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  • khaeru · 1 ✖

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  • concat() fails when args have sparse.COO data and different fill values · 1 ✖

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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
541160571 https://github.com/pydata/xarray/issues/3381#issuecomment-541160571 https://api.github.com/repos/pydata/xarray/issues/3381 MDEyOklzc3VlQ29tbWVudDU0MTE2MDU3MQ== khaeru 1634164 2019-10-11T17:49:09Z 2019-10-11T17:49:09Z NONE

Thanks both for the comments. I understand sparse's behaviour; to clarify, the bug (IMO) is that xarray doesn't handle this for the user. To condense my example: ```python

Same as above to ---

import numpy as np import pandas as pd import xarray as xr

foo = [f'foo{i}' for i in range(6)] bar = [f'bar{i}' for i in range(6)] raw = np.random.rand(len(foo) // 2, len(bar))

b_series = pd.DataFrame(raw, index=foo[3:], columns=bar) \ .stack() \ .rename_axis(index=['foo', 'bar'])

---

b = xr.DataArray.from_series(b_series, sparse=True) c = b.sum(dim='foo').expand_dims({'foo': ['total']}) d = xr.concat([b, c], dim='foo') ```

This succeeds when sparse=False and fails when sparse=True. - Shouldn't it succeed automatically? I feel like it should. - If it does, what should be the fill value on d? I'm not clear what the intended behaviour is.

I haven't touched xarray internals before, but if time allows I will try to add some tests.

 
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   concat() fails when args have sparse.COO data and different fill values 503711327

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