I Did My First Small Data Analysis Project Last Night: I'm Hooked

Source: Dev.to

Introduction

I recently got a smartwatch and thought it would be useful to analyze its data as part of my coding learning path, which includes data analysis. Using my own data seemed like the perfect starting point.

Data Collection

• I have been using Google Fit on my Android phone since 2017 as a step/activity tracker.
• I set up Google Takeout to back up my data to Google Drive every two months (the maximum frequency for that dataset).
• The first backup arrived as two zip files.

I focused on a single CSV file: Daily Activity, which contains one line per day. The file has 2,084 rows, representing nine years of daily step data.

Initial Analysis

I wanted to start analyzing the data right away, so I asked a friendly AI for a step‑by‑step guide to running Python in the terminal for data analysis. I kept the process simple:

1. Removed columns that were empty or not relevant (e.g., estimated calorie counts).
2. Concentrated on step counts.
3. Calculated low, median, and high daily step counts, broken down by year.

Findings

• The median daily step count dropped by about half in 2024, the year I broke my leg and spent three months in bed followed by three months relearning how to walk.
• I have not yet returned to my pre‑2024 baseline, but even while walking only indoors for the past month (due to cold weather), the median daily step count is trending upward.

These simple analyses give me a data‑backed record of the impact of my injury and a foundation for setting future step‑count goals.

Next Steps

• Build a visual dashboard that:
  • Displays medians and other statistics.
  • Allows projections based on daily step goals.
• Add additional activities (bike rides, meditation) to the dashboard later.
• Incorporate new data (approximately every two months) to compare projections with actual results and adjust future goals.
• Publish the project on Git (with anonymized data) to document my progress as I learn to code and create useful, personal projects.