NumPy: numpy.hsplit() function

numpy.hsplit() function

The numpy.hsplit() function is used to split an array into multiple sub-arrays horizontally (column-wise).
hsplit is equivalent to split with axis=1, the array is always split along the second axis regardless of the array dimension.

The function is a useful tool for manipulating and analyzing multi-dimensional arrays in NumPy.

Syntax:

numpy.hsplit(ary, indices_or_sections)

Parameters:

Return value:

Example: Splitting a NumPy array horizontally using numpy.hsplit()

>>> import numpy as np
>>> a = np.arange(16.0).reshape(4,4)	   
>>> np.hsplit(a, 2)
[array([[  0.,   1.],
       [  4.,   5.],
       [  8.,   9.],
       [ 12.,  13.]]), array([[  2.,   3.],
       [  6.,   7.],
       [ 10.,  11.],
       [ 14.,  15.]])]

In the above code, a NumPy array 'a' is created using arange() function, and then reshaped to a 4x4 matrix. The np.hsplit() function is then used to horizontally split the array into 2 parts.

Pictorial Presentation:

Example: Splitting a numpy array horizontally with numpy.hsplit() and specific indices

>>> import numpy as np
>>> a = np.arange(16.0).reshape(4,4)
>>> np.hsplit(a, np.array([3,6]))
[array([[  0.,   1.,   2.],
       [  4.,   5.,   6.],
       [  8.,   9.,  10.],
       [ 12.,  13.,  14.]]), array([[  3.],
       [  7.],
       [ 11.],
       [ 15.]]), array([], shape=(4, 0), dtype=float64)]

In the above code the np.hsplit() function is called with the array 'a' and an array of specific indices [3,6]. This will split the array 'a' into three arrays at positions 3 and 6 along the horizontal axis.

• The first array contains the first three columns of the original array 'a'.
• The second array contains the fourth column of the original array 'a'.
• The third array is empty because there are no columns between the indices 6 and 4.

Python - NumPy Code Editor:

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