I wanted to see what stories this data had to tell. I was interested in breaking the data down by ethnicity, and I was able to do that by connecting the records to ethnicity through zip code, and what I found was suprising.

What it does

This is a descriptive analysis of a dataset detailing bail information for multiple cases in different zip codes, connected with demographic information based on zip code.

How I built it

I used Tableau to make the visualizations. To make the date/time ones, I just had to make groups within the original datasets. I then made a new spreadsheet in Excel compiling ethnicity data based on zip code. Then I connected that spreadsheet into Tableau and made the final visualizations. I exported each visualization separately, then brought them into Piktochart and added captions/titles to create the final infographic.

Challenges I ran into

To connect the zip codes to ethnicity data, I had to manually create a spreadsheet compiling ethnicity data from each page for each zip code from the Statistical Atlas, that was not very fun.

Accomplishments that I'm proud of

I'm proud of the end result and the story that it told. I also am proud what I got some concrete conclusions that are impactful.

What I learned

I learned that sometimes if you can't find a specific dataset to meet your needs, you can make your own. I also learned that sometimes the specific direction of your data depends on what the organization wants/needs, and I'm not sure which of my final visualizations is better for this purpose.

What's next for Bail Analysis

I would love to find a better way to analyze the data based on race/ethnicity. Zip code was okay, but overall not the most accurate measure.

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