What does this: s[s[1:] == s[:-1]] do in numpy?

Question

I\'ve been looking for a way to efficiently check for duplicates in a numpy array and stumbled upon a question that contained an answer using this code.

What does th

Answer 1

The slices [1:] and [:-1] mean all but the first and all but the last elements of the array:

>>> import numpy as np
>>> s = np.array((1, 2, 2, 3))  # four element array
>>> s[1:]
array([2, 2, 3])  # last three elements
>>> s[:-1]
array([1, 2, 2])  # first three elements

therefore the comparison generates an array of boolean comparisons between each element s[x] and its "neighbour" s[x+1], which will be one shorter than the original array (as the last element has no neighbour):

>>> s[1:] == s[:-1]
array([False,  True, False], dtype=bool)

and using that array to index the original array gets you the elements where the comparison is True, i.e. the elements that are the same as their neighbour:

>>> s[s[1:] == s[:-1]]
array([2])

Note that this only identifies adjacent duplicate values.