Exploration of data : Understanding the dataset itself was the first step in our investigation. I carefully studied each column, figuring out what the labels and figures meant. It was important to comprehend the context of the data since each item had the weight of a sad occurrence; it wasn’t just a collection of facts.

The Heart of Exploration: Asking the Right Questions : 

Who are those affected by fatal police shootings the most?
I found inequalities depending on ethnicity, age, gender, and signs of mental illness by immersing myself in demographic data.

Analysing demographic data:

What is the average age of the victims, in terms of age distribution? Do various racial groups’ average ages differ significantly from one another?
Gender Inequalities: What is the victims’ gender composition? Exist any gender-specific trends in the deadly police shootings?
Racial Inequalities: Which races make up the victims? Are some racial groupings more severely impacted than others?

Characteristics of the Incident:

Armed vs. Unarmed: What proportion of victims were armed? Is there a discernible difference between being armed or unarmed in terms of the chance of getting shot?
How many occurrences saw victims running away from the scene? Is there a connection between running away and how intense the experience was?
In what percentage of incidents were there police officers wearing body cameras? Does wearing body cams by officers affect the results?
What proportion of victims manifested indicators of mental illness? Are there any links between signs of mental illness and police shootings?

I carefully examined the statistics, and patterns started to appear. Will continue to delve deeper into the analysis, seeking a comprehensive understanding of the underlying factors.