I got a smart watch the other day. And it occurred to me it would be useful to have access to that data as I progress along my coding learning path, which includes learning some data analysis.
What better data to analyze than my own?
I'd been using Google Fit on my android phones since 2017 as a step/activity tracker, so I dug into the Google Takeout options and set up a backup of my data to be sent to my Drive every two months - which was the max frequency for that dataset.
The first data backup was deposited that day. Two zip drives worth.
I decided to focus on just one file - a csv of Daily Activity, each day's activity data on a single line. 2084 lines total. 9 years worth of daily step data.
Now, I didn't want to wait until I was actually in the data analytics sections of the learning pathways I'm following, so I hopped over to a friendly AI and asked it to walk me through running python in terminal for data analysis. Step-by-step. Not do it for me, tell me what to do, and help me figure out what I did wrong when the code doesn't work.
Started super basic.
Strip out the columns that have no data or have data that's not really relevant - like the calorie tracking was an estimate based on activity data.
I focused on step counts. Getting low, median, and high daily step counts. Looked at them yearly, and saw the unsurprising drop of the median step count by half in 2024 - that's the year I broke my leg and spent three months in bed and three months relearning how to walk. I learned I'm still not back at my pre-2024 baseline, but even though I've only been walking indoors the last month because it's been so cold, my median daily average step count IS still trending upwards.
Like, this is super simple data analytics. Really basic stuff on a personal dataset that applies only to me.
But it's also very useful for me.
I have a data-backed record of the impact of my injury.
And I can create a data-backed plan for increasing my step count and getting back to, then surpassing, that pre-2024 baseline.
And because it's very personal, it makes learning the coding part of it easier.
Next up, figuring out how to make a nice visual dashboard that takes that old data, spits out the medians, and allows me to make projections based on daily step goals (I'll add other activities later - I've got a bunch of data on bike rides and meditation as well). Once I get new data, in about two months, I can then add that to the data in the dashboard and compare those projections and the actual data to make adjustments to future goals.
I'll probably be dropping it all in git (data anonymized, of course), not because I think it's anything groundbreaking, but because I want to document my progress as I go learning how to code and creating projects that are genuinely useful and fun to me.
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