Gym Visit Analytics — 2024 Attendance Insights
In this self-directed project, I leveraged attendance data from my local gym to quantify my workout consistency and membership cost efficiency for 2024. I collected visit logs from the gym’s web portal and asked key questions:

• Was I consistent in making it to the gym?

• How many visits did I average per week?

• When during the day and week was I most active?

• Which membership pricing plan would have saved me the most money?

Using monthly and weekly breakdowns, I found that I visited the gym for 43 out of 52 weeks, averaged 3.64 visits per week, with a median and mode of 5 visits per week, and most often workouts occurred in the morning on Monday through Thursday. I also compared membership plans: a standard flat rate versus a variable rate based on visit count. For 2024, the variable rate would have saved ~$40, but I opted to stay with the standard rate for simplicity.

Skills and Technologies

• Data extraction and cleaning (attendance logs)

• Time-series and frequency analysis (visits by week, month, day, time of day)

• Cost-benefit comparison using membership pricing models

• Visualization of attendance patterns (heatmaps, bar charts)

• Translating fitness habits into analytics—combining personal health goals with technical insight

Outcome

This project demonstrates how personal habit data—here gym attendance—can be turned into actionable insights. By quantifying consistency, identifying patterns, and running cost analyses, I drew clear conclusions about my fitness behaviour and membership decisions. It also sparked ideas for deeper integration of wearable data and training analytics in future work.

See Blog Post – Gym Analytics: Insights from My 2024 Gym Visits