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(levels=[[1, 2], ['blue', 'red']],
           codes=[[0, 0, 1, 1], [1, 0, 1, 0]],
           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(levels[, level, inplace, …])	Set new levels on MultiIndex.
set_codes(codes[, level, inplace, …])	Set new codes on MultiIndex.
to_frame([index, name])	Create a DataFrame with the levels of the MultiIndex as columns.
to_flat_index()	Convert a MultiIndex to an Index of Tuples containing the level values.
is_lexsorted()	Return True if the codes are lexicographically sorted
sortlevel([level, ascending, sort_remaining])	Sort MultiIndex at the requested level.
droplevel([level])	Return index with requested level(s) removed.
swaplevel([i, j])	Swap level i with level j.
reorder_levels(order)	Rearrange levels using input order.
remove_unused_levels()	Create a new MultiIndex from the current that removes unused levels, meaning that they are not expressed in the labels.