issue_comments: 384707323

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https://github.com/pydata/xarray/issues/2063#issuecomment-384707323 https://api.github.com/repos/pydata/xarray/issues/2063 384707323 MDEyOklzc3VlQ29tbWVudDM4NDcwNzMyMw== 1217238 2018-04-26T16:35:24Z 2018-04-26T18:21:40Z MEMBER

I think the following script should reproduce the issue and identify which library is the source of the issue: ``` import dask.array as da import numpy as np import pandas as pd import bottleneck

rng = np.random.RandomState(0) x = np.concatenate([rng.randn(16, 8).astype(np.float32), np.nan * np.zeros((4, 8)).astype(np.float32)])

print('numpy', np.nanvar(x)) print('dask', da.nanvar(da.from_array(x, 4)).compute()) print('pandas', pd.Series(x.ravel()).var(ddof=0)) print('bottleneck', bottleneck.nanvar(x)) ```

On my laptop, this prints: numpy 1.0792575 dask 1.0792574 pandas 1.0792568922042847 bottleneck 1.0792568922042847

 
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