The Numpy library in Python comes with a number of built-in functions to manipulate the data in arrays. In this tutorial, we will look at a function that helps us set all the values in a Numpy array to one.

## How to set all values to one in Numpy?

You can use the `numpy.ndarray.fill()`

function to set all the values in a Numpy array to one. Pass `1`

as the argument (this is the value used to fill all the values in the array).

The following is the syntax –

# set all values in numpy array ar to 1 ar.fill(1)

It modifies the array in-place, filling each value with one (the passed value).

Let’s now look at a step-by-step example of using the above function.

### Step 1 – Create a Numpy array

First, we will create a Numpy array that we will use throughout this tutorial.

import numpy as np # create a numpy array ar = np.array([-2, -1, 0, 1, 2, 3, -4]) # display the array print(ar)

Output:

[-2 -1 0 1 2 3 -4]

Here, we used the `numpy.array()`

function to create a Numpy array containing some numbers.

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### Step 2 – Set each value to 1 using `numpy.ndarray.fill()`

Apply the `numpy.ndarray.fill()`

function on the array and pass `1`

as the parameter to set each value to one in the array.

Let’s apply this function to the array created above.

# set all values to one ar.fill(1) # display the array print(ar)

Output:

[1 1 1 1 1 1 1]

You can see that each value in the array `ar`

is now 1.

The `numpy.ndarray.fill()`

function works similarly on higher-dimensional arrays. For example, let’s apply this function to a 2D array of some numbers.

# create 2D numpy array ar = np.array([[-1, 2, -3], [0, 51, 7], [1, 125, 8]]) # set all values to one ar.fill(1) # display the array print(ar)

Output:

[[1 1 1] [1 1 1] [1 1 1]]

You can see that each value in the above 2D array is now one.

You might also be interested in –

- Numpy – Get the Sign of Each Element in Array
- Get the Median of Numpy Array – (With Examples)
- Numpy – Get Standard Deviation of Array Values
- Numpy – Get Min Value in Array

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