[python] How to add items into a numpy array

I need to accomplish the following task:

from:

a = array([[1,3,4],[1,2,3]...[1,2,1]])

(add one element to each row) to:

a = array([[1,3,4,x],[1,2,3,x]...[1,2,1,x]])

I have tried doing stuff like a[n] = array([1,3,4,x])

but numpy complained of shape mismatch. I tried iterating through a and appending element x to each item, but the changes are not reflected.

Any ideas on how I can accomplish this?

target = []

for line in a.tolist():
    new_line = line.append(X)
    target.append(new_line)

return array(target)

If x is just a single scalar value, you could try something like this to ensure the correct shape of the array that is being appended/concatenated to the rightmost column of a:

import numpy as np
a = np.array([[1,3,4],[1,2,3],[1,2,1]])
x = 10
b = np.hstack((a,x*np.ones((a.shape[0],1))))

returns b as:

array([[  1.,   3.,   4.,  10.],
       [  1.,   2.,   3.,  10.],
       [  1.,   2.,   1.,  10.]])

import numpy as np
a = np.array([[1,3,4],[1,2,3],[1,2,1]])
b = np.array([10,20,30])
c = np.hstack((a, np.atleast_2d(b).T))

returns c:

array([[ 1,  3,  4, 10],
       [ 1,  2,  3, 20],
       [ 1,  2,  1, 30]])

Appending a single scalar could be done a bit easier as already shown (and also without converting to float) by expanding the scalar to a python-list-type:

import numpy as np
a = np.array([[1,3,4],[1,2,3],[1,2,1]])
x = 10

b = np.hstack ((a, [[x]] * len (a) ))

returns b as:

array([[ 1,  3,  4, 10],
       [ 1,  2,  3, 10],
       [ 1,  2,  1, 10]])

Appending a row could be done by:

c = np.vstack ((a, [x] * len (a[0]) ))

returns c as:

array([[ 1,  3,  4],
       [ 1,  2,  3],
       [ 1,  2,  1],
       [10, 10, 10]])

np.insert can also be used for the purpose

import numpy as np
a = np.array([[1, 3, 4],
              [1, 2, 3],
              [1, 2, 1]])
x = 5
index = 3 # the position for x to be inserted before
np.insert(a, index, x, axis=1)

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

index can also be a list/tuple

>>> index = [1, 1, 3] # equivalently (1, 1, 3)
>>> np.insert(a, index, x, axis=1)
array([[1, 5, 5, 3, 4, 5],
       [1, 5, 5, 2, 3, 5],
       [1, 5, 5, 2, 1, 5]])

or a slice

>>> index = slice(0, 3)
>>> np.insert(a, index, x, axis=1)
array([[5, 1, 5, 3, 5, 4],
       [5, 1, 5, 2, 5, 3],
       [5, 1, 5, 2, 5, 1]])

One way to do it (may not be the best) is to create another array with the new elements and do column_stack. i.e.

>>>a = array([[1,3,4],[1,2,3]...[1,2,1]])
[[1 3 4]
 [1 2 3]
 [1 2 1]]

>>>b = array([1,2,3])
>>>column_stack((a,b))
array([[1, 3, 4, 1],
       [1, 2, 3, 2],
       [1, 2, 1, 3]])