NumPy Joining Arrays
Joining arrays in NumPy allows you to combine multiple arrays into a single array. This is useful for various data manipulation tasks. NumPy provides several functions to join arrays.
Concatenating Arrays
The numpy.concatenate() function joins a sequence of arrays along an existing axis.
Example: Concatenating 1-D Arrays
import numpy as np
# Creating two 1-D arrays
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
# Concatenating the arrays
result = np.concatenate((arr1, arr2))
print(result) # Output: [1 2 3 4 5 6]Example: Concatenating 2-D Arrays
import numpy as np
# Creating two 2-D arrays
arr1 = np.array([[1, 2], [3, 4]])
arr2 = np.array([[5, 6], [7, 8]])
# Concatenating the arrays along axis 0
result = np.concatenate((arr1, arr2), axis=0)
print(result)
# Output:
# [[1 2]
# [3 4]
# [5 6]
# [7 8]]
# Concatenating the arrays along axis 1
result = np.concatenate((arr1, arr2), axis=1)
print(result)
# Output:
# [[1 2 5 6]
# [3 4 7 8]]Stacking Arrays
The numpy.stack() function joins a sequence of arrays along a new axis.
Example: Stacking 1-D Arrays
import numpy as np
# Creating two 1-D arrays
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
# Stacking the arrays along a new axis
result = np.stack((arr1, arr2), axis=0)
print(result)
# Output:
# [[1 2 3]
# [4 5 6]]
result = np.stack((arr1, arr2), axis=1)
print(result)
# Output:
# [[1 4]
# [2 5]
# [3 6]]Stacking Along Rows and Columns
NumPy provides helper functions like hstack() and vstack() for stacking along rows and columns, respectively.
Example: Horizontal Stacking
import numpy as np
# Creating two 1-D arrays
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
# Horizontal stacking
result = np.hstack((arr1, arr2))
print(result) # Output: [1 2 3 4 5 6]Example: Vertical Stacking
import numpy as np
# Creating two 1-D arrays
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
# Vertical stacking
result = np.vstack((arr1, arr2))
print(result)
# Output:
# [[1 2 3]
# [4 5 6]]Depth Stacking
The dstack() function stacks arrays along the third dimension.
Example: Depth Stacking
import numpy as np
# Creating two 1-D arrays
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
# Depth stacking
result = np.dstack((arr1, arr2))
print(result)
# Output:
# [[[1 4]
# [2 5]
# [3 6]]]Joining Arrays with append()
You can also use the numpy.append() function to join arrays.
Example: Using append()
import numpy as np
# Creating two 1-D arrays
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
# Using append to join arrays
result = np.append(arr1, arr2)
print(result) # Output: [1 2 3 4 5 6]Conclusion
Joining arrays in NumPy is an essential operation for data manipulation. Whether you’re concatenating, stacking, or appending arrays, NumPy provides a variety of functions to efficiently combine arrays.