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pandas.MultiIndex

class pandas.MultiIndex [source]

A multi-level, or hierarchical, index object for pandas objects.

Parameters:
levels : sequence of arrays

The unique labels for each level.

codes : sequence of arrays

Integers for each level designating which label at each location.

New in version 0.24.0.

labels : sequence of arrays

Integers for each level designating which label at each location.

Deprecated since version 0.24.0: Use codes instead

sortorder : optional int

Level of sortedness (must be lexicographically sorted by that level).

names : optional sequence of objects

Names for each of the index levels. (name is accepted for compat).

copy : bool, default False

Copy the meta-data.

verify_integrity : bool, default True

Check that the levels/codes are consistent and valid.

See also

MultiIndex.from_arrays
Convert list of arrays to MultiIndex.
MultiIndex.from_product
Create a MultiIndex from the cartesian product of iterables.
MultiIndex.from_tuples
Convert list of tuples to a MultiIndex.
MultiIndex.from_frame
Make a MultiIndex from a DataFrame.
Index
The base pandas Index type.

Notes

See the user guide for more.

Examples

A new MultiIndex is typically constructed using one of the helper methods MultiIndex.from_arrays(), MultiIndex.from_product() and MultiIndex.from_tuples(). For example (using .from_arrays):

>>> arrays = [[1, 1, 2, 2], ['red', 'blue', 'red', 'blue']]
>>> pd.MultiIndex.from_arrays(arrays, names=('number', 'color'))
MultiIndex([(1,  'red'),
            (1, 'blue'),
            (2,  'red'),
            (2, 'blue')],
           names=['number', 'color'])

See further examples for how to construct a MultiIndex in the doc strings of the mentioned helper methods.

Attributes

names Names of levels in MultiIndex
nlevels Integer number of levels in this MultiIndex.
levshape A tuple with the length of each level.
levels
codes

Methods

from_arrays(arrays[, sortorder, names]) Convert arrays to MultiIndex.
from_tuples(tuples[, sortorder, names]) Convert list of tuples to MultiIndex.
from_product(iterables[, sortorder, names]) Make a MultiIndex from the cartesian product of multiple iterables.
from_frame(df[, sortorder, names]) Make a MultiIndex from a DataFrame.
set_levels(self, levels[, level, inplace, …]) Set new levels on MultiIndex.
set_codes(self, codes[, level, inplace, …]) Set new codes on MultiIndex.
to_frame(self[, index, name]) Create a DataFrame with the levels of the MultiIndex as columns.
to_flat_index(self) Convert a MultiIndex to an Index of Tuples containing the level values.
is_lexsorted(self) Return True if the codes are lexicographically sorted
sortlevel(self[, level, ascending, …]) Sort MultiIndex at the requested level.
droplevel(self[, level]) Return index with requested level(s) removed.
swaplevel(self[, i, j]) Swap level i with level j.
reorder_levels(self, order) Rearrange levels using input order.
remove_unused_levels(self) Create a new MultiIndex from the current that removes unused levels, meaning that they are not expressed in the labels.

© 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.MultiIndex.html