Using ggvis¶
ggvis is a data visualization package for R
For more information, see http://ggvis.rstudio.com/
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
- 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
library(dataiku)
dkuInstallGgvisDependenciesOnce()
Warning
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:
library(dataiku)
library(ggvis)
# Prepare the chart
chart <- mtcars %>% ggvis(~wt, ~mpg) %>% layer_points()
# And display it
dkuDisplayGgvis(Line)
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)