cudf.Series.factorize

Series.factorize(sort=False, na_sentinel=None, use_na_sentinel=None)

Encode the input values as integer labels.

Parameters:

sortbool, default True

Sort uniques and shuffle codes to maintain the relationship.

na_sentinelnumber, default -1

Value to indicate missing category.

Deprecated since version 23.04: The na_sentinel argument is deprecated and will be removed in a future version of cudf. Specify use_na_sentinel as either True or False.

use_na_sentinelbool, default True

If True, the sentinel -1 will be used for NA values. If False, NA values will be encoded as non-negative integers and will not drop the NA from the uniques of the values.

Returns:

(labels, cats)(cupy.ndarray, cupy.ndarray or Index)

• labels contains the encoded values

• cats contains the categories in order that the N-th item corresponds to the (N-1) code.

Examples

>>> import cudf
>>> s = cudf.Series(['a', 'a', 'c'])
>>> codes, uniques = s.factorize()
>>> codes
array([0, 0, 1], dtype=int8)
>>> uniques
StringIndex(['a' 'c'], dtype='object')