NumPy full() function in Python is used to return a new array of a given shape and data type filled with fill_value. In this article, I will explain syntax and how to use the numpy.full()
function which returns an array of fill_value with the given shape, order, and datatype.
1. Quick Examples of full() Function
If you are in a hurry, below are some quick examples of how to use NumPy full() function in Python.
# Below are the quick examples
# Example 1: Use numpy.full() function on 1-D array
arr2 = np.full(6, 4)
# Example 2: Use numpy.full() function with two-dimensional arrays
arr2 = np.full((4, 3),8)
# Example 3: Return Array with dtype=str
arr2 = np.full((4,3),'2',dtype=str)
# Example 4: Return Array with dtype=float
arr2 = np.full((3,4),'3',dtype=float)
# Example 5: Return Array with dtype=int
arr2 = np.full((2,4),'7',dtype=int)
2. Syntax of NumPy full()
Following is the syntax to create numpy.full()
 function.
# Syntax of numpy.full()
numpy.full(shape, fill_value, dtype=None, order='C', *, like=None)
2.1 Parameters of full()
Following are the parameters of full().
shape
–  It defines the shape of the array which is an int or sequence of ints. The shape of the new array, e.g., (4, 3) or 2.fill_value
– Value to fill in the array.dtype
– It is an optional parameter that specifies the data type of the returned array.order
– {‘C’, ‘F’}, optional: To store multi-dimensional data in row-major (C) or column-major (F) order/pattern in the memory location.like
– value should be array_like, optional
2.2 Return value of full()
It returns ndarray of fill_value with the given shape, order, and datatype.
3. Use NumPy full() Function on 1-D Array
To create a one-dimensional Numpy array of size 6
, with the value 4
use NumPy full() function. Here shape=6 is used to specify the length of the array, we’re indicating that we want the output to have six elements and fill_value=4 specifies the array to be filled with value 4.
import numpy as np
# Use numpy full() function on 1-D array
arr2 = np.full(shape=6, fill_value=4)
print(arr2)
# Output
# [4 4 4 4 4 4]
4. Use NumPy full() Function with Two-Dimensional Arrays
Let’s create a two-dimensional Numpy array with 4 rows and 3 columns with the value 8 for all elements. By using shape=(4,3)
, we’re indicating that we want the output to have 4 rows and 3 columns. The code fill_value=8 fills that 4×3 array with 8.
# Use numpy full() function with two-dimensional arrays
arr2 = np.full(shape=(4, 3),fill_value=8)
print(arr2)
# Output
# [[8 8 8]
# [8 8 8]
# [8 8 8]
# [8 8 8]]
5. Return Array with dtype=str
If you want full()
output array in a specific data type uses the dtype argument. To return an array of values of type String use dtype=str
. The following example returns a 2-D array with values filled with 2 but the data type of value is String.
# Return Array with dtype=str
arr2 = np.full((4,3),'2',dtype=str)
print(arr2)
# Output
# [['2' '2' '2']
# ['2' '2' '2']
# ['2' '2' '2']
# ['2' '2' '2']]
6. Return Array with dtype=float
To create a Numpy array that’s filled with floating point numbers instead of integers use dtype=float. The following example returns the array in float type.
# Return Array with dtype=float
arr2 = np.full((3,4),'3',dtype=float)
print(arr2)
# Output
# [[3. 3. 3. 3.]
# [3. 3. 3. 3.]
# [3. 3. 3. 3.]]
Conclusion
In this article, I have explained how to use numpy.full()
function which returns an array of fill_value with the given shape, order, and datatype. By using this function, I have also explained how to fill values on 1-D and 2-D arrays and fill values with string & float types.
Happy Learning!!
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