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  • align() outer join returns DataArrays that are all NaNs · 5 ✖

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397085835 https://github.com/pydata/xarray/issues/2215#issuecomment-397085835 https://api.github.com/repos/pydata/xarray/issues/2215 MDEyOklzc3VlQ29tbWVudDM5NzA4NTgzNQ== shoyer 1217238 2018-06-13T21:02:44Z 2018-06-13T21:02:44Z MEMBER

OK, great. I'm going to close this then, and simply recommend that anyone encounter this issue try upgrading pandas.

 
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   align() outer join returns DataArrays that are all NaNs 329438885
394911109 https://github.com/pydata/xarray/issues/2215#issuecomment-394911109 https://api.github.com/repos/pydata/xarray/issues/2215 MDEyOklzc3VlQ29tbWVudDM5NDkxMTEwOQ== shoyer 1217238 2018-06-06T01:30:51Z 2018-06-06T01:30:51Z MEMBER

This what I see when printing aligned from your example: In [26]: aligned Out[26]: (<xarray.DataArray (x: 20, y: 5)> array([[ 0., nan, nan, nan, nan], [nan, 1., nan, nan, nan], [nan, nan, 2., nan, nan], [nan, nan, nan, 3., nan], [nan, nan, nan, nan, 4.], [ 5., nan, nan, nan, nan], [nan, 6., nan, nan, nan], [nan, nan, 7., nan, nan], [nan, nan, nan, 8., nan], [nan, nan, nan, nan, 9.], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan]]) Coordinates: * x (x) MultiIndex - ints (x) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 - nans (x) float64 nan nan nan nan nan nan nan nan nan nan nan nan nan ... * y (y) object 'a' 'b' 'c' 'd' 'e', <xarray.DataArray (x: 20, y: 5)> array([[nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [nan, nan, nan, nan, nan], [ 0., nan, nan, nan, nan], [nan, 1., nan, nan, nan], [nan, nan, 2., nan, nan], [nan, nan, nan, 3., nan], [nan, nan, nan, nan, 4.], [ 5., nan, nan, nan, nan], [nan, 6., nan, nan, nan], [nan, nan, 7., nan, nan], [nan, nan, nan, 8., nan], [nan, nan, nan, nan, 9.]]) Coordinates: * x (x) MultiIndex - ints (x) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 - nans (x) float64 nan nan nan nan nan nan nan nan nan nan nan nan nan ... * y (y) object 'a' 'b' 'c' 'd' 'e')

The only material difference I can see in our environments is that I'm running pandas 0.23 and you're running pandas 0.22. Can you try updating pandas and see if that fixes the issue?

 
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   align() outer join returns DataArrays that are all NaNs 329438885
394765439 https://github.com/pydata/xarray/issues/2215#issuecomment-394765439 https://api.github.com/repos/pydata/xarray/issues/2215 MDEyOklzc3VlQ29tbWVudDM5NDc2NTQzOQ== shoyer 1217238 2018-06-05T16:01:04Z 2018-06-05T16:01:04Z MEMBER

Since the align is an outer join, I would expect all the non-NaN values in the original DataArrays to also appear in the aligned DataArrays.

Sorry, I'm not quite following -- can we please give a specific example of which output from your example looks wrong, and print how it should look instead?

 
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   align() outer join returns DataArrays that are all NaNs 329438885
394761483 https://github.com/pydata/xarray/issues/2215#issuecomment-394761483 https://api.github.com/repos/pydata/xarray/issues/2215 MDEyOklzc3VlQ29tbWVudDM5NDc2MTQ4Mw== shoyer 1217238 2018-06-05T15:50:04Z 2018-06-05T15:50:04Z MEMBER

Thanks for the example. Can you please identify exactly which behavior you find surprising, and what you think the result should be?

 
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   align() outer join returns DataArrays that are all NaNs 329438885
394753520 https://github.com/pydata/xarray/issues/2215#issuecomment-394753520 https://api.github.com/repos/pydata/xarray/issues/2215 MDEyOklzc3VlQ29tbWVudDM5NDc1MzUyMA== shoyer 1217238 2018-06-05T15:28:45Z 2018-06-05T15:28:45Z MEMBER

Are you sure the indexes along the aligned dimensions match exactly? Small differences in floats are the most common source of this issue.

Try using second.reindex_like(first, method='nearest') instead of xarray.align(first, second).

 
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   align() outer join returns DataArrays that are all NaNs 329438885

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