learn-python/contrib/numpy/concatenation-of-arrays.md

Concatenation of Arrays

Concatenation of arrays in NumPy refers to combining multiple arrays into a single array, either along existing axes or by adding new axes. NumPy provides several functions for this purpose.

Functions of Concatenation

np.concatenate

Joins two or more arrays along an existing axis.

Syntax

numpy.concatenate((arr1, arr2, ...), axis)

Args:

• arr1, arr2, ...: Sequence of arrays to concatenate.
• axis: Axis along which the arrays will be joined. Default is 0.

Example

Concatenate along axis 0

import numpy as np
#creating 2 arrays
arr1 = np.array([1 2 3],[7 8 9])
arr2 = np.array([4 5 6],[10 11 12])

result_1 = np.concatenate((arr1, arr2), axis=0)
print(result_1)

Output

[[ 1  2  3]
 [ 7  8  9]
 [ 4  5  6]
 [10 11 12]]

Concatenate along axis 1

result_2 = np.concatenate((arr1, arr2), axis=1)
print(result_2)

Output

[[ 1 2 3 4 5 6 ]
 [ 7 8 9 10 11 12]]

np.vstack

Vertical stacking of arrays (row-wise).

Syntax

numpy.vstack(arrays)

Args:

• arrays: Sequence of arrays to stack.

Example

import numpy as np
#create arrays
arr1= np.array([1 2 3], [7 8 9])
arr2 = np.array([4 5 6],[10 11 12])

result = np.vstack((arr1, arr2))
print(result)

Output

[[ 1  2  3]
 [ 7  8  9]
 [ 4  5  6]
 [10 11 12]]

3. np.hstack

Stacks arrays horizontally (column-wise).

Syntax

numpy.hstack(arrays)

Args:

• arrays: Sequence of arrays to stack.

Example

import numpy as np
#create arrays
arr1= np.array([1 2 3], [7 8 9])
arr2 = np.array([4 5 6],[10 11 12])

result = np.hstack((arr1, arr2))
print(result)

Output

[[ 1  2  3] [ 4  5  6]
 [ 7  8  9] [10 11 12]]

np.dstack

Stacks arrays along the third axis (depth-wise).

Syntax

numpy.dstack(arrays)

• arrays: Sequence of arrays to stack.

Example

import numpy as np
#create arrays
arr1= np.array([1 2 3], [7 8 9])
arr2 = np.array([4 5 6],[10 11 12])

result = np.dstack((arr1, arr2))
print(result)

Output

[[[ 1  4]
  [ 2  5]
  [ 3  6]]

 [[ 7 10]
  [ 8 11]
  [ 9 12]]]

np.stack

Joins a sequence of arrays along a new axis.

numpy.stack(arrays, axis)

Args:

• arrays: Sequence of arrays to stack.

Example

import numpy as np
#create arrays
arr1= np.array([1 2 3], [7 8 9])
arr2 = np.array([4 5 6],[10 11 12])

result = np.stack((arr1, arr2), axis=0)
print(result)

Output

[[[ 1  2  3]
  [ 7  8  9]]

 [[ 4  5  6]
  [10 11 12]]]

Concatenation with Mixed Dimensions

When concatenating arrays with different shapes, it's often necessary to reshape them to have compatible dimensions.

Example

Concatenate along axis 0

arr1 = np.array([[1, 2, 3], [4, 5, 6]])
arr2 = np.array([7, 8, 9])

result_0= np.concatenate((arr1, arr2[np.newaxis, :]), axis=0)
print(result_0)

Output

[[1 2 3]
 [4 5 6]
 [7 8 9]]

Concatenate along axis 1

result_1 = np.concatenate((arr1, arr2[:, np.newaxis]), axis=1)
print(result_1)

Output

[[1 2 3 7]
 [4 5 6 8]]