Introduction to Python NumPy Joining Array

Python NumPy Joining Array

In NumPy, you can join or concatenate arrays along different axes using various functions.

Here are some common functions for joining arrays:

Using np.concatenate()

The np.concatenate() function allows you to join arrays along a specified axis.

It takes a sequence of arrays as input and concatenates them into a single array.

import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])

# Join arrays along the first axis (axis=0)
result = np.concatenate((arr1, arr2))
print(result) #Output: [1 2 3 4 5 6]

Using np.stack()

The np.stack() function stacks arrays along a new axis. It takes a sequence of arrays as input and stacks them along the specified axis.

import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])

# Stack arrays along a new axis (axis=0)
result = np.stack((arr1, arr2))
print(result) # Output:  [[1 2 3][4 5 6]]

Using np.vstack() and np.hstack()

The np.vstack() function vertically stacks arrays, while np.hstack() horizontally stacks arrays.

import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])

# Vertically stack arrays
vstack_result = np.vstack((arr1, arr2))
print(vstack_result)

# Horizontally stack arrays
hstack_result = np.hstack((arr1, arr2))
print(hstack_result) #Output [[1 2 3][4 5 6]][1 2 3 4 5 6]