Work with scatter plots

In addition to regular trends, you can display data in XY scatter plots. While a regular trend shows the variation of a tag’s value over time, a scatter plot shows the variation of a tag’s value over the variation of another tag’s value. This allows you to see correlations between the two tags.

For example, you could show how product yield varies depending on the reactor temperature in a manufacturing process, and use this information to determine the optimum temperature:

In this example, the X axis represents the reactor temperature as historized by the ReactTemp tag (the "X axis tag"). The Y axis represents the product yield as historized by the ProductGood tag (the "Y axis tag"). For each available data sample of either tag during the chosen time period, a corresponding value for the other tag is matched or interpolated and plotted on the chart.

For more information, see How Are Value Pairs Matched?.

Plotted over time, the two tags look like this:

Compared to this type of display, the scatter plot shows the correlation much more clearly.

The following sections show you how to configure a scatter plot and manipulate the display. Many of these features work in a regular trend. Therefore, these sections mainly explain the specific differences when working with scatter plots.