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An analysis and visualization of the NYC Marathon's 2016 run data.
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README.md

Visualing NYC Marathon 2016 Strava Data

Summary

I’ve been an enthusiastic (if slow) runner since I was in high school. If there’s one thing we runners love, its our data. I have the privledge of being chosen for the New York City Marathon's 2016 lottery last year, so my husband and I took a trip to NYC last November. Going to NYC was a blast, and I finished the race 4:31 - that is, 4 hours and 31 minutes. A PR for me!

When you're training for a marathon, you spend far too much time looking at training plans, reading about the 80-20 rule, negative splits, nutrition, pace zones - and just as importantly, finding out what every other runner is up to! I was curious how my fellow racers trained and performed, and so, inspired by this excellent post by Colin Eberhart, I decided to try my first attempt at web scraping and analyze our race data.

Technical Stack

  • HTML
  • CSS
  • Javascript & jQuery
  • Node (data scraper)
  • Heroku & HerokuDB (deployment and database)
  • Chart.js

Main Highlights

Comparing finishing times

Compares the finishing times of all NYC finishers against their gender, age, nationality and longest training run (assuming 17 weeks prior to the marathon was their training cycle).

Breaking down runner demographics

Compares the finishing times of all NYC finishers against their gender, age, nationality and longest training run (assuming 17 weeks prior to the marathon was their training cycle).

Favorite Challenges

  • Web Scraping - This was my first time grabbing data and scraping for it. It was really fun to figure out how.
  • Writing the functions needed to render complex charts for Chart.js

Special Thanks

About the Developer

Keeley Hammond is a software developer living in Portland, OR. She really likes to run, and likes looking through her Garmin and Strava data even more.

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