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indexable — scikit-learn 1.7.0 documentation

sklearn.utils.indexable(*iterables)[source]#

Make arrays indexable for cross-validation.

Checks consistent length, passes through None, and ensures that everything can be indexed by converting sparse matrices to csr and converting non-iterable objects to arrays.

Parameters:

*iterables{lists, dataframes, ndarrays, sparse matrices}

List of objects to ensure sliceability.

Returns:

resultlist of {ndarray, sparse matrix, dataframe} or None

Returns a list containing indexable arrays (i.e. NumPy array, sparse matrix, or dataframe) or None.

Examples

>>> from sklearn.utils import indexable
>>> from scipy.sparse import csr_matrix
>>> import numpy as np
>>> iterables = [
...     [1, 2, 3], np.array([2, 3, 4]), None, csr_matrix([[5], [6], [7]])
... ]
>>> indexable(*iterables)
[[1, 2, 3], array([2, 3, 4]), None, <...Sparse...dtype 'int64'...shape (3, 1)>]

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