issues: 646716560

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
646716560 MDU6SXNzdWU2NDY3MTY1NjA= 4186 to_xarray() result is incorrect when one of multi-index levels is not sorted 67515585 closed 0     15 2020-06-27T16:58:29Z 2020-07-02T20:39:02Z 2020-07-02T20:39:02Z NONE      

What happened: to_xarray() sorts multi-index level values and returns result for the sorted values but it doesn't sort levels or expects levels to be sorted resulting in completely incorrect order of data for the displayed coordinates. ```python df: C1 C2 lev1 lev2
b foo 0 1 a foo 2 3

df.to_xarray(): <xarray.Dataset> Dimensions: (lev1: 2, lev2: 1) Coordinates: * lev1 (lev1) object 'b' 'a' * lev2 (lev2) object 'foo' Data variables: C1 (lev1, lev2) int64 2 0 C2 (lev1, lev2) int64 3 1 ```

What you expected to happen: Should account for the order of levels in the original index.

Minimal Complete Verifiable Example:

python import pandas as pd df = pd.concat( { 'b': pd.DataFrame([[0, 1]], index=['foo'], columns=['C1', 'C2']), 'a': pd.DataFrame([[2, 3]], index=['foo'], columns=['C1', 'C2']), } ).rename_axis(['lev1', 'lev2']) print('df:\n', df, '\n') print('df.to_xarray():\n', df.to_xarray(), '\n') print('df.index.levels[0]:\n', df.index.levels[0])

Anything else we need to know?:

Environment:

Output of <tt>xr.show_versions()</tt> INSTALLED VERSIONS ------------------ commit: None python: 3.8.2 | packaged by conda-forge | (default, Apr 24 2020, 08:20:52) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 5.4.7-100.fc30.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_GB.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.3 xarray: 0.15.1 pandas: 1.0.5 numpy: 1.19.0 scipy: 1.5.0 netCDF4: 1.5.3 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.1.3 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2.19.0 distributed: 2.19.0 matplotlib: 3.2.2 cartopy: None seaborn: 0.10.1 numbagg: installed setuptools: 46.3.0.post20200513 pip: 20.1 conda: None pytest: 5.4.3 IPython: 7.15.0 sphinx: None 
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