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Identify the Time Range of an Outlying Data Point in Scatter Plot View

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When in Scatter Plot view, is it possible to see the time stamp of a given sample? Specifically, I would like to know when outliers are occurring so that I can navigate back to trend view and further investigate what else was going on during that time frame. 

How to visualize the time frame:

The best way to find a time frame of an outlying data point with the current version of Seeq is to make a condition that encapsulates that data point. The following example shows how to identify what your condition should be, create a condition, color code your scatter plot to highlight samples that occur during your capsules, and view the start and end time of your capsules in the capsules pane. 

1. We have a scatter plot comparing two variables with some outliers, and we would like to know what the time stamps are when those outliers are occurring. In the example shown below, we have outlying data points when the Coil Inlet Temperature is below about 460F, and when the Flue Gas Exit Temperature is below about 805F. 


2. We will create a condition for each of the outlying data point scenarios described above. In this example, we will do so using a simple value search for each. 



3. Now when we return to scatter plot view, we have the ability to color our scatter plot based on various capsules. 

In versions prior to R.21.0.44, this is done using the "Capsules" button at the top of the Scatter Plot Display. In R.21.0.44 and later versions, this is done with the "Color" button. 


You can select Color based on conditions, and add your conditions.


Then your scatter plot will show samples that fall within the capsules of your conditions in the color specified for your condition in the Details pane. 


4. Add the capsule end time to the capsules pane to get the full time range that you want to further investigate in trend view. You can also utilize Seeq's Chain View feature from trend view to view what was going on with your signals of interest during your conditions. 



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