Open In App

numpy.ndarray.fill() in Python

Improve
Improve
Like Article
Like
Save
Share
Report

numpy.ndarray.fill() method is used to fill the numpy array with a scalar value.

If we have to initialize a numpy array with an identical value then we use numpy.ndarray.fill(). Suppose we have to create a NumPy array a of length n, each element of which is v. Then we use this function as a.fill(v). We need not use loops to initialize an array if we are using this fill() function.

Syntax : ndarray.fill(value)

Parameters:
value : All elements of a will be assigned this value.

Code #1:




# Python program explaining
# numpy.ndarray.fill() function
import numpy as geek
  
a = geek.empty([3, 3])
  
# Initializing each element of the array
# with 1 by using nested loops 
for i in range(3):
    for j in range(3):
        a[i][j] = 1
  
print("a is : \n", a)    
  
  
# now we are initializing each element
# of the array with 1 using fill() function. 
a.fill(1)
  
print("\nAfter using fill() a is : \n", a)
       


Output:

a is : 
 [[ 1.  1.  1.]
 [ 1.  1.  1.]
 [ 1.  1.  1.]]

After using fill() a is : 
 [[ 1.  1.  1.]
 [ 1.  1.  1.]
 [ 1.  1.  1.]]

 

Code #2:




# Python program explaining
# numpy.ndarray.fill() function
import numpy as geek
  
a = geek.arange(5)
  
print("a is \n", a)
  
# Using fill() method
a.fill(0)
  
print("\nNow a is :\n", a)
       


Output:

a is 
 [0 1 2 3 4]

Now a is :
 [0 0 0 0 0]

 
Code #3: numpy.ndarray.fill() also works on multidimensional array.




# Python program explaining
# numpy.ndarray.fill() function
  
import numpy as geek
  
a = geek.empty([3, 3])
  
# Using fill() method
a.fill(0)
  
print("a is :\n", a)


Output:

a is :
 [[ 0.  0.  0.]
 [ 0.  0.  0.]
 [ 0.  0.  0.]]


Last Updated : 28 Dec, 2018
Like Article
Save Article
Previous
Next
Share your thoughts in the comments
Similar Reads