Using Dygraphs

The dygraphs package is an R interface to the dygraphs JavaScript charting library. It provides rich facilities for charting time-series data in R.

More information on dygraphs can be found at

Installing dygraphs

The dygraphs package is not installed by default in DSS. The recommended method for doing so is to use a code environment. See how to install R packages

You need to install the dygraphs package. If you are using a Conda environment, you can also choose to install in the Conda section the r-dygraphs package.

Displaying charts in a Jupyter notebook

dygraphs charts will not work properly if you only use the dygraph() method in a Jupyter R notebook.

To display dygraphs charts in a Jupyter notebook, use:


the_graph <- dygraph(mydata)


For example, to display the sample lungDeaths dataset

lungDeaths <- cbind(mdeaths, fdeaths)

Converting a date column to a time-series

Dygraphs works primarily with time series. If you have a DSS dataset with a “date” column, you’ll need to convert your dataframe to a time series or XTS object.

For example, the following will create a time-series of revenue by order_ts

df <- dkuReadDataset("orders")

timeseries <- xts(df$revenue,$order_ts))

# You can then plot timeseries
dkuDisplayDygraph(dygraph(timeseries) %>% dyRangeSelector())

Displaying charts on a dashboard

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

Each dygraphs chart can become a single insight in the dashboard. Each chart will retain full interactive capabilities (if you have defined them in your dygraph)

To do so, create static insights

# dg is a dygraphs object, created using the dygraph() function

dkuSaveHTMLInsight("my-dygraphs-plot", dg)

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

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 dkuSaveHTMLInsight code can be:

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

Using in Shiny

Dygraphs can be used directly in Shiny. See for more information.

See for a complete code sample