issue_comments: 333275551

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https://github.com/pydata/xarray/pull/1597#issuecomment-333275551 https://api.github.com/repos/pydata/xarray/issues/1597 333275551 MDEyOklzc3VlQ29tbWVudDMzMzI3NTU1MQ== 1386642 2017-09-30T02:20:41Z 2017-09-30T02:21:14Z CONTRIBUTOR

Okay. I just changed the names of the methods and wrote a test case for the problem with the dtype of the stacked dimensions not being preserved by to_stacked_array.

At the moment, I am filling in the missing dimensions with None, so the resulting index has dtype object'. This is then concatenated with the bona fide indices of the variables which are not missing this index, so the index as a whole is cast to the lowest common denominator, which is object. Unfortunately we can't just put Nan in because, NaN is a floating point number thing, so I don't think all numpy dtypes have the equivalent of NaN. @shoyer Do you have any thoughts about how to resolve this?

 
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