I have built a shiny dashboard which has a set of data loaded in as a data frame. It uses dplyr to then select columns, mutate new columns if needed, apply a set of filters and then plot using a variety of high-level ggplot2-based packages.
We try to do the data load, select and mutate just the once. The filtering is sat in a reactive variable, accessed by the plot, and is based upon different input values.
As far as I see this is a pretty standard and typical use case.
I'm wondering whether anyone could advise on workflow patterns to make the output more responsive.
There are two scenarios I encounter with this writing pattern which appear to cause significant user interface delay which I'd like to avoid:
- Firstly, when the dashboard first loads it tries to plot the charts using NULL data. I've found I can get around this by using if(is.null(my_data_frame)) and returning geom_blank() rather than our plot. Is there a neater / faster way to do this? 
- Secondly (and more challengingly): to the right of my plot are a (potentially large) set of filter options to allow the user to analyse subsets. If the user clicks several of these options in rapid succession, Shiny will repeatedly recalculate our reactive() value and replot the chart for each click event: where the user actually just needed to set or clear 5 options. Is there a way to prevent this happening - so if the recalculation isn't complete we don't continue with the plot in progress as we've just made the data stale? Or do you think about grouping options with an update button to prevent this? 
eventReactive()instead of justreactive(). Have the calculation run when user presses someactionButtonafter checking/unchecking options. For more help provide minimum working example. - Shree