Need some inspo for your next data passion project? Look no further.
Do you want your resume to stand out from the crowd?
Do you want a compelling project to talk about in your next job interview?
Do you have tons of time on your hands?
If so, you should start a personal data project — a “passion project.”
A “passion project” is focused on something that is already interesting to you, so you may not mind spending extra time doing research.
Read on for some of my favorite data analysis passion projects! Get ready to be inspired.
Looking for passion project ideas?
You can analyze…LEGOs.
Stacy Giroux analyzed her kids’ personal LEGO collection over twenty years, looking at the most popular themes (Star Wars is their favorite!) and how many bricks are in their sets (older kids enjoy more complex sets.)
You can analyze…animal shelter intakes.
Jessica Mehrens examined intake and outcome data between 2013–2023 from the PAWsome Animal Shelter, looking at the most common types of animals and breeds at the shelter, how long animals normally stay at the shelter, how many animals get adopted, and more.
You can analyze…donuts.
Evan Wimpey analyzed the quality of different donut brands over time, comparing Britts Donut Shop in Carolina Beach to Krispy Kreme (yeast donuts) and Dunkin’ (cake donuts.)
You can analyze…Halloween candy.
Eric Sims analyzed FiveThirtyEight’s Ultimate Halloween Candy Power Ranking dataset, which showed the results of an online voting challenge for 85 different candies.
His biggest takeaway? “If you want to make everyone happy, chocolate and peanut butter are the undisputed winning combination. All Reese’s products were winners.”
You can analyze…your sleeping patterns.
Thais Cooke analyzed her sleep patterns for three months to find out how sleep disruptions impacted her the next day and the main factors that caused sleep disruption.
She found that sleep disruption had a big impact on her fatigue the next day and that the disruptions were usually caused by noise or caregiving.
You can analyze…your weightlifting goals.
Kelly Adams analyzed her weightlifting data in 5 main barbell lifts over three months. The five lifts were the deadlift, bench press, overhead press, row, and squat.
You can analyze…Mozart.
Chris Brelsford analyzed Mozart’s output by year and his choice of key/time signatures. He found that the year Mozart married was his second most productive year in terms of works released.
You can analyze…the Corleone family.
Tré R. used network science and natural language processing (NLP) to analyze the social structures of The Godfather.
Final Thoughts
Passion projects are a great way to stand out from the crowd, delve into a subject you’re interested in, and practice different systems. It shows employers that you can work with unique data and ask useful questions.
Bonus: If you really want to impress, start with messy data and include descriptions of how you cleaned it up (for example, cite the Python code you used.) Cleaning data is a central part of a data analyst’s role.
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Further Reading:
Maven Analytics: “Why You Should Include Passion Projects in Your Data Portfolio” by Stacy Giroux
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