issue_comments: 415201313

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https://github.com/pydata/xarray/pull/2375#issuecomment-415201313 https://api.github.com/repos/pydata/xarray/issues/2375 415201313 MDEyOklzc3VlQ29tbWVudDQxNTIwMTMxMw== 6815844 2018-08-22T22:22:48Z 2018-08-22T22:22:48Z MEMBER

But maybe it is better to choose the first dim that is MultiIndex rather than the first dim.

first dimension is not well defined in Dataset, as it is a union of the dims of all the dataarrays it has. For example, in the following example, ds.unstack()['var'] and da['var'].unstack() will give different results.

```python In [15]: import numpy as np ...: import xarray as xr ...: ...: ds = xr.Dataset({'var': (('x', 'y', 'z', 'w'), np.random.randn(2,3,4,5))}) ...: ds = ds.stack(b=['z', 'w']).stack(a=['x', 'y']) ...: ds ...: Out[15]: <xarray.Dataset> Dimensions: (a: 6, b: 20) Coordinates: * b (b) MultiIndex - z (b) int64 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 - w (b) int64 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 * a (a) MultiIndex - x (a) int64 0 0 0 1 1 1 - y (a) int64 0 1 2 0 1 2 Data variables: var (b, a) float64 -1.277 -0.4031 -0.3816 ... 1.398 0.6763 -0.6735

In [16]: list(ds.dims) Out[16]: ['a', 'b']

In [17]: list(ds['var'].dims) Out[17]: ['b', 'a'] ```

but in that case should we allow passing in multiple dims?

I like this direction. stack accepts multiple pairs of dimensions to be stacked, like ds.stack(a=['x', 'y'], b=['z', 'w']). In this method, it repeatedly calls _stack_once method. I think unstack also can have the similar logic.

 
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