Split a NumPy array into subarrays according to the values (sorted in ascending order) of another array

Question

Suppose I have two NumPy arrays

x = [[5, 2, 8],
     [4, 9, 1],
     [7, 8, 9],
     [1, 3, 5],
     [1, 2, 3],
     [1, 2, 4]]
y = [0, 0, 1, 1, 1, 2]

I want to efficiently split the array x into sub-arrays according to the values in y.

My desired outputs would be

z_0 = [[5, 2, 8],
       [4, 9, 1]]
z_1 = [[7, 8, 9],
       [1, 3, 5],
       [1, 2, 3]]
z_2 = [[1, 2, 4]]

Assuming that y starts with zero and is sorted in ascending order, what is the most efficient way to do this?

Mad Physicist · Accepted Answer · 2021-03-19 06:09:06Z

2

If y is grouped (doesn't have to be sorted), you can use diff to get the split points:

indices = np.flatnonzero(np.diff(y)) + 1

You can pass those directly to np.split:

z = np.split(x, indices, axis=0)

If you want to know the labels too:

labels = y[np.r_[0, indices]]

answered Mar 19, 2021 at 6:09

Mad Physicist

116k29 gold badges202 silver badges292 bronze badges

Sign up to request clarification or add additional context in comments.

1 Answer 1