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class pandas.MultiIndex[source]

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


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

Convert list of arrays to MultiIndex
Create a MultiIndex from the cartesian product of iterables
Convert list of tuples to a MultiIndex
The base pandas Index type


See the user guide for more.


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.


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


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
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