160.007 to -67.867, with the mean around -97.041. Roughly 25% of incidents occurred west of -112.028, and 75% west of -83.152. The standard deviation is approximately 16.525, indicating location dispersion.
Latitude: Latitude values range from about 19.498 to 71.301, with the mean around 36.676. About 25% of incidents occurred south of 33.480, and 75% south of 40.027. The standard deviation is about 5.380, indicating location dispersion along the latitude axis.