Create visualizations for cummalitive booking habits

[Peter-Lam]

As climbing gyms begin to remove capacity limits and reservation systems, create some new and update existing visualizations to give climbers a reference point when going to gyms in the future.

What already exists:

• Popularity by gym & time slot
• Relative to the current capacity
• Booking by weather

What could be helpful for the future:

• Popularity by gym & regular time intervals (every hour)
• Add a field to data points to show the % full based on the capacity of that time
  • For example: 50 bookings in March when the capacity was 50 ppl means 100% capacity, where as now it's like 50%
• Update jupyter graphs for weather trends
  • How do other variables influence how busy a gym is (weather, time of the year, events, lockdown)
• Bonus: Highlight and graph the differences in popularity based on lockdown rules
  • For example: 1st return from lockdown, 2nd ....
  • This would be more accurate if curious on data based on the limit but not 100% needed

[Peter-Lam]

Popularity by gym capacity has been updated.

Choosing not to implement:

Update jupyter graphs for weather trends

    How do other variables influence how busy a gym is (weather, time of the year, events, lockdown)

Bonus: Highlight and graph the differences in popularity based on lockdown rules

    For example: 1st return from lockdown, 2nd ....
    This would be more accurate if curious on data based on the limit but not 100% needed