Jittering is a method that is used for visual clarity in scatterplots, and can be very useful to show the amount of data points that are in the dataset.
As shown below, the 3 categories against sales are represented by circles, but because they are overlapping it is hard to see how many points there are.
![](https://www.thedataschool.co.uk/content/images/2022/11/image-100.png)
In order to fix this, we can jitter the scatterplot by creating a calculated field:
![](https://www.thedataschool.co.uk/content/images/2022/11/image-101.png)
Then we drag the new calculated field onto the columns:
![](https://www.thedataschool.co.uk/content/images/2022/11/image-109.png)
Then we change the field to a dimension:
![](https://www.thedataschool.co.uk/content/images/2022/11/image-110.png)
And finally we do some formatting tips, like change the size to a smaller level, and remove the header:
![](https://www.thedataschool.co.uk/content/images/2022/11/image-111.png)
![](https://www.thedataschool.co.uk/content/images/2022/11/image-112.png)
Here is the final comparison after using the technique:
![](https://www.thedataschool.co.uk/content/images/2022/11/image-113.png)
It is important to note that the field on the columns is a discrete one, as a continuous axis may be confused with the jittering - i.e. the horizontal deviations do not have importance.