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,

numpy.full(shape, fill_value, dtype=None, order='C')

*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.

import numpy as np

*Checkout some examples,*

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Example 1:

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

# Create a 1D Numpy Array of length 10 & all elements initialized with value 5 arr = np.full(10, 5)

*Contents of the Create Numpy array:*

[5 5 5 5 5 5 5 5 5 5]

*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

#Create a 2D Numpy Array of 4 rows & 5 columns. All intialized with value 7 arr = np.full((4,5), 7)

*Contents of the Create Numpy array:*

[[7 7 7 7 7] [7 7 7 7 7] [7 7 7 7 7] [7 7 7 7 7]]

*Data Type of Contents of the Numpy Array :Â ***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

# Create a 3D Numpy array & all elements initialized with value 8 arr = np.full((2,4,5), 8)

*Contents of the Create Numpy array:*

[[[8 8 8 8 8] [8 8 8 8 8] [8 8 8 8 8] [8 8 8 8 8]] [[8 8 8 8 8] [8 8 8 8 8] [8 8 8 8 8] [8 8 8 8 8]]]

*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.

# Create a 1D Numpy array & all float elements initialized with value 9 arr = np.full(10, 9, dtype=float)

*Contents of the Create Numpy array:*

[9. 9. 9. 9. 9. 9. 9. 9. 9. 9.]

*Data Type of Contents of the Numpy Array* : *float64*

**Complete example is as follows,**

import numpy as np def main(): print('*** Create 1D Numpy Array filled with identical values ***') # Create a 1D Numpy Array of length 10 & all elements intialized with value 5 arr = np.full(10, 5) print('Contents of the Numpy Array : ' , arr) print('Data Type of Contents of the Numpy Array : ', arr.dtype) print('Shape of the Numpy Array : ', arr.shape) print('*** Create 2D Numpy Array filled with identical values ***') #Create a 2D Numpy Array of 4 rows & 5 columns. All intialized with value 7 arr = np.full((4,5), 7) print('Contents of the Numpy Array : ', arr, sep='\n') print('Data Type of Contents of the Numpy Array : ', arr.dtype) print('Shape of the Numpy Array : ', arr.shape) print('*** Create 3D Numpy Array filled with identical values ***') # Create a 3D Numpy array & all elements initialized with value 8 arr = np.full((2,4,5), 8) print('Contents of the Numpy Array : ', arr, sep='\n') print('Data Type of Contents of the Numpy Array : ', arr.dtype) print('Shape of the Numpy Array : ', arr.shape) print('*** Create 1D Numpy Array of specified Data Type filled with identical values ***') # Create a 1D Numpy array & all float elements initialized with value 9 arr = np.full(10, 9, dtype=float) print('Contents of the Numpy Array : ', arr) print('Data Type of Contents of the Numpy Array : ', arr.dtype) print('Shape of the Numpy Array : ', arr.shape) if __name__ == '__main__': main()

**Output:**

*** Create 1D Numpy Array filled with identical values *** Contents of the Numpy Array : [5 5 5 5 5 5 5 5 5 5] Data Type of Contents of the Numpy Array : int32 Shape of the Numpy Array : (10,) *** Create 2D Numpy Array filled with identical values *** Contents of the Numpy Array : [[7 7 7 7 7] [7 7 7 7 7] [7 7 7 7 7] [7 7 7 7 7]] Data Type of Contents of the Numpy Array : int32 Shape of the Numpy Array : (4, 5) *** Create 3D Numpy Array filled with identical values *** Contents of the Numpy Array : [[[8 8 8 8 8] [8 8 8 8 8] [8 8 8 8 8] [8 8 8 8 8]] [[8 8 8 8 8] [8 8 8 8 8] [8 8 8 8 8] [8 8 8 8 8]]] Data Type of Contents of the Numpy Array : int32 Shape of the Numpy Array : (2, 4, 5) *** Create 1D Numpy Array of specified Data Type filled with identical values *** Contents of the Numpy Array : [9. 9. 9. 9. 9. 9. 9. 9. 9. 9.] Data Type of Contents of the Numpy Array : float64 Shape of the Numpy Array : (10,)