How does the weather impact my walking distance?

Below is a graph of my steps compared to the average temperature, from January through May 2019.

Temperature is the line, and steps are the bars.



It all started with the realization that I could export data from my health app. If the data is there and I can mess with it, the temptation is too great not to do so. And if I can turn it into some interesting visuals, all the better.


What I found looking at the data

There is a correlation between the temperature and how far I walked.


During a few months in particular, the correlation was much stronger. Compare the R² in January to April, for instance. The R² should be somewhat representative of the proportion of variance in steps explained by the temperature.

So, in January, the temperature was much more predictive of my walking distance than in April. This makes sense - when temperatures had more fluctuation, my walking distance did as well.

It's interesting to look at the results of the models on a month-to-month basis. January's model makes sense, intuitively. I'd walk roughly 3x as much at 72°F as at -15°F. Compare that to March's model, which predicts that an 87°F dip in temperature from 72°F to -15°F would only cut down my walking distance by about 3,000 steps. I like walking, but not that much.

Unusual or unseasonable changes in weather led to outsized changes in walking distance. Essentially, a nice day in the midst of many cold ones motivated me to get outside more. The corollary: a cold day in the middle of nice ones meant less walking.


A few spots stood out...

So I dug deeper into what happened on those dates.

  • On Saturday, January 5th, I walked 21,027 steps, and it was an average temperature of 44°F. That's unseasonably warm. It was also the weekend, and I'd recently returned from holiday travel - which meant lots of time sitting in the car.
  • On Wednesday, January 30th, I only walked 2,447 steps - that's less than 12% of the distance I did on January 5th. Here's the thing - it was the middle of a polar vortex. The average temperature that day (without windchill) was -14°F. It was literally unsafe to be outside for more than a few moments. I did brave the cold to walk to a nearby gas station, and the sprint back felt like a near death experience.
  • Sunday, February 24th also was a low step day, with 4184 steps. The average temperature of 15°F. Not as cold as the polar vortex, but still oppressive to be outside.
  • Tuesday, March 26th was weirdly low in steps, with 4268 and a temperature of 43°F. No interesting explanation here - just a day without much walking and lots on the agenda.
  • Friday, April 19th was full of walking, with 23,474 steps. It was also beautiful, with a temperature of 52°F and a warm evening. It was Good Friday, so I had the day off of work, leaving plenty of time for activities.

But there is always more data to analyze!

How time of day affected my steps


1. My walk to work in the morning was when I logged quite a few steps - 1,138 on average between 8am and 9am.

2. Usually, I walk across my office's campus to eat lunch. On average, that journey between 11am and 12pm nets me 716 steps.


3. Between 4pm and 6pm I usually take about 2,633 steps. Why so many more than on my way to work, though? Well, I often run some errands or grab groceries on the way.

4. I usually work out in the 7-9pm range, and the steps to go do so average about 1,308.

How day of the week affected my steps

  • Saturdays had my highest number of steps on average, with Fridays in a close second. This makes sense - more free time, social activities, and reasons to be walking around.
  • It was interesting that Monday sprang ahead of Sunday, Tuesday, and Wednesday to me. But, I almost always end up walking to work out on Mondays, and I have a hunch that my energy levels are generally higher than midweek.
  • To that end, it seems like I have the lowest energy levels on Wednesday. Will this trend continues in the future? All spring, I had a Tuesday evening class that often left me feeling drained on Wednesdays.

How to to analyze your own step patterns

If this has piqued your interest, none of this is too difficult to do. You need your phone, a laptop, and a tool like Tableau, PowerBI, or Excel.

  • First, get QS Access for iPhone. If you're on Android, these instructions may help.
  • Open QS Access, and select the toggle for "Steps" shown below. You can choose to export measurements on an hourly, or daily basis. I did both for the purposes of this analysis.
  • From here, it's gonna be fairly dependent on what tools you have at your disposal. I have Tableau, so I used that to do most of my initial analysis. If you have a .edu email address, you can get a year for free.
  • I set up tables with:
    • Days on the X axis and sum (step count) on the Y
    • Weekday on the X axis and avg (step count) on the Y
    • Hour on the X axis and avg (step count) on the Y
  • Then, to add the temperature data, I used the NOAA's Climate Data Online site.I grabbed the "Local climatology data" for my location, and then pulled the dry bulb temperature for analysis.
  • I exported what I created from Tableau as .pngs, and then made it look a little nicer using Illustrator. An aside, but Tableau badly needs the option to export vector graphics.