xarray.DataArray.unstack¶

DataArray.unstack(self, dim: Union[Hashable, Sequence[Hashable], NoneType] = None, fill_value: Any = <NA>, sparse: bool = False) → 'DataArray'¶

Unstack existing dimensions corresponding to MultiIndexes into multiple new dimensions.

New dimensions will be added at the end.

Parameters

dim (hashable or sequence of hashable, optional) – Dimension(s) over which to unstack. By default unstacks all MultiIndexes.
fill_value (value to be filled. By default, np.nan) –
sparse (use sparse-array if True) –

Returns

unstacked – Array with unstacked data.

Return type

DataArray

Examples

>>> arr = DataArray(np.arange(6).reshape(2, 3),
...                 coords=[('x', ['a', 'b']), ('y', [0, 1, 2])])
>>> arr
<xarray.DataArray (x: 2, y: 3)>
array([[0, 1, 2],
       [3, 4, 5]])
Coordinates:
  * x        (x) |S1 'a' 'b'
  * y        (y) int64 0 1 2
>>> stacked = arr.stack(z=('x', 'y'))
>>> stacked.indexes['z']
MultiIndex(levels=[['a', 'b'], [0, 1, 2]],
           codes=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]],
           names=['x', 'y'])
>>> roundtripped = stacked.unstack()
>>> arr.identical(roundtripped)
True