Previously, my use of election data was limited to viewing turnout and showing votes for each candidate showing which recieved more votes. This year I used Python & Pandas to find some interesting facts hidden within the primary election data. Things like, which endorsed candidate lost their election, or if mail-in votes effect the outcome from the ballot box on election day.

With the COVID-19 pandemic mail-in voting has seen a huge bump as people are less likely to go to the polls. This post will take A look into the scale of mail-in voting for the 2020 primary compared to previous elections.

Last year I attempted to make a live election graph in Tableau. However, Tableau Public only allows data to automatically update once every 24 hours. Clearly... that didn't work out well, so this year I decided to try again and create my first Python web app using Flask, Bootstrap and AWS.

Using previous election results data from Rhode Island's Board of Elections since 2010, I normalized the data and removed multi-vote races using Python to find the 5 closest single-vote elections for every primary/general each year. I found it a bit surprising how many elections were decided by fewer then 10 votes between the top 2 candidates.

I found it a pain to find out how my state rep voted on a bill. The current process requires you to know the specific day the bill was voted on then scroll through all the votes that day to find the exact bill your looking for and thats if you know the bill number. This combines information from the bill status details to allow you to search for bills by category while also showing you floor votes.

A wordcloud generated from Gina Raimondo's State of the State address for 2020. The wordcloud is the top 250 most common words with Rhode, Island and stopwords removed. All words are converted into lowercase with punctuation and special characters removed along with plurals normalized.