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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