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Police Shootings Data Analysis

At the end of summer 2022 I joined a Tableaux data visualization competition. I chose to analyze the raw data of police shootings from 2015-2022. The result I created was awarded 1st place, and this is what I made.

Project Date: August 2022

Project Timeline: 2 weeks

This data was collected from:

The commentary can be continued at the Washington Post

Created with

Process Breakdown


Understanding Data


The first step of understanding data is cleaning up the raw data. Using the data dictionary I put the coded terms into more human friendly data points. 


Generating Graphs


Once the data is readable, the next step is addressing what needs to be investigated and what type of visualization makes the most sense.


Merging into Dashboards


After each graph is created they need to be placed in groups on dashboards to become true infographics.


Results and Reflection

There's always something that could be added. While my work earned me 1st place, I found areas I would add to my report if given a second chance.

Gathering data

Lots of unfiltered code and non human friendly data to be cleaned up

The dataset was pulled from Being filled with raw data it was up to me to turn the abbreviations into complete words for the end product.

Raw graphs

Auto-generated colors and graph keys

The dataset was pulled from Being filled with raw data it was up to me to turn the abbreviations into complete words for the end product.

The victor

My end product merged my 7 graphs into 4 total dashboards that were used to illustrate different statistics about the recorded shootings.

The filters on the side are clickable too

As a reward for my stellar visualizations, I won some free merchandise and a gift card!

Judge panel comments

Judge A

“Great Work Kyle; I would love to see some of your thoughts written up in a textbox about your analysis of everything; and you could add a grammar/spell check  But all in all, THIS IS AWESOME!!”


The judges highlighted many of the areas I felt I could have taken a step further.


I spent a lot of space representing the data. Turning these points into a story could make more viewers care about the data. Data without a story is relevant but weak. 

Population as %

This data would be best represented through the use of proportions and percentages of the state population rather than raw population counts. As mentioned by one of the Judges.


While better than the other submissions I still feel like this array of visualizations is limited. Portions of the design still feel semi-professional rather than publishable.

Time extension

Many of these shortcomings are a result of this being made in 2 weeks. The best thing I could be given to make better work would be a larger heads up and overall time table.

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