My main focus is on analyzing the various variables present in the provided dataset from the Washington Post, particularly emphasizing the examination of their interrelationships. The dataset revolves around fatal police shootings and encompasses two distinct sets of data.
The second dataset specifically furnishes information about law enforcement officers linked to these incidents.
Key variables in this dataset include ID, Name, Type (officers’ roles), States, ORI codes, and Total Shootings. Upon scrutinizing this data, a notable observation is the prevalence of officers associated with local police departments, and the highest recorded number of fatal shootings attributed to a single officer is 129.
In the earlier blog entry, I offered an overview of the first dataset, highlighting its 12 variables.
The primary goal is to investigate potential correlations among these variables. Additionally, I pinpointed crucial features that could establish connections between the two datasets for future analyses.
In the forthcoming blog post, I intend to delve deeper into these variables, further exploring the correlations that can be derived from them.