pandas.MultiIndex#
- class pandas.MultiIndex(levels=None, codes=None, sortorder=None, names=None, dtype=None, copy=False, name=None, verify_integrity=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.
- 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.
Attributes
Names of levels in MultiIndex.
Levels of the MultiIndex.
Integer number of levels in this MultiIndex.
A tuple with the length of each level.
Return the dtypes as a Series for the underlying MultiIndex.
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, verify_integrity])Set new levels on MultiIndex.
set_codes
(codes, *[, level, verify_integrity])Set new codes on MultiIndex.
to_frame
([index, name, allow_duplicates])Create a DataFrame with the levels of the MultiIndex as columns.
Convert a MultiIndex to an Index of Tuples containing the level values.
sortlevel
([level, ascending, ...])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.
Create new MultiIndex from current that removes unused levels.
get_level_values
(level)Return vector of label values for requested level.
get_indexer
(target[, method, limit, tolerance])Compute indexer and mask for new index given the current index.
get_loc
(key)Get location for a label or a tuple of labels.
get_locs
(seq)Get location for a sequence of labels.
get_loc_level
(key[, level, drop_level])Get location and sliced index for requested label(s)/level(s).
drop
(codes[, level, errors])Make a new
pandas.MultiIndex
with the passed list of codes deleted.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 methodsMultiIndex.from_arrays()
,MultiIndex.from_product()
andMultiIndex.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.