gvisTreeMap | R Documentation |
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.
gvisTreeMap(
data,
idvar = "",
parentvar = "",
sizevar = "",
colorvar = "",
options = list(),
chartid
)
data |
a |
idvar |
column name of |
parentvar |
column name of |
sizevar |
column name of |
colorvar |
column name of |
options |
list of configuration options, see: \Sexpr[results=rd]{gsub("CHARTNAME", googleChartName, readLines(file.path(".", "inst", "mansections", "GoogleChartToolsURLConfigOptions.txt")))} \Sexpr[results=rd]{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 |
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 (...).
returns list
of class
\Sexpr[results=rd]{paste(readLines(file.path(".", "inst",
"mansections", "gvisOutputStructure.txt")))}
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.
Markus Gesmann markus.gesmann@gmail.com,
Diego de Castillo decastillo@gmail.com
Google Chart Tools API: \Sexpr[results=rd]{gsub("CHARTNAME", googleChartName, readLines(file.path(".", "inst", "mansections", "GoogleChartToolsURL.txt")))}
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.
## 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)
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