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Create an object to more easily perform multi-index slicing.
See Also
--------
MultiIndex.remove_unused_levels : New MultiIndex with no unused levels.
Notes
-----
See :ref:`Defined Levels <advanced.shown_levels>`
for further info on slicing a MultiIndex.
Examples
--------
>>> midx = pd.MultiIndex.from_product([['A0','A1'], ['B0','B1','B2','B3']])
>>> columns = ['foo', 'bar']
>>> dfmi = pd.DataFrame(np.arange(16).reshape((len(midx), len(columns))),
... index=midx, columns=columns)
Using the default slice command:
>>> dfmi.loc[(slice(None), slice('B0', 'B1')), :]
foo bar
A0 B0 0 1
B1 2 3
A1 B0 8 9
B1 10 11
Using the IndexSlice class for a more intuitive command:
>>> idx = pd.IndexSlice
>>> dfmi.loc[idx[:, 'B0':'B1'], :]
foo bar
A0 B0 0 1
B1 2 3
A1 B0 8 9
B1 10 11
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IndexingMixinzH
Mixin for adding .loc/.iloc/.at/.iat to Dataframes and Series.
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