If there was a variable in an xarray dataset with a time dimension with daily values over some multiyear time span
2017-01-01 ... 2018-12-31, then it is possible to group the data by month, or by the day of the year, using
.groupby("time.month") or .groupby("time.dayofyear")
Is there a way to efficiently group the data by the day of the month, for example if I wanted to calculate the mean value on the 21st of each month?
CodePudding user response:
See the xarray docs on the DateTimeAccessor helper object. For more info, you can also check out the xarray docs on Working with Time Series Data: Datetime Components, which in turn refers to the pandas docs on date/time components.
You're looking for day. Unfortunately, both pandas and xarray simply describe .dt.day as referring to "the days of the datetime" which isn't particularly helpful. But if you take a look at python's native datetime.Date.day definition, you'll see the more specific:
date.day
Between 1 and the number of days in the given month of the given year.
So, simply
da.groupby("time.day")
Should do the trick!
CodePudding user response:
I not sure, but maybe you can do like this:
import datetime
x = datetime.datetime.now()
day = x.strftime("%d")
month = x.strftime("%m")
year = x.strftime("%Y")
.groupby(month) or .groupby(year)
