Can np.stack() handle arrays of different shapes?
np.stack() can handle arrays of different shapes. However, the arrays must have the same dimensions along the specified axis.
np.stack() differ from
np.concatenate() are used to combine arrays, but
np.stack() creates a new axis along which the arrays are stacked, while
np.concatenate() combines arrays along an existing axis.
What happens if I use an invalid value for the
If you use an invalid value for the
axis parameter, NumPy will raise a
ValueError indicating that the axis is out of bounds.
Can I stack more than two arrays using
np.stack() can stack multiple arrays. Simply provide the arrays as an iterable sequence, and specify the desired axis.
Is there a limit to the number of dimensions that
np.stack() can handle?
np.stack() can handle arrays with any number of dimensions. It creates a new axis for stacking along the specified dimension.