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  • hottwaj · 1 ✖

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  • Support multi-dimensional grouped operations and group_over · 1 ✖

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  • NONE · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
265462343 https://github.com/pydata/xarray/issues/324#issuecomment-265462343 https://api.github.com/repos/pydata/xarray/issues/324 MDEyOklzc3VlQ29tbWVudDI2NTQ2MjM0Mw== hottwaj 5629061 2016-12-07T14:35:01Z 2016-12-07T14:35:01Z NONE

In case it is of interest to anyone, the snippet below is a temporary and quite dirty solution I've used to do a multi-dimensional groupby...

It runs nested groupby-apply operations over each given dimension until no further grouping needs to be done, then applies the given function "apply_fn"

def nested_groupby_apply(dataarray, groupby, apply_fn): if len(groupby) == 1: return dataarray.groupby(groupby[0]).apply(apply_fn) else: return dataarray.groupby(groupby[0]).apply(nested_groupby_apply, groupby = groupby[1:], apply_fn = apply_fn)

Obviously performance can potentially be quite poor. Passing the dimensions to group over in order of increasing length will reduce your cost a little.

 
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   Support multi-dimensional grouped operations and group_over 58117200

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