issue_comments

@shoyer That did it. Under pandas 0.22, the DataArrays in aligned are all NaNs. I updated to pandas 0.23, and the non-NaN values were there as expected. To double-check, I downgraded to 0.22 again and got all NaNs again.

I found a way to reproduce the error. One of the MuliIndex levels on the DataArrays has NaNs in it. If I remove that level, the correct values appear in the result. Should the presence of that MultiIndex level cause this behavior?

``` import string import numpy as np import xarray as xr

dims = ("x", "y") shape = (10, 5) das = [] for j in (0, 1): data = np.full(shape, np.nan, dtype="float64") for i in range(shape[0]): data[i, i % shape[1]] = float(i) coords_d = { "ints": ("x", range(jshape[0], (j+1)shape[0])), "nans": ("x", np.array([np.nan] * shape[0], dtype="float64")), "lower": ("y", list(string.ascii_lowercase[:shape[1]])) } da = xr.DataArray(data=data, dims=dims, coords=coords_d) da.set_index(append=True, inplace=True, x=["ints", "nans"], y=["lower"]) das.append(da) nonzeros_raw = [np.nonzero(~np.isnan(da)) for da in das] print("nonzeros_raw: ") print(nonzeros_raw) aligned = xr.align(*das, join="outer") nonzeros_aligned = [np.nonzero(~np.isnan(da)) for da in aligned] print("nonzeros_aligned: ") print(nonzeros_aligned) assert nonzeros_raw[0].shape == nonzeros_aligned[0].shape ```

This is what I would expect to see returned by align():

(<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) object 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) object nan nan nan nan nan nan nan nan nan nan nan nan nan ... * y (y) object 'a' 'b' 'c' 'd' 'e')

I see something very similar, but with the nans level removed, if I do this:
xr.align(*[da.reset_index("nans", drop=True) for da in das], join="outer")

For clarity, here are the prints of the arrays before and after alignment:

Before alignment:
[<xarray.DataArray (x: 10, 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.]]) Coordinates: * x (x) MultiIndex - ints (x) int64 0 1 2 3 4 5 6 7 8 9 - nans (x) float64 nan nan nan nan nan nan nan nan nan nan * y (y) object 'a' 'b' 'c' 'd' 'e', <xarray.DataArray (x: 10, 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.]]) Coordinates: * x (x) MultiIndex - ints (x) int64 10 11 12 13 14 15 16 17 18 19 - nans (x) float64 nan nan nan nan nan nan nan nan nan nan * y (y) object 'a' 'b' 'c' 'd' 'e']

After alignment:
(<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], [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) object 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], [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) object nan nan nan nan nan nan nan nan nan nan nan nan nan ... * y (y) object 'a' 'b' 'c' 'd' 'e')

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. Perhaps I am misinterpreting the behavior of join="outer".