Using Roles via googleVis

Roles add the ability to pass columns for further processing downstream. Role columns must follow column they pertain to. Proper naming conventions must be be observed. For example, roles fulfilling tooltip roles and must be called “foo.blah.tooltip”. For more details see the Google documentation.

The following examples should help to illustrate the concept.

The first example uses a data set that has the additional column pop.html.tooltip with the first 11 letters of the Latin alphabet. This column is mapped automatically as a tooltip, when the user hovers over the chart point.

df <- data.frame(year=1:11,pop=1:11,
                 pop.html.tooltip=letters[1:11])
plot( 
  gvisScatterChart(df)
)

HTML code can be embedded into the tooltip as well, if the option isHtml is set to true.

levels(df$pop.html.tooltip)[1] <- 
  '<a href="http://www.r-project.com"><img src="http://www.r-project.org/Rlogo.jpg" alt="R logo" /></a>'
plot( 
  gvisScatterChart(df,
                   options=list(tooltip="{isHtml:'true'}"))
)

Often it is helpful to highlight certain parts of the data. The Google API distinguishes between certainty and emphasis. In a similar way to above additional columns with boolean values have to be added to the data.

df <- data.frame(year=1:11, x=1:11,
                 x.scope=c(rep(TRUE, 8), rep(FALSE, 3)),
                 y=11:1, y.html.tooltip=LETTERS[11:1],                 
                 y.certainty=c(rep(TRUE, 5), rep(FALSE, 6)),
                 y.emphasis=c(rep(FALSE, 4), rep(TRUE, 7)))
plot(
  gvisScatterChart(df,options=list(lineWidth=2))
)

Using roles with column or bar charts has some specifics. Instead of 'emphasize' use 'style' to change the colours.

dat <- data.frame(Year=2010:2013,
                  Sales=c(600, 1500, 800, 1000),
                  Sales.html.tooltip=c('$600K in our first year!',
                                       'Sunspot activity made this our best year ever!',
                                       '$800K in 2012.',
                                       '$1M in sales last year.'),
                  Sales.certainty=c(TRUE, FALSE, TRUE, FALSE))
plot(
  gvisColumnChart(dat, xvar='Year', 
                  yvar=c('Sales', 'Sales.certainty')
  )
)
df <- data.frame(country=c("US", "GB", "BR"), 
                 val1=c(1,3,4), 
                 val1.emphasis=c(TRUE, TRUE, FALSE),
                 val2=c(23,12,32))
plot(
  gvisLineChart(df, xvar="country", 
                yvar=c("val1", "val1.emphasis")
  )
)
plot(
  gvisLineChart(df, xvar="country", 
                yvar=c("val1", "val1.emphasis", "val2")
  )
)

Setting the annotations style to 'line' allows to add little reference lines to the plot.

dat <- data.frame(Year=2010:2013, 
                  Sales=c(600, 1500, 800, 1000),
                  Sales.annotation=c('First year', NA, NA, 'Last Year'),
                  Sales.annotationText=c('$600K in our first year!',
                                       NA,
                                       NA,
                                       '$1M in sales last year.'))      

plot(
  gvisLineChart(dat, xvar='Year', 
                  yvar=c('Sales',
                         'Sales.annotation',
                         'Sales.annotationText'),
                         options=list(annotations = "{style:'line'}")
  )
)

Intervals help to add error bars, confidence levels, etc. Note that the options are set either via interval or intervals, if set across all intervals. The examples below give an indication of what can be achieved with intervals. For more details visit the Google documentation.

df <- data.frame(Year=2013:2014, Sales=c(120, 130), 
                 Sales.interval.1=c(100,110), 
                 Sales.interval.2=c(140, 150),
                 Sales.interval.3=c(90, 100),
                 Sales.interval.4=c(150, 170),
                 Sales.style=c('red', 'gold'),
                 Sales.annotation=c("North", "South"),
                 check.names=FALSE)

plot(
  gvisBarChart(df, xvar='Year', 
               yvar=c('Sales',                       
                      'Sales.interval.1', 
                      'Sales.interval.2',
                      'Sales.style',
                      'Sales.annotation')
  )
)
plot(
  gvisLineChart(df, xvar='Year', 
               yvar=c('Sales', 
                      'Sales.interval.1', 
                      'Sales.interval.2'),
               options=list(series="[{color:'purple'}]")
  )
)
plot(
  gvisLineChart(df, xvar='Year', 
                yvar=c('Sales', 
                       'Sales.interval.1', 
                       'Sales.interval.2', 
                       'Sales.interval.3', 
                       'Sales.interval.4'),
                options=list(series="[{color:'purple'}]",
                             lineWidth=4,
                             interval="{
            'i1': { 'style':'line', 'color':'#D3362D', 'lineWidth': 0.5 },
            'i2': { 'style':'line', 'color':'#F1CA3A', 'lineWidth': 1 },
            'i3': { 'style':'line', 'color':'#5F9654', 'lineWidth': 2 },
            'i4': { 'style':'line', 'color':'#5F9654', 'lineWidth': 3 }
        }")
  )
)
plot(
  gvisLineChart(df, xvar='Year', 
                yvar=c('Sales', 
                       'Sales.interval.1', 
                       'Sales.interval.2', 
                       'Sales.interval.3', 
                       'Sales.interval.4'),
                options=list(series="[{color:'purple'}]",
                             lineWidth=4,
                             intervals="{ 'style':'area' }",
                             interval="{
                               'i1': { 'color': '#4374E0', 'style':'bars', 'barWidth':0, 'lineWidth':4, 'pointSize':10, 'fillOpacity':1 },
                               'i2': { 'color': '#E49307', 'style':'bars', 'barWidth':0, 'lineWidth':4, 'pointSize':10, 'fillOpacity':1 }}"                                                          
                             )
  )
)