num_samples

pybear.base.num_samples(X)

Return the number of samples in an array-like X.

X must have a ‘shape’ attribute.

numpy, pandas, & polars:

X must be 1 or 2 dimensional.

scipy:

X must be 2 dimensional.

If X is a 1D vector (i.e., len(X.shape)==1), return len(X).

Parameters:

XXContainer of shape (n_samples, n_features) or (n_samples,)

Object to find the number of samples in, that has a ‘shape’ attribute.

Returns:

rowsint

Number of samples.

Notes

Type Aliases

NumpyTypes:

numpy.ndarray

PandasTypes:

pandas.Series | pandas.DataFrame

PolarsTypes:

polars.Series | polars.DataFrame

ScipySparseTypes:

ss.csc_matrix | ss.csc_array | ss.csr_matrix | ss.csr_array | ss.coo_matrix | ss.coo_array | ss.dia_matrix | ss.dia_array | ss.lil_matrix | ss.lil_array | ss.dok_matrix | ss.dok_array | ss.bsr_matrix | ss.bsr_array

XContainer:

NumpyTypes | PandasTypes | PolarsTypes | ScipySparseTypes

Examples

>>> from pybear.base import num_samples
>>> import numpy as np
>>> X = np.random.randint(0, 10, (5, 4))
>>> num_samples(X)
5