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 |
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See also
MultiIndex.from_arrays
MultiIndex.from_product
MultiIndex.from_tuples
Index
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. |
levels | |
labels |
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 |
© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
http://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.MultiIndex.html