I have three numpy arrays. The shape of the first is (413, 2), the shape of the second is (176, 2), and the shape of the third is (589,). If you'll notice, 413 176 = 589. What I want to accomplish is to use the 589 values of the third np array and make the first two arrays of shapes (413, 3) and (176, 3) respectively.

So, what I want is to take the values in the third np array and append them to the columns of the first and second np arrays. I can do the logic for applying to the first and then using the offset of the length of the first to continue appending to the second with the correct values. I suppose I could also combine np arrays 1 and 2, they are separated for a reason though because of my data preprocessing.

To put it visually if that helps, what I have is like this:

Array 1:
[[1 2]
 [3 4]
 [4 5]]

Array 2:
[[6 7]
 [8 9]
 [10 11]]

Array 3:
[1 2 3 4 5 6]

And what I want to have is:

Array 1:
[[1 2 1]
 [3 4 2]
 [4 5 3]]

Array 2:
[[6 7 4]
 [8 9 5]
 [10 11 6]]

I've tried using np.append, np.concatenate, and np.vstack but have not been able to achieve what I am looking for. I am relatively new to using numpy, and Python in general, so I imagine I am just using these tools incorrectly.

Many thanks for any help that can be offered! This is my first time asking a question here so if I did anything wrong or left anything out please let me know.

CodePudding user response：

Split the third array using the length of array1, then horizontally stack them. You need to use either np.newaxis or array.reshape to change the dimensionality of the slice of array3.

import numpy as np

array1 = np.array(
  [[1, 2],
   [3, 4],
   [4, 5]]
)

array2 = np.array(
  [[6, 7],
   [8, 9],
   [10, 11]]
)

array3 = np.array([1, 2, 3, 4, 5, 6])

array13 = np.hstack([array1, array3[:len(array1), np.newaxis]])
array23 = np.hstack([array1, array3[len(array1):, np.newaxis]])

Outputs:

array13
array([[1, 2, 4],
       [3, 4, 5],
       [4, 5, 6]])


array23
array([[ 6,  7,  4],
       [ 8,  9,  5],
       [10, 11,  6]])