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stepcount-analysis

step count analysis from apple health data.

this python script analysis step count features of me myself in Sweden (25/9 ~ 14/12/2016, 15 ~ 17/1/2017) and in China (23/5 ~ 24/9/2016, 15/12/2016 ~ 14/1/2017).

requirements

  • numpy
  • pandas
  • python 2.7

procedures

  • import data from my cell phone
  • extract data from xml to csv-friendly form
  • data cleanning. some meaningless data are dropped (thus effective steps are kept)
  • mean/var analysis.

what is effective steps?

steps per minutes (spm) which are between 80 and 150. why?

  • less than 80 -> (random wandering at home) | (slow walks)
  • greater than 150 -> overlapping data (i cannot achieve 150spm lol)

results

  • spm in Sweden are 4% higher than what in China. (significance test passed)
  • (effective) steps per day in Sweden are 10% less than what in China. (significance test not passed)

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step count analysis from apple health data.

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