treemap (version 1.0-4)

tmPlot: Create treemap

Description

Create treemap

Usage

tmPlot(dtf, index, vSize, vColor = NULL, type = "value",
    title = NA, subtitle = NA, algorithm = "pivotSize",
    sortID = "-size", palette = NA, vColorRange = NA,
    fontsize.title = 14, fontsize.labels = 11,
    fontsize.legend = 12, lowerbound.cex.labels = 0.4,
    inflate.labels = FALSE, force.print.labels = FALSE,
    aspRatio = NA, na.rm = FALSE)

Arguments

dtf

a data.frame. Required.

index

vector containing the column names in dtf that contain the aggregation indices. Required.

vSize

name of the variable that determines the sizes of the rectangles. For small multiples, a vector of variable names (one for each treemap) should be given. Required.

vColor

name of the variable that, in combination with type, determines the colors of the rectangles. The variable can be scaled by the addition of "*" or "/". For small multiples, a vector of variable names (o

type

the type of the treemap: [object Object],[object Object],[object Object],[object Object],[object Object]

title

title of the treemap. For small multiples, a vector of titles should be given. Titles are used to describe the sizes of the rectangles.

subtitle

subtitle of the treemap. For small multiples, a vector of subtitles should be given. Subtitles are used to describe the colors of the rectangles.

algorithm

name of the used algorithm: "squarified" or "pivotSize". The squarified treemap algorithm (Bruls et al., 2000) produces good aspect ratios, but ignores the sorting order of the rectangles (sortID). The ordered treemap, pivot-by-si

sortID

name of the variable that determines the order in which the rectangles are placed from top left to bottom right. Also the values "size" and "color" can be used. To inverse the sorting order, use "-" in the prefix. By default, large rectangles

palette

either a color palette or a name of a Brewer palette (see display.brewer.all()). A Brewer palette can be reversed by prefixing its name with a "-".

vColorRange

range of the vColor-values that is mapped to palette. Only applicable for type=="value".

fontsize.title

(maximum) font size of the title

fontsize.labels

font size(s) of the data labels, which can be:

• one number, which specifies the font size for all aggregation levels
• vector of two numbers, which specific the font sizes for 1) the highest and 2) the other aggregation levels

fontsize.legend

(maximum) font size of the legend

lowerbound.cex.labels

multiplier between 0 and 1 that sets the lowerbound for the data label font sizes: 0 means draw all data labels, and 1 means only draw data labels if they fit at fontsize.data

inflate.labels

logical that determines whether data labels are inflated inside the rectangles

force.print.labels

logical that determines whether data labels are being forced to be printed (also when they don't fit)

aspRatio

preferred aspect ratio of the main rectangle, defined by width/height. When set to NA, the available window size is used.

na.rm

logical that determines whether missing values are omitted during aggregation

Value

• A list is silently returned:
• tm
  list with for each treemap a data.frame containing information about the rectangles
• nRow
  number of rows in the treemap grid
• nCol
  number of rows in the treemap grid
• vSize
  argument vSize
• vColor
  argument vColor
• This list can be used to locate a mouse click (see tmLocate).

References

Bederson, B., Shneiderman, B., Wattenberg, M. (2002) Ordered and Quantum Treemaps: Making Effective Use of 2D Space to Display Hierarchies. ACM Transactions on Graphics, 21(4): 833-854. Bruls, D.M., C. Huizing, J.J. van Wijk. Squarified Treemaps. In: W. de Leeuw, R. van Liere (eds.), Data Visualization 2000, Proceedings of the joint Eurographics and IEEE TCVG Symposium on Visualization, 2000, Springer, Vienna, p. 33-42.

Examples

### fictive structural business statistics (sbs) data of 2008 and 2009
data(sbsData)


### treemap examples

# comparisson treemaps: colors indicate change of vSize with respect to vColor
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize="employees09", 
	   vColor="employees08",
	   type="comp")

# four comparisson treemaps
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize=c("employees09", "value added09", "turnover09", "salaries09"), 
	   vColor=c("employees08", "value added08", "turnover08", "salaries08"),
	   type="comp")

# density treemaps: colors indicate density (like a population density map)
tmPlot(sbsData,
	   index=c("section", "subsection"), 
	   vSize="turnover09",
	   vColor="employees09*1000",
	   type="dens")

tmPlot(sbsData,
	   index=c("section", "subsection"), 
	   vSize="employees09",
	   vColor="turnover09",
	   type="dens")

# linked treemaps: objects are linked by color over different treemaps
tmPlot(sbsData[sbsData$section=="Manufacturing",],
	   index="subsection",
	   vSize=c("income09", "employees09", "expenditures09", "salaries09"),
	   type="linked")

# index treemap: each aggregation index has distinct color
tmPlot(sbsData,
	   index=c("section", "subsection"), 
	   vSize="employees09",
	   type="index")


# value treemap (aka Map of the Market)
sbsData$employees.growth <- sbsData$employees09 - sbsData$employees08
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize="employees09", 
	   vColor="employees.growth",
	   type="value")

### layout algorithm: squarified
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize="employees09", 
	   vColor="employees.growth",
	   type="value",
	   algorithm="squarified")


### graphical options: fontsize

# draw labels at fixed fontsize (fit only)
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize="employees09", 
	   vColor="employees08",
	   type="comp",
	   fontsize.labels=12, 
	   lowerbound.cex.labels=1)

# draw labels at flexible fontsize (skip tiny rectangles)
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize="employees09", 
	   vColor="employees08", 
	   type="comp",
	   fontsize.labels=12, 
	   lowerbound.cex.labels=.6)

# draw labels at maximal fontsize
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize="employees09", 
	   vColor="employees08", 
	   type="comp",
	   fontsize.labels=10, 
	   lowerbound.cex.labels=1, 
	   inflate.labels = TRUE)

# draw all labels at fixed fontsize
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize="employees09", 
	   vColor="employees08", 
	   type="comp",
	   fontsize.labels=10, 
	   lowerbound.cex.labels=1, 
	   force.print.labels=TRUE)


### graphical options: color palette

# terrain colors
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize="employees09", 
	   vColor="employees.growth", 
	   type="value", 
	   palette=terrain.colors(10))

# Brewer's Red-White-Grey palette reversed with predefined range
tmPlot(sbsData, 
	   index=c("section", "subsection"), 
	   vSize="employees09", 
	   vColor="employees.growth", 
	   type="value", 
	   palette="-RdGy", 
	   vColorRange=c(-20000,20000))