feature: stats for high-water-mark, busiest-time, and queue-like vs. stack-like

[tevpg]

more stats! Fun ones! Possible keyword "z" [zany stats?]

see mockups in screen mockups text file.

reports on:

• daily high water mark (most bikes on hand at any given time)
• busiest times of day
• both of above as histograms
• degree to which bike activity was queue-like vs stack-like (Todd is probably the only person who cares about this one)

[tevpg]

Queue-like or Stack-like?

Been thinking about how to measure this. I think something like: a stay is queue-like to the degree that the stays end after stays that began earlier than it. And vice versa. See diagram with logic

It could be a bit expensive because it is semi-cartesian (each stay is compared with ~1/2 of all other stays) but because only ~100 or so bikes, may not be a problem

The data structure this will need is a list of stays, each with its start time and end time (and for convenience, duration). Times would be better as num, to help with charting (see next paragraph).

This data structure also lends itself well to making charts like this to visualize bike visits.

[tevpg]

Combine these into summary statistics report. Ties to issue #11

Proposed format (to keep compact on that small screen):

Summary statistics at HH:MM (2 bike(s) still at valet):

Bike check-ins:      Stays:
  Total:   107         < 1.5h:      26
  AM:       49         1.5-5.0h:    51
  PM:       58         >5.0h:       30
  Regular:  64         Max:      11:13 [tag(s) wb3]
  Oversize: 43         Min:      00:01 [tag(s) wc10, we13, we12]
                       Median:   02:33
                       Mode:     02:00 (by 2 bikes, 30 minute blocks)

Most bikes on hand at valet:
                Regular  Oversize  Total  Time
Most regular:      60       20       80    10:15,14:30
Most oversize:     42       31       73    13:11
Most combined:     55       29       84    13:55

Most bike transactions:
            CheckedIn  Out   Total
09:30-10:00      45      0      45
16:00-16:30       5     39      44
08:00-08:30      37      0      37

Stays were 47% queue-like, 53% stack-like

[tevpg]

Combined this issue into #11, marking this one as duplicate