Skip to content
Create a gist now

Instantly share code, notes, and snippets.

Embed URL


Subversion checkout URL

You can clone with
Download ZIP
Cambridge R user meeting, May 2012

Interactive charts and slides with R, googleVis and knitr

G <- gvisGeoChart(Exports, "Country", "Profit", 
                  options=list(width=250, height=120), chartid="c1")

T <- gvisBarChart(Exports[,1:2], yvar="Profit", xvar="Country",                  
                  options=list(width=250, height=260, 
                               legend='none'), chartid="c2")

GT <- gvisMerge(G,T, horizontal=FALSE, chartid="gt") 

## Tree map

M <- gvisTreeMap(Regions,  "Region", "Parent", "Val", "Fac",
                    options=list(width=400, height=380,
                                 showScale=TRUE), chartid="c3")

GTM <- gvisMerge(GT, M, horizontal=TRUE,
                     tableOptions="cellspacing=5", chartid="gtm")

print(GTM, 'chart')

Markus Gesmann, Cambridge R user group meeting, 29 May 2012


  • Motivation
  • Introduction to googleVis
  • Examples with googleVis
  • How I created this talk with RStudio, knitr, pandoc and slidy


  • In 2006 Hans Rosling gave an inspiring talk at TED
  • He challenged the views and perceptions of many listeners
  • To visualise his talk he used animated bubble charts, aka motion charts

Google Chart Tools

  • Google integrated the motion charts into their Visualisation API in 2007
  • Google Visulisation API makes it easy to create interactive charts for web pages
  • It uses JavaScript and DataTable / JSON as input
  • Output is either HTML5/SVG or Flash
  • Browser with internet connection required to display chart
  • Please read the Google Terms of Service before you start

Introduction to googleVis

  • googleVis is a package for R and provides an interface between R and the Google Chart Tools, see Using the Google Visualisation API with R, The R Journal, 3(2):40-44, December 2011
  • The functions of the package allow users to visualise data with the Google Chart Tools without uploading their data to Google
  • The output of googleVis functions is html code that contains the data and references to JavaScript functions hosted by Google
  • To view the output a browser with an internet connection is required, the actual chart is rendered in the browser; some charts require Flash

Key ideas of googleVis

  • Create wrapper function in R which generate html files with references to Google's Chart Tools API
  • Transform R data frames into JSON objects with RJSONIO
cat(toJSON(CityPopularity)) ## example data from googleVis
  • Display the HTML output with the R HTTP help server
  • Development started in August 2010, intially to visualise data at Lloyd's

googleVis version 0.2.16 provides interfaces to

  • Motion Charts
  • Annotated Time Lines
  • Maps, Geo Maps and Charts
  • Intensity Maps
  • Tables, Gauges, Tree Maps
  • Line-, Bar-, Column-, Area- and Combo Charts
  • Scatter-, Bubble-, Candlestick-, Pie- and Org Charts

Run demo(googleVis) to see examples of all charts and read the vignette for more details.

World Bank example


Video tutorial

The googleVis concept

  • Charts: 'gvis' + ChartType
  • For a motion chart we have
M <- gvisMotionChart(data, idvar='id', timevar='date', options=list(), chartid)
  • Output of googleVis is a list of list
  • Display the chart by simply plotting the output plot(M)
    • Plot will generate a temporay html-file and open it in a new browser window
  • Specific parts can be extracted, e.g. the chart M$html$chart or data M$html$chart["jsData"]

Embedding googleVis chart into your web page

Suppose you have an existing web page and would like to integrate the output of a googleVis function, such as gvisMotionChart.

In this case you only need the chart output from gvisMotionChart. So you can either copy and paste the output from the R console

 print(M, 'chart') ## or cat(M$html$chart)

into your existing html page, or write the content directly into a file

print(M, 'chart', file='myfilename')

and process it from there.

Simple line chart

df <- data.frame(label=c("A", "B", "C"), val1=c(0.10,0.13,0.14), val2=c(23,12,32))
lc <- gvisLineChart(df)
print(lc, 'chart') ## So knitr includes the html output of the chart 

Line chart with options set

print(gvisLineChart(df, xvar="label", yvar=c("val1","val2"),
                        options=list(title="Hello World", legend="bottom",
                          titleTextStyle="{color:'red', fontSize:18}",                         
                          vAxis="{gridlines:{color:'red', count:3}}",
                          hAxis="{title:'My Label', titleTextStyle:{color:'blue'}}",
                          series="[{color:'green', targetAxisIndex: 0}, 
                                   {color: 'blue',targetAxisIndex:1}]",
                          vAxes="[{title:'Value 1 (%)', format:'#,###%'}, 
                                  {title:'Value 2 (\U00A3)'}]",                          
                          curveType="function", width=500, height=300                         
                          )), 'chart')

Chart countries' S&P credit rating

  • Plot countries' S&P credit rating sourced from Wikipedia
  • See my blog post for more details
## Get and prepare data
url <- ""
page <- readLines(url)
x <- readHTMLTable(page, which=3)
levels(x$Rating) <- substring(levels(x$Rating), 4, 
x$Ranking <- x$Rating
levels(x$Ranking) <- nlevels(x$Rating):1
x$Ranking <- as.character(x$Ranking)
x$Rating <- paste(x$Country, x$Rating, sep=": ")

Chart countries' S&P credit rating

print(gvisGeoMap(x, "Country", "Ranking", "Rating",
                  colors="[0x91BFDB, 0XFC8D59]")), 'chart')

Geo chart with markers

data(quakes); quakes$latlong<-paste(quakes$lat, quakes$long, sep=":")
print(gvisGeoChart(quakes, locationvar="latlong", colorvar="depth", sizevar="mag",
                   options=list(displayMode="Markers", region="009",
                   colorAxis="{colors:['red', 'grey']}",
                   backgroundColor="lightblue")), 'chart')

Merging gvis-objects

G <- gvisGeoChart(Exports, "Country", "Profit", options=list(width=250, height=120))
B <- gvisBarChart(Exports[,1:2], yvar="Profit", xvar="Country",                  
                  options=list(width=250, height=260, legend='none'))
M <- gvisMotionChart(Fruits, "Fruit", "Year",options=list(width=400, height=380))
GBM <- gvisMerge(gvisMerge(G,B, horizontal=FALSE), 
                 M, horizontal=TRUE, tableOptions="cellspacing=5")
print(GBM, 'chart')

Further case studies

Other R packages

How I created this presentation with RStudio, knitr, pandoc and slidy

  • knitr is a package by Yihui Xie that brings literate programming to a new level
    • It allows to create content really quickly, without worrying to much about layout and R formatting
  • RStudio integrated knitr into its IDE, which allows to knit Rmd-files by the push of a button into markdown
  • Markdown output can be converted into serveral other file formats, such as html, with pandoc
  • slidy is one of the options to create interactive html-slides with pandoc
pandoc -s -S -i -t slidy --mathjax 
  -o Cambridge_R_googleVis_with_knitr_and_RStudio_May_2012.html


  • Interactive charts and reports open a new way to engage with readers and users, who would find data and figures boring otherwise
  • RStudio, knitr and googleVis might be the way forward to create interactive analysis reports and presentations
  • The markdown language should be sufficient for most tasks to draft a report, and the integration with RStudio makes it a pleasure to work with knitr.

Thanks to ...



Getting error in line 66 in running from Rstudio (version .99) on R 3.2.0

cat(toJSON(CityPopularity)) ## example data from googleVis

could not find toJSON call withCallingHandlers->withVisible_> eval->eval->cat

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Something went wrong with that request. Please try again.