issues: 121336727

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
121336727 MDU6SXNzdWUxMjEzMzY3Mjc= 673 resampling with missing data 12929592 closed 0     2 2015-12-09T20:55:09Z 2015-12-13T00:27:43Z 2015-12-13T00:27:24Z NONE      

I regularly use resample and groupby to analyse a 40 year hourly 2D dataset with no problems. However, a new dataset that I am working with is missing some leap year days and the output is wrong with what seems like months have been swapped around. Is this because the number of days in the month is used to divide to get the mean? So my actual question is - how is the mean taken when using groupby or resample, does it count the number hours or days in the dataset and how does it deal with missing data?

Some of the steps I follow:

Python ds=xray.open_mfdataset(filepath) dsvariable=ds[variable] resampledaily=(dsvariable.resample('D', dim='time', how='max')) resamplemonthly=(resampledaily.resample('1MS', dim='time', how='mean')) monthly_ts=resamplemonthly.groupby('time').mean()

 
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