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 zero.
How to set all values to zero in Numpy?
You can use the
numpy.ndarray.fill() function to set all the values in a Numpy array to zero. Pass
0 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 0 ar.fill(0)
It modifies the array in-place, filling each value with zero (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)
[-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
numpy.ndarray.fill() function on the array and pass
0 as the parameter to set each value to zero in the array.
Let’s apply this function to the array created above.
# set all values to zero ar.fill(0) # display the array print(ar)
[0 0 0 0 0 0 0]
You can see that each value in the array
ar is now
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 zero ar.fill(0) # display the array print(ar)
[[0 0 0] [0 0 0] [0 0 0]]
You can see that each value in the above 2D array is now zero.
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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