train-data-viz

Training data visualization & analysis through Python. A fun little tool for me to easily see and interpret the training I'm doing during quarantine, to make it less boring. Generates some fun stats to keep me motivated. #CircumnavigateTheGlobe

This is a work in progress. COMING SOON!

• more readable date formatting
• prettier & bigger graphs/chartss
• web app????????????????

Author: Elisa Luo [email protected]. Columbia University Division I Women's Rowing. Yeah Lions!

Library: used the pandas library. https://pandas.pydata.org/docs/index.html

Input: a .csv file with 4 columns: date, mode (bike, erg, run, lift), time_elapsed, and distance in KM. (metric, because we're not savages here. But perhaps will add a conversion option)

Features:

• automated calculation of adjusted distance, based on the following conversion factors:
  • erg x1
  • bike x0.5
  • run x1.25
• currently generates the following charts:
  • stacked bar graph, by date and time elapsed per mode
  • stacked bar graph, by date and distance per mode
  • stacked bar graph, by date and adjusted distance per mode
  • pie graph, by mode and time elapsed
  • pie graph, by mode and distance
  • pie graph, by mode and adjusted distance
• currently calcuates the following stats:
  • total time spent training in minutes, hours, and days
  • period of time the data spans (in days)
  • total distance travelled (in KM)
  • percentage of the way around the earth travelled
  • average amount of minutes spent training per day

Sample text output (with my real training data):

You spent a total of 4728 minutes training over a period of 34 days! That's 78.8 hours or 3.283333333333333 days!
You travelled a total of 1232.9 KM. That's 3.076481597005615% around the earth!
You averaged 139.05882352941177 minutes of training per day!

Sample charts output (with my real training data):

• bar.png
• pie1.png
• pie2.png

Sample data:

• train2.csv