Proposed new feature or change:

Mailing list post

It is common to want to pad an array along a specific axis. Examples:

• https://stackoverflow.com/questions/72106542/how-to-pad-the-i-j-axes-of-a-3d-np-array-without-padding-its-k-axis
• https://stackoverflow.com/questions/56076094/zero-pad-ndarray-along-axis
• https://stackoverflow.com/questions/66225047/padding-a-3-dimensional-numpy-array-with-the-medians-alongside-specific-axis
• https://stackoverflow.com/questions/19349410/how-to-pad-with-zeros-a-tensor-along-some-axis-python
• https://stackoverflow.com/questions/74966041/how-to-pad-a-specific-dimension-of-a-numpy-array

Doing so with numpy.pad requires constructing a list of pairs of length equal to the ndim of the array, with exactly one of those pairs at the right position containing the desired pad widths. This can be verbose and cumbersome when there are several axes.

I propose a new, more user-friendly way to pad along a specific axis (or axes): Let the pad_width argument accept a dictionary whose keys are axes and whose values are the (before, after) pair (or perhaps single number) for the corresponding axis. Example:

# before
np.pad(array, [(0, 0), (0, 0), (1, 2), (0, 0), (0, 0)])
# after
np.pad(array, {-3: (1, 2)})

This should require only minor modification to the implementation of numpy.pad. If others like this idea, I can create a PR for it.