appending values to numpy array

Question

I have two different arrays b0 and b1 where: b0=[1,2] b1=[3,4]

I want list[1st element of b0, 1st element of b1] to appended into new array B and similarly: list[2nd element of b0, 2nd element of b1] to appended into new array B and so on......

that is my new array should be something like: array([1,3],[2,4])

Below is my code:

b0=np.array([1,2])
b1=np.array([3,4])

for val in range(len(b1)):
    L=[b0[val],b1[val]]
    B=np.append(L,axis=0)
print(B)

I am getting missing on positional argument values error. Kindly help me to fix it.

Please take a look at the help or documentation. The signature is numpy.append(arr, values, axis=None), so you need an array arr, the values values you want to append to arr and optionally the axis. — Niklas Mertsch
– Niklas Mertsch, Commented May 16, 2019 at 6:38

N. Arunoprayoch · Accepted Answer · 2019-05-16 06:50:58Z

1

If you insist to use numpy array, this is what I would do.

new = []
for x, y in zip(b0, b1):
    new.append([x, y])

new = np.array(new)

Or list comprehension

new = np.array([[x,y] for x, y in zip(b0, b1)])

Result:

array([[1, 3],
       [2, 4]])

answered May 16, 2019 at 6:50

N. Arunoprayoch

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Comments

Xuekai Du · Accepted Answer · 2019-05-16 07:03:08Z

0

Using np.append here isn't the most convenient way in my opinion. You can always cast python list into np.array and it's much easier to just use zip in this case.

b0=np.array([1,2])
b1=np.array([3,4])
B=np.array(list(zip(b0,b1)))

output:

>>> B
array([[1, 3],
       [2, 4]])

answered May 16, 2019 at 7:03

Xuekai Du

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Comments

hpaulj · Accepted Answer · 2019-05-16 07:10:27Z

In [51]: b0=np.array([1,2]) 
    ...: b1=np.array([3,4])

Order's wrong:

In [56]: np.vstack((b0,b1))                                                  
Out[56]: 
array([[1, 2],
       [3, 4]])

but you can transpose it:

In [57]: np.vstack((b0,b1)).T                                                
Out[57]: 
array([[1, 3],
       [2, 4]])

stack is a more general purpose concatenator

In [58]: np.stack((b0,b1), axis=1)                                           
Out[58]: 
array([[1, 3],
       [2, 4]])

or with:

In [59]: np.column_stack((b0,b1))                                            
Out[59]: 
array([[1, 3],
       [2, 4]])

More details on combining arrays in my other recent answer: https://stackoverflow.com/a/56159553/901925

All these, including np.append use np.concatenate, just tweaking the dimensions in different ways first. np.append is often misused. It isn't a list append clone. None should be used repeatedly in a loop. They make a new array each time, which isn't very efficient.

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