In this blog, I primarily discuss the various variables within the given dataset from the Washington Post, with a particular focus on examining their interrelationships. The dataset pertains to fatal police shootings and comprises two distinct sets of data.
The second dataset specifically provides details about law enforcement officers who have been identified in connection with these incidents. It includes variables such as ID, Name, Type (representing the officers’ roles), States, ORI codes, and Total Shootings. While reviewing this data, I observed that the majority of officers listed are affiliated with local police departments, and the highest number of fatal shootings attributed to a single officer is 129.
In a previous blog, I provided an overview of the first dataset, highlighting its 12 variables. My aim is to explore the correlations that may exist among these variables. I also identified key features that may serve as potential points of connection between the two datasets for future analysis.
In my upcoming blog, I will delve deeper into these variables and further explore the correlations that can be drawn between them.