Add/Stack a 1D numpy array to a 2D numpy array

Question

I am working on an AI project of my own where I append the result(a list) of each layer( which can vary in size) to a list. With lists this worked fine, but I transitioned this to numpy arrays for scalability and I couldn't not get this done. Here is what i want to do.

a = np.array([[1,2,3],[4,5,6]])
b= np.array([7,8])

I want to make

a = np.array([[1,2,3],[4,5,6],[7,8]])

I have tried append and concatenate but those seemed to fail, giving an error that they must be of the same size. Your help is appreciated.

np.array([[1,2,3],[4,5,6],[7,8]]) is not a compact scalar dtype array. — cs95
– cs95, Commented Feb 21, 2019 at 1:30

jyalim · Accepted Answer · 2019-02-21 02:20:15Z

1

Assuming you want to append b to a as an additional column, the following takes advantage of numpy.c_:

import numpy as np
new_a = np.c_[a,b]
print(new_a) 
# array([[1, 2, 3, 7],
#       [4, 5, 6, 8]])

Otherwise, be careful with numpy.array objects as the shape of them matters!

answered Feb 21, 2019 at 2:20

jyalim

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evantkchong · Accepted Answer · 2019-02-21 02:47:03Z

As what coldspeed mentioned in the comment for the question, a = np.array([[1,2,3],[4,5,6],[7,8]]) does not generate a compact scalar dtype array but instead generates an array of lists.

Using a.dtype will return the data type of your array's elements.

a = np.array([[1,2,3],[4,5,6]]) returns int32

a = np.array([[1,2,3],[4,5,6],[7,8]]) returns object

Aside from that, the functions Append and Concatenate require that your arrays are of the same length in the dimension you are joining them. Perhaps what you could do is to pad array b with 'nan' to fit the required length:b = np.array([[7,8,np.nan]]) which will give you

[[ 1.  2.  3.]
 [ 4.  5.  6.]
 [ 7.  8. nan]]

As your number of layers increases, you might need to check for the length of b and pad array a instead.

If your intention is to add on array b as a column, then HAL 9001's answer would be better.

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