___________________
_________
_____
_________
_________
2015-06-24 00:00:00
Wednesday
2141
1141
1000
2015-06-25 00:00:00
Thursday
2106
1123
983
2015-06-26 00:00:00
Friday
1748
970
778
2015-06-27 00:00:00
Saturday
695
346
349
2015-06-28 00:00:00
Sunday
153
83
70
2015-06-29 00:00:00
Monday
1841
978
863
2015-06-30 00:00:00
Tuesday
2170
1145
1025
2015-07-01 00:00:00
Wednesday
997
544
453
Synchronize Bicycle Count and Weather Data
Examine the effect of weather on cycling behavior by comparing the bicycle count with weather data.
Load the weather timetable which includes historical weather data from Boston, MA including storm
events.
load BostonWeatherData
head(weatherData)
ans=8×3 timetable
Time
TemperatureF
Humidity
Events
___________
____________
________
____________
01-Jul-2015
72
78
Thunderstorm
02-Jul-2015
72
60
None
03-Jul-2015
70
56
None
04-Jul-2015
67
75
None
05-Jul-2015
72
67
None
06-Jul-2015
74
69
None
07-Jul-2015
75
77
Rain
08-Jul-2015
79
68
Rain
To summarize the times and variables in the timetable, use the summary function.
summary(weatherData)
RowTimes:
Time: 383x1 datetime
Values:
Min
01-Jul-2015
Median
08-Jan-2016
Max
17-Jul-2016
TimeStep
24:00:00
Variables:
TemperatureF: 383x1 double
Values:
Min
2
Median
55
Max
85
Preprocess and Explore Time-stamped Data Using timetable
10-63