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1068703649 https://github.com/pydata/xarray/pull/6353#issuecomment-1068703649 https://api.github.com/repos/pydata/xarray/issues/6353 IC_kwDOAMm_X84_sx-h dcherian 2448579 2022-03-16T03:52:49Z 2022-03-16T03:52:49Z MEMBER

@mathause I suspect coarsen.construct is faster because it's a simple reshape (ignoring the copies associated with handling the boundary condition): https://github.com/pydata/xarray/blob/95bb9ae4233c16639682a532c14b26a3ea2728f3/xarray/core/variable.py#L2373

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 (https://github.com/pydata/xarray/issues/1790)

 
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   Add new tutorial video 1167962844
1068371598 https://github.com/pydata/xarray/pull/6353#issuecomment-1068371598 https://api.github.com/repos/pydata/xarray/issues/6353 IC_kwDOAMm_X84_rg6O max-sixty 5635139 2022-03-15T19:19:33Z 2022-03-15T19:19:33Z MEMBER

Very good video @dcherian !

 
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   Add new tutorial video 1167962844
1068305154 https://github.com/pydata/xarray/pull/6353#issuecomment-1068305154 https://api.github.com/repos/pydata/xarray/issues/6353 IC_kwDOAMm_X84_rQsC mathause 10194086 2022-03-15T18:13:39Z 2022-03-15T18:13:39Z MEMBER

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.

```python 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")

```

 
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   Add new tutorial video 1167962844

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