googleVis (version 0.7.3)

gvisTreeMap: Google Tree Map with R googleChartName <- "treemap" gvisChartName <- "gvisTreeMap"

Description

The gvisTreeMap function reads a data.frame and creates text output referring to the Google Visualisation API, which can be included into a web page, or as a stand-alone page. The actual chart is rendered by the web browser.

Usage

gvisTreeMap(
  data,
  idvar = "",
  parentvar = "",
  sizevar = "",
  colorvar = "",
  options = list(),
  chartid
)

Value

paste(gvisChartName) returns list of class

paste(readLines(file.path(".", "inst", "mansections", "gvisOutputStructure.txt")))

Arguments

data

a data.frame. The data has to have at least four columns. Each row in the data table describes one node (a rectangle in the graph). Each node (except the root node) has one or more parent nodes. Each node is sized and colored according to its values relative to the other nodes currently shown.

idvar

column name of data describing the ID for each node. It can be any valid JavaScript string, including spaces, and any length that a string can hold. This value is displayed as the node header.

parentvar

column name of data that match to entries in idvar. If this is a root node, leave this NA. Only one root is allowed per treemap.

sizevar

column name of data with positive values to define the size of maps. Any positive value is allowed. This value determines the size of the node, computed relative to all other nodes currently shown. This value is ignored for non-leaf nodes (it is actually calculated from the size of all its children).

colorvar

column name of data with values to define range of color. The value is used to calculate a color for this node. Any value, positive or negative, is allowed. The color value is first recomputed on a scale from minColorValue to maxColorValue, and then the node is assigned a color from the gradient between minColor and maxColor.

options

list of configuration options, see:

gsub("CHARTNAME", googleChartName, readLines(file.path(".", "inst", "mansections", "GoogleChartToolsURLConfigOptions.txt")))

paste(readLines(file.path(".", "inst", "mansections", "gvisOptions.txt")))

chartid

character. If missing (default) a random chart id will be generated based on chart type and tempfile

Warning

Tree maps display a tree like structure where every child has to have a unique parent.

Values in column sizevar should be greater than zero and finite.

Author

Markus Gesmann ,

Diego de Castillo

Details

A tree map is a visual representation of a data tree, where each node can have zero or more children, and one parent (except for the root, which has no parents). Each node is displayed as a rectangle, sized and colored according to values that you assign. Sizes and colors are valued relative to all other nodes in the graph. You can specify how many levels to display simultaneously, and optionally to display deeper levels in a hinted fashion. If a node is a leaf node, you can specify a size and color; if it is not a leaf, it will be displayed as a bounding box for leaf nodes. The default behavior is to move down the tree when a user left-clicks a node, and to move back up the tree when a user right-clicks the graph.

The total size of the graph is determined by the size of the containing element that you insert in your page. If you have leaf nodes with names too long to show, the name will be truncated with an ellipsis (...).

References

Google Chart Tools API: gsub("CHARTNAME", googleChartName, readLines(file.path(".", "inst", "mansections", "GoogleChartToolsURL.txt")))

See Also

See also print.gvis, plot.gvis for printing and plotting methods.

Please note that the treemap package offeres a static version of tree maps via its tmPlot function.

Examples

## Please note that by default the googleVis plot command
## will open a browser window and requires Internet
## connection to display the visualisation.

Tree <- gvisTreeMap(Regions,  idvar="Region", parentvar="Parent",
                    sizevar="Val", colorvar="Fac")
plot(Tree)


Tree2 <- gvisTreeMap(Regions,  "Region", "Parent", "Val", "Fac",
                    options=list(width=600, height=500,
                                 fontSize=16,
                                 minColor='#EDF8FB',
                                 midColor='#66C2A4',
                                 maxColor='#006D2C',
                                 headerHeight=20,
                                 fontColor='black',
                                 showScale=TRUE))

plot(Tree2)

## Simple static treemap with no drill down options based on US states
## and their area. However we still have to create a parent id to use
## gvisTreeMap
 
require(datasets)
states <- data.frame(state.name, state.area)

## Create parent variable

total=data.frame(state.area=sum(states$state.area), state.name="USA")

my.states <- rbind(total, states)
my.states$parent="USA"
## Set parent variable to NA at root level
my.states$parent[my.states$state.name=="USA"] <- NA

my.states$state.area.log=log(my.states$state.area)
statesTree <- gvisTreeMap(my.states, "state.name", "parent",
                          "state.area", "state.area.log")
plot(statesTree)


## We add US regions to the above data set to enable drill down capabilities

states2 <- data.frame(state.region, state.name, state.area)

regions <- aggregate(list(region.area=states2$state.area),
                     list(region=state.region), sum)

my.states2 <- data.frame(regionid=c("USA",
                                    as.character(regions$region),
                                    as.character(states2$state.name)),
                         parentid=c(NA, rep("USA", 4),
                                   as.character(states2$state.region)),
                         state.area=c(sum(states2$state.area),
                                      regions$region.area, states2$state.area))

my.states2$state.area.log=log(my.states2$state.area)

statesTree2 <- gvisTreeMap(my.states2, "regionid", "parentid",
                           "state.area", "state.area.log")

plot(statesTree2)

## Now we add another layer with US divisions

states3 <- data.frame(state.region, state.division, state.name, state.area)

regions <- aggregate(list(region.area=states3$state.area),
                     list(region=state.region), sum)

divisions <- aggregate(list(division.area=states3$state.area),
                     list(division=state.division, region=state.region),
                     sum)

my.states3 <- data.frame(regionid=c("USA",
                                    as.character(regions$region),
                                    as.character(divisions$division),
                                    as.character(states3$state.name)),
                         parentid=c(NA, rep("USA", 4), 
                                   as.character(divisions$region),
                                   as.character(states3$state.division)),
                         state.area=c(sum(states3$state.area),
                                      regions$region.area,
                                      divisions$division.area,
                                      states3$state.area))

my.states3$state.area.log=log(my.states3$state.area)

statesTree3 <- gvisTreeMap(my.states3, "regionid", "parentid",
                           "state.area", "state.area.log")

plot(statesTree3)