Local Data Filter - Broadcast Mode

[MShroff]

Hello,

When using Local Data Filter for a set of plots (e.g., if generated using By variables), I can invoke Local Data Filters for each plot in broadcast mode. However, there does not appear to be the ability to select the filter settings for each plot (if the settings are the same) in broadcast mode and therefore, each plot has to have its settings done individually. Can a broadcast feature be added for Local Data Filters?

I've been given to understand that there is a way to copy / paste the filter settings from one plot to others, but for the sake of consistency across platforms, enabling a broadcast feature would be extremely helpful.

Regards

Mehul Shroff

cc: @PatrickGiuliano

[danschikore]

Using JSL or the Dashboard Builder, you can link a single data filter with multiple platforms (including by-groups).  In this JSL example, the filter and by group are both created using the same table.  The Data Filter Context Box() is required in order to link the platforms with the filter.  This process will work for unrelated platforms using the same data table as well as for by-groups.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
New Window( "by group filter",
	Data Filter Context Box(
		H List Box(
			dt << Data Filter( "Local", Add Filter( Columns( :age ) ) ),
			dt << Bivariate( Y( :weight ), X( :height ), By( :sex ) )
		)
	)
);

Broadcast between filters may still be useful in some scenarios, but "shared" data filters can simplify the UI when you want the settings to remain synced at all times.

[PatrickGiuliano]

Wonderful @danschikore thank you for providing this handy solution!

And thanks @MShroff for posting! I'm @mentioning you here to doubly ensure you get visibility to it. 

One thing I can suggest for Wishlist requests is to include at least one graphic if possible, illustrating the current functionality, and one depicting the desired functionality (with some annotation on the picture).  This helps other JMP users on the community see and intuit the request fully -- it also helps us at JMP appreciate the context for the feature request and to see it better from different angles.