Numpy expand dims - Python NumPy expand_dims() Function

NumPy expand_dims() Function:

Numpy expand dims: The expand_dims() function of NumPy module expands an array’s shape(shape of an array). It adds or inserts a new axis to the extended array shape, which will appear at the axis position.

Syntax:

numpy.expand_dims(a, axis)

Parameters

a: This is required. It is an input array.

axis: This is required. It indicates the position in the expanded axes where the new axis (or axes) is to be inserted. Int or a tuple of ints can be used.

Return Value:

NP expand dims: It returns an Array[ndArray]. The output array has one more dimension than the input array.

NumPy expand_dims() Function in Python

Example1: axis=0

Approach:

Import numpy module using the import keyword.
Pass the list as an argument to the array() function to create an array.
Store it in a variable.
Pass the above array and axis=0 as arguments to the expand_dims() to expand the dimensions of the given array on axis=0.
Store it in another variable.
Print the given array.
Print the shape of the given array using the shape attribute.
Print the result i.e expanded array.
Print the shape of the expanded array using the shape attribute.
The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
# Pass the list as an argument to the array() function to create an array.
# Store it in a variable.
gvn_arry = np.array([5, 8, 9])
# Pass the above array and axis=0 as arguments to the expand_dims() to expand 
# the dimensions of the given array on axis=0.
# Store it in another variable.
expnd_arry = np.expand_dims(gvn_arry, axis=0)
# Print the given array
print("The given array:\n", gvn_arry)
# Print the shape of the given array using the shape attribute
print("The shape of the given array:", gvn_arry.shape)
# Print the result i.e expanded array
print("The expanded array:\n", expnd_arry)
# Print the shape of the expanded array using the shape attribute
print("The shape of the expanded array:", expnd_arry.shape)

Output:

The given array:
[5 8 9]
The shape of the given array: (3,)
The expanded array:
[[5 8 9]]
The shape of the expanded array: (1, 3)

Example2: axis=1

Approach:

Import numpy module using the import keyword.
Pass the list as an argument to the array() function to create an array.
Store it in a variable.
Pass the above array and axis=1 as arguments to the expand_dims() to expand the dimensions of the given array on axis=1.
Store it in another variable.
Print the given array.
Print the shape of the given array using the shape attribute.
Print the result i.e expanded array.
Print the shape of the expanded array using the shape attribute.
The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
# Pass the list as an argument to the array() function to create an array.
# Store it in a variable.
gvn_arry = np.array([5, 8, 9])
# Pass the above array and axis=1 as arguments to the expand_dims() to expand 
# the dimensions of the given array on axis=1.
# Store it in another variable.
expnd_arry = np.expand_dims(gvn_arry, axis=1)
# Print the given array
print("The given array:\n", gvn_arry)
# Print the shape of the given array using the shape attribute
print("The shape of the given array:", gvn_arry.shape)
# Print the result i.e expanded array
print("The expanded array:\n", expnd_arry)
# Print the shape of the expanded array using the shape attribute
print("The shape of the expanded array:", expnd_arry.shape)

Output:

The given array:
[5 8 9]
The shape of the given array: (3,)
The expanded array:
[[5]
[8]
[9]]
The shape of the expanded array: (3, 1)

Example3: Both axis= (0,1)

Approach:

Import numpy module using the import keyword.
Pass the list as an argument to the array() function to create an array.
Store it in a variable.
Pass the above array and axis=(0,1) as arguments to the expand_dims() to expand the dimensions of the given array on axis=0 and 1.
Store it in another variable.
Print the given array.
Print the shape of the given array using the shape attribute.
Print the result i.e expanded array.
Print the shape of the expanded array using the shape attribute.
The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
# Pass the list as an argument to the array() function to create an array.
# Store it in a variable.
gvn_arry = np.array([5, 8, 9])
# Pass the above array and axis=(0,1) as arguments to the expand_dims() to expand 
# the dimensions of the given array on axis= 0 and 1.
# Store it in another variable.
expnd_arry = np.expand_dims(gvn_arry, axis=(0,1))
# Print the given array
print("The given array:\n", gvn_arry)
# Print the shape of the given array using the shape attribute
print("The shape of the given array:", gvn_arry.shape)
# Print the result i.e expanded array
print("The expanded array:\n", expnd_arry)
# Print the shape of the expanded array using the shape attribute
print("The shape of the expanded array:", expnd_arry.shape)

Output:

The given array:
[5 8 9]
The shape of the given array: (3,)
The expanded array:
[[[5 8 9]]]
The shape of the expanded array: (1, 1, 3)

Numpy expand dims – Python NumPy expand_dims() Function

NumPy expand_dims() Function in Python

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