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pandas.MultiIndex.from_product

classmethod MultiIndex.from_product(iterables, sortorder=None, names=None) [source]

Make a MultiIndex from the cartesian product of multiple iterables.

Parameters:
iterables : list / sequence of iterables

Each iterable has unique labels for each level of the index.

sortorder : int or None

Level of sortedness (must be lexicographically sorted by that level).

names : list / sequence of str, optional

Names for the levels in the index.

Returns:
index : MultiIndex

See also

MultiIndex.from_arrays
Convert list of arrays to MultiIndex.
MultiIndex.from_tuples
Convert list of tuples to MultiIndex.
MultiIndex.from_frame
Make a MultiIndex from a DataFrame.

Examples

>>> numbers = [0, 1, 2]
>>> colors = ['green', 'purple']
>>> pd.MultiIndex.from_product([numbers, colors],
...                            names=['number', 'color'])
MultiIndex([(0,  'green'),
            (0, 'purple'),
            (1,  'green'),
            (1, 'purple'),
            (2,  'green'),
            (2, 'purple')],
           names=['number', 'color'])

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https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.MultiIndex.from_product.html