In this article we will discuss how to create a Numpy Array of different shapes and initialized with same identical values using numpy.full().

## numpy.full()

Python’s Numpy module provides a function to create a numpy array of given shape and all elements initialized with a given value,

Arguments:
shape: Shape of the new array
fill_value : Intialization value
dtype : Data type of elements | Optional

It returns a Numpy array of given shape and type, all elements in it will be initialized with fill_value.

To use Numpy in our code we need to include following module i.e.

Checkout some examples,

Example 1:

### Create a 1D Numpy Array of length 10 & all elements initialized with value 5

Contents of the Create Numpy array:

Data Type of Contents of the Numpy Array : int32
Shape of the Numpy Array : (10,)

Example 2:

### Create a 2D Numpy Array of 4 rows | 5 columns & all elements initialized with value 7

Contents of the Create Numpy array:

Data Type of Contents of the Numpy Array : int32
Shape of the Numpy Array : (4,5)

Example 3:

### Create a 3D Numpy Array of shape (2,4,5) & all elements initialized with value 8

Contents of the Create Numpy array:

Data Type of Contents of the Numpy Array : int32
Shape of the Numpy Array : (2, 4, 5)

Example 4:

### Create initialized Numpy array of specified data type

Along with initialization value, we can specify the data type too i.e.

Contents of the Create Numpy array:

Data Type of Contents of the Numpy Array : float64

Complete example is as follows,

Output:

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