From 033f67d1cd3cc0e429217089f0e87f461a66b963 Mon Sep 17 00:00:00 2001 From: Nathan LeClaire Date: Sat, 1 Sep 2018 12:13:28 -0700 Subject: [PATCH] =?UTF-8?q?Create=20Posts=20=E2=80=9Cvisualizing-fitness-p?= =?UTF-8?q?rogress-with-apple-health-golang-and-r-ggplot2=E2=80=9D?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...apple-health-golang-and-r-ggplot2.markdown | 28 +++++++++++++++++++ 1 file changed, 28 insertions(+) create mode 100644 content/post/visualizing-fitness-progress-with-apple-health-golang-and-r-ggplot2.markdown diff --git a/content/post/visualizing-fitness-progress-with-apple-health-golang-and-r-ggplot2.markdown b/content/post/visualizing-fitness-progress-with-apple-health-golang-and-r-ggplot2.markdown new file mode 100644 index 00000000..23229e03 --- /dev/null +++ b/content/post/visualizing-fitness-progress-with-apple-health-golang-and-r-ggplot2.markdown @@ -0,0 +1,28 @@ +--- +title: 'Visualizing Fitness Progress with Apple Health, Golang, and R (ggplot2)' +--- +> "A weak man is not as happy as that same man would be if he were strong." +> +> * Mark Rippetoe + +Lately I've been trying to be good about sticking to my workout plan (and eating strategy) so that I can become healthier, stronger, and harder to kill. It will be no surprise to anyone who has attempted the same that it's FUCKING HARD. Not only is compliance to the desired programming and macros difficult, but determining if your programming is actually working can be difficult too. For starters, are you actually following your programming? I mean, do you even know? Most people who are just eating as they think they should are actually whiffing their macros (and probably important micros too). I know I've had some rude wake up calls lately where it turned out what I thought my OK-just-not-perfect diet for my program was actually a bit on the fucked up side, lacking in vital things like carbs that I should have to keep me fueled well. + +Anyway, as for measuring progress in the case of compliance - _just_ looking in the mirror, while a good start, isn't quite sufficient - it's easy to get lost in the nebulous set of confounding variables. + +So, since I'm both a data nerd and a big believer in the "what gets measured, gets managed" philosophy, I've been tracking core metrics (such as mass, calorie count, squat weight) where possible. Though I've had some off periods with calorie tracking (can we just get a magic device that automatically records everything we eat and drink already?) and tracking my workout progression (despite falling prey to the ever popular [Fuckarounditis](https://leangains.com/fuckarounditis/) for a while). + +## Data Collection + +I have a "smart scale" at home which is connected via Bluetooth to my iPhone. The app is a proprietary + +However the default charts in both the proprietary app and in Apple Health don't really strike my fancy. They either make it difficult + +## Exporting Apple Health Data + +## Munging to CSV with Golang + +## Visualizing with ggplot2 + +![null](/static/images/mass_fat_lbm.png) + +## Trends and Conclusions