# Interactive Graphics

There are a several ways to interact with **R** graphics in real time. Three methods are described below.

## GGobi

**GGobi** is an open source visualization program for exploring high-dimensional data. It is freely available for MS Windows, Linux, and Mac platforms. It supports linked interactive scatterplots, barcharts, parallel coordinate plots and tours, with both brushing and identification. A good tutorial is included with the GGobi manual. You can download the software here.

Once GGobi is installed, you can use the **ggobi( )** function in the package **rggobi** to run **GGobi** from within **R** **.** This gives you interactive graphics access to all of your **R** data! See **An Introduction to RGGOBI**.

`# Interact with R data using GGobi`

library(rggobi)

g <- ggobi(mydata)

## iPlots

The** iplots** package provide interactive mosaic plots, bar plots, box plots, parallel plots, scatter plots and histograms that can be linked and color brushed. **iplots** is implimented through the **Java GUI for R**. For more information, see the **iplots website**.

`# Install iplots`

install.packages("iplots",dep=TRUE)

# Create some linked plots

library(iplots)

cyl.f <- factor(mtcars$cyl)

gear.f <- factor(mtcars$factor)

attach(mtcars)

ihist(mpg) # histogram

ibar(carb) # barchart

iplot(mpg, wt) # scatter plot

ibox(mtcars[c("qsec","disp","hp")]) # boxplots

ipcp(mtcars[c("mpg","wt","hp")]) # parallel coordinates

imosaic(cyl.f,gear.f) # mosaic plot

On windows platforms, hold down the **cntrl key **and move the mouse over each graph to get identifying information from points, bars, etc.

## Interacting with Plots (Indentifying Points)

**R** offers two functions for identifying points and coordinate locations in plots. With **identify()**, clicking the mouse over points in a graph will display the row number or (optionally) the rowname for the point. This continues until you select **stop **. With **locator() **you can add points or lines to the plot using the mouse. The function returns a list of the (x,y) coordinates. Again, this continues until you select **stop**.

`# Interacting with a scatterplot `

attach(mydata)

plot(x, y) # scatterplot

identify(x, y, labels=row.names(mydata)) # identify points

coords <- locator(type="l") # add lines

coords # display list

## Other Interactive Graphs

See scatterplots for a description of rotating 3D scatterplots in **R**.

## Other Visualization Programs

Explore building interactive plots with ggvis from RStudio in this course.