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[dcherian]

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[mathause]

Nice! I did not know about coarsen(...).construct(...) - interesting. I usually use set_index for that - could be interesting to test which approach is faster.

def _to_seasonal(ds):

    year = ds.time.dt.year.data
    season = ds.time.dt.season.data

    # assign new coords
    ds = ds.assign_coords(year=("time", year), season=("time", season))

    # reshape the array to (..., "season", "year")
    return ds.set_index(time=("year", "season")).unstack("time")

[max-sixty]

Very good video @dcherian !

[dcherian]

@mathause I suspect coarsen.construct is faster because it's a simple reshape (ignoring the copies associated with handling the boundary condition):

xarray/xarray/core/variable.py

Line 2373 in 95bb9ae

return variable.data.reshape(shape), tuple(axes)

Unstacking allocates a new array and then assigns all values. It is definitely the more general solution though.

We should discuss this in the proposed cookbook (#1790)