Splitting Arrays in NumPy

Array splitting can be vertical, horizontal, or depth-wise. We can use functions hsplit(), vsplit() and dsplit() respectively for the same . We can split arrays into arrays of the same shape by indicating the position after which the split should occur.

• Horizontal splitting: The ‘hsplit()’ function splits an array along axis parameter = 1. ‘numpy.hsplit’ is equivalent to ‘split’ with axis parameter = 1, the array is always splitted along the second axis regardless of the array dimension. This function split an array into multiple sub-arrays horizontally (column-wise).

  Syntax:

  numpy.hsplit(ary, indices_or_sections)

  Example:

  
  

  
  
  

  # Horizontal array splitting using np.hsplit() import numpy as np       # Making of  a 3x3 array a = np.arange(9).reshape(3, 3)    # Horizontal splitting of array  # 'a' using np.hsplit(). print("The array {} gets splitted \ horizontally to form {} ".format(a, np.hsplit(a, 3)))    # Horizontal splitting of array 'a'  # using 'split' with axis parameter = 1. print("The array {} gets splitted \ horizontally to form {} ".format(a, np.split(a, 3, 1)))

  Output:

   The array [[0 1 2]
   [3 4 5]
   [6 7 8]] gets splitted horizontally to form [array([[0],
         [3],
         [6]]), array([[1],
         [4],
         [7]]), array([[2],
         [5],
         [8]])] 
  The array [[0 1 2]
   [3 4 5]
   [6 7 8]] gets splitted horizontally to form [array([[0],
         [3],
         [6]]), array([[1],
         [4],
         [7]]), array([[2],
         [5],
         [8]])]

• Vertical splitting: The ‘vsplit()’ function splits an array along axis parameter = 0.‘numpy.vsplit’ is equivalent to ‘split’ with axis parameter = 0. This function split an array into multiple sub-arrays vertically (row-wise).

  numpy.vsplit(ary, indices_or_sections)

  Example:

  
  

  
  
  

  import numpy as np       # Making of  a 3x3 array a = np.arange(9).reshape(3, 3)    # Vertical splitting of array 'a' # using np.vsplit(). print("The array {} gets splitted \ vertically to form {} ".format(a, np.vsplit(a, 3)))    # Vertical splitting of array 'a'  # using 'split' with axis parameter = 0. print("The array {} gets splitted \ vertically to form {} ".format(a, np.split(a, 3, 0)))

  Output:

  The array [[0 1 2]
  [3 4 5]
  [6 7 8]] gets splitted vertically to form [array([[0, 1, 2]]), array([[3, 4, 5]]), array([[6, 7, 8]])]
  The array [[0 1 2]
  [3 4 5]
  [6 7 8]] gets splitted vertically to form [array([[0, 1, 2]]), array([[3, 4, 5]]), array([[6, 7, 8]])]

• Depth-wise splitting: It Split the array into multiple sub-arrays along the 3rd axis (depth).

  numpy.dsplit(ary, indices_or_sections)

  Example:

  
  

  
  
  

  import numpy as np       # Making of  a 3x3x3 array. b = np.arange(27).reshape(3, 3, 3)    # Depth-wise splitting of array # 'b' using np.dsplit(). print("The array {} gets splitted \ depth-wise to form {}".format(b, np.dsplit(b, 3)))

  Output:

  The array [[[ 0 1 2]
  [ 3 4 5]
  [ 6 7 8]]

  [[ 9 10 11]
  [12 13 14]
  [15 16 17]]

  [[18 19 20]
  [21 22 23]
  [24 25 26]]] gets splitted depth-wise to form [array([[[ 0],
  [ 3],
  [ 6]],

  [[ 9],
  [12],
  [15]],

  [[18],
  [21],
  [24]]]), array([[[ 1],
  [ 4],
  [ 7]],

  [[10],
  [13],
  [16]],

  [[19],
  [22],
  [25]]]), array([[[ 2],
  [ 5],
  [ 8]],

  [[11],
  [14],
  [17]],

  [[20],
  [23],
  [26]]])]