• Provides an interface between Google Chart Tools and R
• Includes the beauty of Hans Rosling's motion charts (purchase of Gapminder by Google)
• https://github.com/mages/googleVis

install.packages('googleVis')

Who is Hans Rosling?

9 Ted Talks (through 6/2014… the highest number - next was 6)

• Google Chart Tools provide a way to visualize data on web sites
• The API makes it easy to create interactive charts
• Browser with internet connection required to display chart
• Please read the Google Terms of Service before you start

• Transform R data frames into JSON objects with RJSONIO

library(RJSONIO)
dat <- data.frame(x=LETTERS[1:2], y=1:2)
cat(toJSON(dat)) 

## {
##  "x": [ "A", "B" ],
## "y": [ 1, 2 ] 
## }

• Create wrapper functions in R which generate html files with references to Google's Chart Tools API
• Display the HTML output with the R HTTP help server

• 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 temporary 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"]

• Histogram, Line, Line with two axes, Bar, Column, Area, Stepped Area, Combo, Scatter, Bubble, Motion, Candlestick, Pie, Gauge, Table, Organization Chart, Tree Map, Sankey, Calendar, and Time line (to check on Annotation, Annotated time line)
• Mapping: Intensity Map, Geo Chart, Geo markers, Google map markers,Geo Map

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

set.seed(123)
datHist=data.frame(A=rpois(100, 20),
                   B=rpois(100, 5),
                   C=rpois(100, 50))
suppressMessages(library(googleVis))
Hist <- gvisHistogram(datHist, options=list(
  legend="{ position: 'right', maxLines: 2 }",
  colors="['#5C3292', '#1A8763', '#871B47']",
  width=850, height=360))
plot(Hist)

#print(Hist,file="hist.html")

df=data.frame(country=c("US", "GB", "BR"), 
              val1=c(10,13,14), 
              val2=c(23,12,32))
Line <- gvisLineChart(df,options=list(width=750, height=500))
plot(Line)

Line2 <- gvisLineChart(df, "country", c("val1","val2"),
                       options=list(
                         series="[{targetAxisIndex: 0},
                                 {targetAxisIndex:1}]",
                         vAxes="[{title:'val1'}, {title:'val2'}]",
                         width=750, height=400
                       ))
plot(Line2)

Dashed <-  gvisLineChart(df, xvar="country", yvar=c("val1","val2"),
                        options=list(
                          series="[{color:'green', targetAxisIndex: 0, 
                          lineWidth: 1, lineDashStyle: [2, 2, 20, 2, 20, 2]}, 
                          {color: 'blue',targetAxisIndex: 1, 
                          lineWidth: 2, lineDashStyle: [4, 1]}]",
                          vAxes="[{title:'val1'}, {title:'val2'}]", width=750,height=400
                        ))
plot(Dashed)

Bar <- gvisBarChart(df,options=list(width=750, height=400))
plot(Bar)

Column <- gvisColumnChart(df,options=list(width=750, height=400))
plot(Column)

Area <- gvisAreaChart(df,options=list(width=750, height=400))
plot(Area)

SteppedArea <- gvisSteppedAreaChart(df, xvar="country", 
                                    yvar=c("val1", "val2"),
                                    options=list(isStacked=TRUE, width=750,height=400))
plot(SteppedArea)

Combo <- gvisComboChart(df, xvar="country",
                        yvar=c("val1", "val2"),
                        options=list(seriesType="bars",
                                     series='{1: {type:"line"}}',width=750,height=400))
plot(Combo)

head(women)

##   height weight
## 1     58    115
## 2     59    117
## 3     60    120
## 4     61    123
## 5     62    126
## 6     63    129

Scatter <- gvisScatterChart(women, 
                            options=list(
                              legend="none",
                              pointSize=4,lineWidth=.5, 
                              title="Women", vAxis="{title:'weight (lbs)'}",
                              hAxis="{title:'height (in)'}", 
                              width=700, height=350))
plot(Scatter)

M <- matrix(nrow=6,ncol=6)
M[col(M)==row(M)] <- 1:6
dat <- data.frame(X=1:6, M)
SC <- gvisScatterChart(dat, 
                       options=list(
                         title="Customizing points",
                         legend="right",
                         pointSize=30,
                         series="{
                              0: { pointShape: 'circle' },
                              1: { pointShape: 'triangle' },
                              2: { pointShape: 'square' },
                              3: { pointShape: 'diamond' },
                              4: { pointShape: 'star' },
                              5: { pointShape: 'polygon' }
                              }",
                         width=750,height=400))

plot(SC)

Line3 <-  gvisLineChart(df, xvar="country", yvar=c("val1","val2"),
                        options=list(
                          title="Hello World",
                          titleTextStyle="{color:'red', 
                                           fontName:'Courier', 
                                           fontSize:16}",                         
                          backgroundColor="#D3D3D3",                          
                          vAxis="{gridlines:{color:'red', count:3}}",
                          hAxis="{title:'Country', titleTextStyle:{color:'blue'}}",
                          series="[{color:'green', targetAxisIndex: 0}, 
                                   {color: 'orange',targetAxisIndex:1}]",
                          vAxes="[{title:'val1'}, {title:'val2'}]",
                          legend="bottom",
                          curveType="function",
                          width=750,
                          height=400                         
                        ))

plot(Line3)

head(Fruits)

