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 labels : sequence of arrays Integers for each level designating which label at each location 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 : boolean, default False Copy the meta-data verify_integrity : boolean, default True Check that the levels/labels 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

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']],
       labels=[[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
labels

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
set_levels(levels[, level, inplace, …])	Set new levels on MultiIndex.
set_labels(labels[, level, inplace, …])	Set new labels on MultiIndex.
to_hierarchical(n_repeat[, n_shuffle])	Return a MultiIndex reshaped to conform to the shapes given by n_repeat and n_shuffle.
to_frame([index])	Create a DataFrame with the levels of the MultiIndex as columns.
is_lexsorted()	Return True if the labels are lexicographically sorted
sortlevel([level, ascending, sort_remaining])	Sort MultiIndex at the requested level.
droplevel([level])	Return Index with requested level 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 removing unused levels, meaning that they are not expressed in the labels