• Each student will submit the activity individually to Canvas, but students are encouraged to help one another complete the work
• Complete the Bicycle Sharing Activity found in the DataComputing eBook
  • make sure you carefully follow the instructions and mirror the code in the activity as you work
  • every task in the activity should have narrative text describing your observations; most steps also require code chunks and corresponding output.
  • you should make commits in GitHub as you complete the activity
• submit the completed R Notebook as HTML to Canvas before deadline

The data are slightly larger for this activity when compared to most of the others. You'll have more than 650,000 rows of data and several variables, so it's a good idea to use the "small" subset of the data to do your programming and then switch to the large data file at the very end. Also, you'll have to be patient with joins as R is working with larger data sets (though it really shouldn't take more than 2 minutes).

Assignment is worth a total of 10 points.

• Turn in HTML with embedded .Rmd file
• [2 points] Side-by-side boxplots of rental durations (How Long section)
• [4 points total] A.2 plots (When are bikes used section)
  • [0.5 point] density plot: day of the year 91 to 365)
  • [0.5 point] density plot: day of the week (Sunday to Saturday; numeric is fine)
  • [0.5 point] density plot: hour of the day (0 to 24)
  • [0.5 point] density plot: minute in the hour (0 to 60)
  • [1 points] Plot rental frequency by hour, weekday, & client type
  • [1 points] Plot rental density by hour, weekday, & client type
• [2 points] Distance plots (How Far? section)
  • [1 point] density plot of station to station distances
  • [1 point] density plot of ride distances
• [2 points] Mapping the stations leaflet (interactive map)
• [EXTRA CREDIT: 2 pts] Long Distance Stations challenge task