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.]]
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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]
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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.]]
