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Data Viz Project

This repo houses my attempt at the course Final Project from the Winter 2021 offering of EDLD 652: Data Visualization for Educational Data Science, offered through the University of Oregon's College of Education.

Peer Review - DF for JS

Fantastic work, Joe. This is an awesome project and a really nice way to leverage 5 years of data collection. It made me wish I had gotten my Garmin watch earlier; I see tons of possibilities in tracking running data! Honestly - appreciate the inspiration.

Areas of Strength

  1. You have +many ideas for visualizations and they're all awesome in different ways. As you were playing with the strava package features (e.g., plot_map(), plot_calendar()), you were able to produce some pretty incredible figures with a single line of code.
  2. You're effectively able to take the same data, represent it differently, and tell a different story (or, perhaps, answer a different question for the viewer). Your first viz is great, and I was left wondering if the apparent increase in activity over time was more to do with long bike rides, or more to do with increased amount of days where you recorded an activity. Then, the next viz with the plot_calendar() answered that question perfectly!
  3. The searchable table is a really nice feature to follow up the visuals. It allows a data analyst to quickly ask questions of the dataset you've visualized, if they have any lingering questions. Nice!

Point of Learning

I certainly learned a ton about the Strava package. As we spoke about offline, there are a few different user-created R packages that are helpful to sort, package, and visualize your Strava data. I learned a ton about that community, some of the coding you can wrap around their functions, and power/limitations using their functions.

Improvements

I made small improvements on each of your first three visualizations in-line code. All small points. Mostly aesthetics, a touch of tidying, and a comment on sticking points with the Strava package. Well, at least, it was a sticking point for me. You may have more luck!

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