CODEWITHSUNDEEP
pythonnumpynumpy-ndarray
Tushar Agrawal
Tushar Agrawal

Reputation: 93

How to insert a column in one dimensional NumPy array

I have a NumPy array 

import numpy as np
A = np.array([2, 3, 4, 5, 6, 7, 8, 9, 10, 11])

I want to insert a new column to A to make it look like 

A=[[1,2], [1,3], [1,4], [1,5], [1,6], [1,7], [1,8], [1,9], [1,10], [1,11]]

I tried using NumPy.insert(A,0,1,axis=1) but it gives following error:

AxisError: axis 1 is out of bounds for array of dimension 1

I can't find where I am doing wrong. Please help me rectify this and suggest any other method(s).

Upvotes: 0

Views: 499

Answers (3)

hpaulj
hpaulj

Reputation: 231335

The column_stack or array that others suggest are fine, but to stick with the insert:

In [126]: A = np.array([2, 3, 4, 5, 6, 7, 8, 9, 10, 11])                                               
In [127]: A.shape                                                                                      
Out[127]: (10,)
In [128]: A[:,None].shape                                                                              
Out[128]: (10, 1)
In [129]: np.insert(A[:,None],0,1, axis=1)                                                             
Out[129]: 
array([[ 1,  2],
       [ 1,  3],
       [ 1,  4],
       [ 1,  5],
       [ 1,  6],
       [ 1,  7],
       [ 1,  8],
       [ 1,  9],
       [ 1, 10],
       [ 1, 11]])

To do an insert on axis 1, A has to have such an axis, i.e. has to be 2d. That's what your error message was all about. A is only 1d.

Upvotes: 1

Aly Hosny
Aly Hosny

Reputation: 827

np.insert insert only single value, you need to stack a second column. you can use np.column_stack or np.c_

import numpy as np

A=np.array([2,3,4,5,6,7,8,9,10,11])
arr1 = np.ones(len(A))
out = np.c_[arr1,A]
array([[ 1.,  2.],
       [ 1.,  3.],
       [ 1.,  4.],
       [ 1.,  5.],
       [ 1.,  6.],
       [ 1.,  7.],
       [ 1.,  8.],
       [ 1.,  9.],
       [ 1., 10.],
       [ 1., 11.]])
np.column_stack((arr1,A))
array([[ 1.,  2.],
       [ 1.,  3.],
       [ 1.,  4.],
       [ 1.,  5.],
       [ 1.,  6.],
       [ 1.,  7.],
       [ 1.,  8.],
       [ 1.,  9.],
       [ 1., 10.],
       [ 1., 11.]])

Upvotes: 1

Ralvi Isufaj
Ralvi Isufaj

Reputation: 482

Perhaps this is what you want:

a = np.array([1,2,3,4,5,6,7,8,9,10,11])
b = np.ones(a.shape[0])
c = np.array((b,a)).T

Output is:

[[ 1.  1.]
 [ 1.  2.]
 [ 1.  3.]
 [ 1.  4.]
 [ 1.  5.]
 [ 1.  6.]
 [ 1.  7.]
 [ 1.  8.]
 [ 1.  9.]
 [ 1. 10.]
 [ 1. 11.]]

Upvotes: 0

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