pandas.IndexSlice = <pandas.core.indexing._IndexSlice object> Create an object to more easily perform multi-index slicing
See also
MultiIndex.remove_unused_levels
See Defined Levels for further info on slicing a MultiIndex.
>>> 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
© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.IndexSlice.html