# numpy.ndarray.fill() in Python

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.]]
```

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