Concat two arrays of different dimensions numpy
Question:
I am trying to concatenate two numpy arrays to add an extra column: array_1
is (569, 30)
and array_2
is is (569, )
combined = np.concatenate((array_1, array_2), axis=1)
I thought this would work if I set axis=2
so it will concatenate vertically. The end should should be a 569 x 31 array.
The error I get is ValueError: all the input arrays must have same number of dimensions
Can someone help?
Thx!
Answers:
You can use numpy.column_stack
:
np.column_stack((array_1, array_2))
Which converts the 1-d array to 2-d implicitly, and thus equivalent to np.concatenate((array_1, array_2[:,None]), axis=1)
as commented by @umutto.
a = np.arange(6).reshape(2,3)
b = np.arange(2)
a
#array([[0, 1, 2],
# [3, 4, 5]])
b
#array([0, 1])
np.column_stack((a, b))
#array([[0, 1, 2, 0],
# [3, 4, 5, 1]])
You can simply use numpy
‘s hstack
function.
e.g.
import numpy as np
combined = np.hstack((array1,array2))
To stack them vertically try
np.vstack((array1,array2))
You can convert the 1-D array to 2-D array with the same number of rows using reshape function and concatenate the resulting array horizontally using numpy’s append function.
Note: In numpy’s append function, we have to mention axis along which we want to insert the values.
If axis=0, arrays are appended vertically. If axis=1, arrays are appended horizontally.
So, we can use axis=1, for current requirement
e.g.
a = np.arange(6).reshape(2,3)
b = np.arange(2)
a
#array([[0, 1, 2],
# [3, 4, 5]])
b
#array([0, 1])
#First step, convert this 1-D array to 2-D (Number of rows should be same as array 'a' i.e. 2)
c = b.reshape(2,1)
c
#array([[0],
[1]])
#Step 2, Using numpy's append function we can concatenate both arrays with same number of rows horizontally
requirement = np.append((a, c, axis=1))
requirement
#array([[0, 1, 2, 0],
# [3, 4, 5, 1]])
I am trying to concatenate two numpy arrays to add an extra column: array_1
is (569, 30)
and array_2
is is (569, )
combined = np.concatenate((array_1, array_2), axis=1)
I thought this would work if I set axis=2
so it will concatenate vertically. The end should should be a 569 x 31 array.
The error I get is ValueError: all the input arrays must have same number of dimensions
Can someone help?
Thx!
You can use numpy.column_stack
:
np.column_stack((array_1, array_2))
Which converts the 1-d array to 2-d implicitly, and thus equivalent to np.concatenate((array_1, array_2[:,None]), axis=1)
as commented by @umutto.
a = np.arange(6).reshape(2,3)
b = np.arange(2)
a
#array([[0, 1, 2],
# [3, 4, 5]])
b
#array([0, 1])
np.column_stack((a, b))
#array([[0, 1, 2, 0],
# [3, 4, 5, 1]])
You can simply use numpy
‘s hstack
function.
e.g.
import numpy as np
combined = np.hstack((array1,array2))
To stack them vertically try
np.vstack((array1,array2))
You can convert the 1-D array to 2-D array with the same number of rows using reshape function and concatenate the resulting array horizontally using numpy’s append function.
Note: In numpy’s append function, we have to mention axis along which we want to insert the values.
If axis=0, arrays are appended vertically. If axis=1, arrays are appended horizontally.
So, we can use axis=1, for current requirement
e.g.
a = np.arange(6).reshape(2,3)
b = np.arange(2)
a
#array([[0, 1, 2],
# [3, 4, 5]])
b
#array([0, 1])
#First step, convert this 1-D array to 2-D (Number of rows should be same as array 'a' i.e. 2)
c = b.reshape(2,1)
c
#array([[0],
[1]])
#Step 2, Using numpy's append function we can concatenate both arrays with same number of rows horizontally
requirement = np.append((a, c, axis=1))
requirement
#array([[0, 1, 2, 0],
# [3, 4, 5, 1]])