What does this np.append() function mean? [on hold]

Question

my_array=[]
my_array.append(np.where(s==10)[0][1])

s is an array. What does the [0] and [1] in the append function mean?

Answer 1

It is very hard to say without knowing what s is, however, I can explain the logic.

Let's say s looks like this:

>>> s
array([[10, 15, 10],
       [20, 34, 10],
       [23, 10, 19]])

np.where(condition) gives the indices of array where the condition matches. Now if it's a two dimensional array (as in this case) it will return two sets of indices, one for rows, one for columns, like this:

>>> np.where(s==10)
(array([0, 0, 1, 2]), array([0, 2, 2, 1]))

This reads like: (0,0), (0,2), (1,2), (2,1) which are the positions where condition matched.

Now if you wanted the row indices you will need to access the first element (0th index) of the tuple returned by where statement:

>>> np.where(s==10)[0]
array([0, 0, 1, 2])

And now if you wanted the second occurrence of 10 in the row indices, you will need to access the 2nd element (1st index), which is 0

>>> np.where(s==10)[0][1]
0

Now you just append that to empty my_array list:

>>> my_array = []
>>> my_array.append(np.where(s==10)[0][1])
# which essentially means my_array.append(0)
>>> my_array
[0]

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