How to divide timeseries data into seasonal variation

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Niraj Acharya
Niraj Acharya el 8 de Sept. de 2019
Respondida: Guillaume el 9 de Sept. de 2019
This is the first instant of my data.
DateTime Global_active_power Global_reactive_power Voltage Global_intensity Sub_metering_1 Sub_metering_2 Sub_metering_3
1/01/2007 0:00 2.58 0.136 241.97 10.6 0 0 0
I want to divide it into summe and winter data.
  2 comentarios
Guillaume
Guillaume el 8 de Sept. de 2019
What is your definition of summer and winter (when do they start and end)?
Niraj Acharya
Niraj Acharya el 8 de Sept. de 2019
Editada: Niraj Acharya el 8 de Sept. de 2019
June, July and August are summer while December, January and February are winter. I have list of date in this form:
DateTime
1/1/2007 0.00
1/2/2007 1.00
1/3/2007 1.10
........

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Respuestas (1)

Guillaume
Guillaume el 9 de Sept. de 2019
Note that if you're indeed using timeseries, you may be better off using timetables instead. They're slightly easier to use and are more powerful.
The following applies to timetables, I believe it's more or less the same syntax for timeseries.
While you can indeed split the data into winter and summer (and discard the rest):
summer = yourtimetable(ismember(month(yourtimetable.DateTime), 6:8), :); %6 to 8 is June, July, August
winter = yourtimetable(ismember(month(yourtimetable.DateTime), [1, 2, 12]), :); %1, 2, 12 is January, February, December
you may be better off adding a new variable named Season of type categorical:
yourtimetable.Season = discretize(mod(month(yourtimetable.DateTime), 12), 0:3:12, 'categorical', {'winter', 'spring', 'summer', 'autumn'}); %the mod is to bring december as first month
you can then do group calculation by season with e.g. groupsummary.

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