Numpy column_stack() Function

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The Numpy column_stack() function is used to stack 1D or 2D arrays as columns into a 2D array. This function is defined in the numpy module. It is particularly useful when we want to stack one or more 1D arrays as columns in a new 2D array, or if we want to concatenate two 2D arrays along the second axis.

The numpy.column_stack() function stacks 1D arrays into columns of a 2D array, resulting in an array with shape (n, m), where n is the length of the arrays and m is the number of arrays. When provided with 2D arrays, it works like numpy.hstack(), concatenating them along the second axis if they have matching dimensions in other axes.

Syntax

Following is the syntax of the Numpy column_stack() function −

numpy.column_stack(arrays)

Parameters

Following are the parameters of the Numpy column_stack() function −

• arrays - A sequence of 1D or 2D arrays. For 1D arrays, all must have the same length. For 2D arrays, they must have the same shape along all but the second axis.

Return Values

The function returns a 2D array with each input array stacked as a column in the output.

Example

Following is a basic example to stack two 1D arrays as columns using Numpy column_stack() function −

import numpy as np
array1 = np.array([10, 20, 30])
array2 = np.array([40, 50, 60])
column_stacked_array = np.column_stack((array1, array2))
print("Array 1 -", array1)
print("Array 2 -", array2)
print("Column Stacked Array -\n", column_stacked_array)

Output

Following is the output of the above code −

Array 1 - [10 20 30]
Array 2 - [40 50 60]
Column Stacked Array -
 [[10 40]
  [20 50]
  [30 60]]

Example - Stacking 2D Arrays

In the following example, we stack two 2D arrays with matching shapes along the rows. The arrays will be concatenated along the second axis, resulting in a larger 2D array −

import numpy as np
array1 = np.array([[1, 2], [3, 4]])
array2 = np.array([[5, 6], [7, 8]])
column_stacked_array = np.column_stack((array1, array2))
print("Array 1 -\n", array1)
print("Array 2 -\n", array2)
print("Column Stacked Array -\n", column_stacked_array)

Output

Following is the output of the above code −

Array 1 -
 [[1 2]
  [3 4]]
Array 2 -
 [[5 6]
  [7 8]]
Column Stacked Array -
 [[1 2 5 6]
  [3 4 7 8]]

Example - Stacking Arrays with Different Shapes

If the input arrays have incompatible shapes, such as mismatched lengths for 1D arrays or different shapes along other axes for 2D arrays, numpy.column_stack() will raise a ValueError. In the following example, we attempt to stack arrays of incompatible shapes −

import numpy as np
array1 = np.array([1, 2, 3])
array2 = np.array([4, 5])
try:
    column_stacked_array = np.column_stack((array1, array2))
except ValueError as e:
    print("ValueError:", e)

Output

Following is the output of the above code −

ValueError: all the input arrays must have same number of dimensions, but the array at index 1 has 2 dimension(s)