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  • tqfjo · 2 ✖

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  • Stack + to_array before to_xarray is much faster that a simple to_xarray 2

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
586552823 https://github.com/pydata/xarray/issues/2459#issuecomment-586552823 https://api.github.com/repos/pydata/xarray/issues/2459 MDEyOklzc3VlQ29tbWVudDU4NjU1MjgyMw== tqfjo 40251676 2020-02-15T04:31:54Z 2020-02-15T04:31:54Z NONE

@crusaderky Thanks for the pointer to xarray.DataArray(df) -- that makes my life a ton easier.


That said, if it helps anyone to know, I did just want a DataArray, but figured there was no alternative to first running the rather singular to_xarray. I also still find the runtime surprising, though I know nothing about xarray's internals.

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  Stack + to_array before to_xarray is much faster that a simple to_xarray 365973662
586066908 https://github.com/pydata/xarray/issues/2459#issuecomment-586066908 https://api.github.com/repos/pydata/xarray/issues/2459 MDEyOklzc3VlQ29tbWVudDU4NjA2NjkwOA== tqfjo 40251676 2020-02-14T02:25:25Z 2020-02-14T02:25:25Z NONE

I've run into this twice. This time I'm seeing a difference of very roughly 100x or more just using a transpose -- I can't test or time it properly right now, but this is what it looks like:

``` ipdb> df x a b ... c d y 0 0 ... 7 7 z ...
0 0.000000 0.0 ... 0.0 0.0 1 -0.000416 0.0 ... 0.0 0.0

[2 rows x 2932 columns] ipdb> df.to_xarray()

ipdb> df.T.to_xarray()

<Finishes instantly>

```

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  Stack + to_array before to_xarray is much faster that a simple to_xarray 365973662

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