Numpy - Stacking and Splitting Arrays

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Stacking and splitting arrays are common operations in NumPy that can be used to combine or separate arrays in various ways.

To stack arrays horizontally (i.e., column-wise), you can use the hstack function, which takes a sequence of arrays as arguments and returns a single array with the arrays stacked horizontally. For example:

import numpy as np

# Create two arrays
x = np.array([1, 2, 3])
y = np.array([4, 5, 6])

# Stack the arrays horizontally
z = np.hstack((x, y))

print(z)  # [1 2 3 4 5 6]

To stack arrays vertically (i.e., row-wise), you can use the vstack function, which takes a sequence of arrays as arguments and returns a single array with the arrays stacked vertically. For example:

# Stack the arrays vertically
z = np.vstack((x, y))

print(z)  # [[1 2 3]
          #  [4 5 6]]

To split an array into multiple smaller arrays, you can use the split function, which takes an array and a sequence of indices or a boolean mask and returns a list of subarrays. For example:

# Create a one-dimensional array
x = np.array([1, 2, 3, 4, 5, 6])

# Split the array into three subarrays
y = np.split(x, [2, 4])

print(y)  # [array([1, 2]), array([3, 4]), array([5, 6])]

You can also specify an axis along which to split the array using the axis argument. For example:

# Create a two-dimensional array
x = np.array([[1, 2, 3], [4, 5, 6]])

# Split the array along the second axis
y = np.split(x, 2, axis=1)

print(y)  # [array([[1], [4]]), array([[2], [5]]), array([[3], [6]])]