##     Fruit Year Location Sales Expenses Profit       Date
## 1  Apples 2008     West    98       78     20 2008-12-31
## 2  Apples 2009     West   111       79     32 2009-12-31
## 3  Apples 2010     West    89       76     13 2010-12-31
## 4 Oranges 2008     East    96       81     15 2008-12-31
## 5 Bananas 2008     East    85       76      9 2008-12-31
## 6 Oranges 2009     East    93       80     13 2009-12-31

Bubble <- gvisBubbleChart(Fruits, idvar="Fruit", 
                          xvar="Sales", yvar="Expenses",
                          colorvar="Year", sizevar="Profit",
                          options=list(
                            hAxis='{minValue:75, maxValue:125}',width=700,height=400))
plot(Bubble)

M1=gvisMotionChart(Fruits, "Fruit", "Year", 
                     options=list(width=500, height=350))
#print(M1,file="M1.html")
plot(M1)

Candle <- gvisCandlestickChart(OpenClose, 
                               options=list(legend='none', width=700,height=400))
plot(Candle)

Pie <- gvisPieChart(CityPopularity, options=list(width=700,height=400))
plot(Pie)

Gauge <-  gvisGauge(CityPopularity, 
                    options=list(min=0, max=800, greenFrom=500,
                                 greenTo=800, yellowFrom=300, yellowTo=500,
                                 redFrom=0, redTo=300, width=400, height=300))
plot(Gauge)

PopTable <- gvisTable(Population, 
                      formats=list(Population="#,###",
                                   '% of World Population'='#.#%'),
                      options=list(page='enable'))
plot(PopTable)

Org <- gvisOrgChart(Regions, 
                    options=list(width=600, height=250,
                                 size='large', allowCollapse=TRUE))
plot(Org)

Tree <- gvisTreeMap(Regions,  
                    "Region", "Parent", 
                    "Val", "Fac", 
                    options=list(fontSize=16))
plot(Tree)

datSK <- data.frame(From=c(rep("A",3), rep("B", 3)),
                    To=c(rep(c("X", "Y", "Z"),2)),
                    Weight=c(5,7,6,2,9,4))

Sankey <- gvisSankey(datSK, from="From", to="To", weight="Weight",
                     options=list(
                       sankey="{link: {color: { fill: '#d799ae' } },
                            node: { color: { fill: '#a61d4c' },
                            label: { color: '#871b47' } }}"))

plot(Sankey)

Cal <- gvisCalendar(Cairo, 
                    datevar="Date", 
                    numvar="Temp",
                    options=list(
                      title="Daily temperature in Cairo",
                      height=320,
                      calendar="{yearLabel: { fontName: 'Times-Roman',
                               fontSize: 32, color: '#1A8763', bold: true},
                               cellSize: 10,
                               cellColor: { stroke: 'red', strokeOpacity: 0.2 },
                               focusedCellColor: {stroke:'red'}}")
)

plot(Cal)

datTL <- data.frame(Position=c(rep("President", 3), rep("Vice", 3)),
                    Name=c("Washington", "Adams", "Jefferson",
                           "Adams", "Jefferson", "Burr"),
                    start=as.Date(x=rep(c("1789-03-29", "1797-02-03", 
                                          "1801-02-03"),2)),
                    end=as.Date(x=rep(c("1797-02-03", "1801-02-03", 
                                        "1809-02-03"),2)))

Timeline <- gvisTimeline(data=datTL, 
                         rowlabel="Name",
                         barlabel="Position",
                         start="start", 
                         end="end",
                         options=list(timeline="{groupByRowLabel:false}",
                                      backgroundColor='#ffd', 
                                      height=350,
                                      colors="['#cbb69d', '#603913', '#c69c6e']"))
#print(Timeline,file="Timeline.html")

plot(Timeline)

Intensity <- gvisIntensityMap(df,options=list( width=750, height=400))
plot(Intensity)

Geo=gvisGeoChart(Exports, locationvar="Country", 
                 colorvar="Profit",
                 options=list(projection="kavrayskiy-vii",
                 width=750, height=400))
plot(Geo)

library(datasets)
states <- data.frame(state.name, state.x77)
GeoStates <- gvisGeoChart(states, "state.name", "Illiteracy",
                          options=list(region="US", displayMode="regions", resolution="provinces",
                                       width=600, height=400))
plot(GeoStates)

GeoMarker <- gvisGeoChart(Andrew, "LatLong", 
                          sizevar='Speed_kt',
                          colorvar="Pressure_mb", 
                          options=list(region="US"))
plot(GeoMarker)

AndrewMap <- gvisMap(Andrew, "LatLong" , "Tip", 
                     options=list(showTip=TRUE, 
                                  showLine=TRUE, 
                                  enableScrollWheel=TRUE,
                                  mapType='terrain', 
                                  useMapTypeControl=TRUE))
plot(AndrewMap)

AndrewGeo <- gvisGeoMap(Andrew, 
                        locationvar="LatLong", 
                        numvar="Speed_kt", 
                        hovervar="Category", 
                        options=list(height=350, 
                                     region="US", 
                                     dataMode="markers"))
plot(AndrewGeo)

G <- gvisGeoChart(Exports, "Country", "Profit", 
                  options=list(width=600, height=400))
T <- gvisTable(Exports, 
               options=list(width=440, height=400))

GT <- gvisMerge(G,T, horizontal=TRUE) 
plot(GT)

Code for this deck can be found at: https://github.com/patilv/googleVis-tutorial