pandas.MultiIndex¶

class pandas.MultiIndex(levels=None, codes=None, sortorder=None, names=None, dtype=None, copy=False, name=None, verify_integrity: bool = True, _set_identity: bool = True)[source]¶

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

Parameters

levelssequence of arrays: The unique labels for each level.
codessequence of arrays: Integers for each level designating which label at each location.

New in version 0.24.0.
sortorderoptional int: Level of sortedness (must be lexicographically sorted by that level).
namesoptional sequence of objects: Names for each of the index levels. (name is accepted for compat).
copybool, default False: Copy the meta-data.
verify_integritybool, 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.
`get_locs`(self, seq)	Get location for a sequence of labels.

pandas.IntervalIndex.get_indexer pandas.MultiIndex.names