Using ggvis

ggvis is a data visualization package for R

For more information, see

Installing ggvis

Installing the ggvis package

The ggvis package is not installed by default. The recommended way to install it is to use a code environment

See how to install R packages

  • For a regular R environment, you need to install the ggvis package
  • If you are using a Conda environment, you can also choose instead to install in the Conda section the r-ggvis package.

Installing the frontend dependencies

To work, ggvis first needs some frontend libraries, that need to be preinstalled once.

To install the dependencies, open a R notebook and run



It is not possible to run this if your DSS instance has multi-user-security enabled.

In that case, your DSS administrator needs to run this from a command-line ./bin/R prompt, after setting the DIP_HOME env variable to the location of the DSS data directory

Displaying charts in a Jupyter notebook

ggvis charts will not work properly if you only enter it in a Jupyter notebook

Instead, use the dkuDisplayGgvis method.

For example; to display the first example in the ggvis documentation:


    # Prepare the chart
    chart <- mtcars %>% ggvis(~wt, ~mpg) %>% layer_points()

# And display it

Displaying charts on a dashboard

googleVis charts generated using R code can be shared on a DSS dashboard using the “static insights” system.

Each chart can become a single insight in the dashboard.

To do so, create static insights

# Prepare the chart
chart <- mtcars %>% ggvis(~wt, ~mpg) %>% layer_points()

# Save it as an insight
dkuSaveGgvisInsight("my-ggvis-plot", chart)

From the Dashboard, you can then add a new “Static” insight, select the my-ggvis-plot insight

Plots can be donwloaded in SVG or PNG format

Refreshing charts on a dashboard

You can refresh the charts automatically on a dashboard by using a scenario to re-run the above piece of code.

This call to dkuSaveGgvisInsight code can be:

  • In a DSS recipe (use a regular “Build” scenario step)
  • In a Jupyter notebook (use a “Export notebook” scenario step)