Learn R Programming

Hmisc (version 5.1-3)

dotchart3: Enhanced Version of dotchart Function

Description

These are adaptations of the R dotchart function that sorts categories top to bottom, adds auxdata and auxtitle arguments to put extra information in the right margin, and for dotchart3 adds arguments cex.labels, cex.group.labels, and groupfont. By default, group headings are in a larger, bold font. dotchart3 also cuts a bit of white space from the top and bottom of the chart. The most significant change, however, is in how x is interpreted. Columns of x no longer provide an alternate way to define groups. Instead, they define superpositioned values. This is useful for showing three quartiles, for example. Going along with this change, for dotchart3 pch can now be a vector specifying symbols to use going across columns of x. x was changed in this way because to put multiple points on a line (e.g., quartiles) and keeping track of par() parameters when dotchart2 was called with add=TRUE was cumbersome. dotchart3 changes the margins to account for horizontal labels.

dotchartp is a version of dotchart3 for making the chart with the plotly package.

summaryD creates aggregate data using summarize and calls dotchart3 with suitable arguments to summarize data by major and minor categories. If options(grType='plotly') is in effect and the plotly package is installed, summaryD uses dotchartp instead of dotchart3.

summaryDp is a streamlined summaryD-like function that uses the dotchartpl function to render a plotly graphic. It is used to compute summary statistics stratified separately by a series of variables.

Usage

dotchart3(x, labels = NULL, groups = NULL, gdata = NULL,
          cex = par("cex"), pch = 21, gpch = pch, bg = par("bg"),
          color = par("fg"), gcolor = par("fg"), lcolor = "gray",
          xlim = range(c(x, gdata), na.rm=TRUE), main = NULL, xlab = NULL,
          ylab = NULL, auxdata = NULL, auxtitle = NULL, auxgdata=NULL,
          axisat=NULL, axislabels=NULL,
          cex.labels = cex, cex.group.labels = cex.labels * 1.25,
          cex.auxdata=cex, groupfont = 2,
          auxwhere=NULL, height=NULL, width=NULL, ...)

dotchartp(x, labels = NULL, groups = NULL, gdata = NULL, xlim = range(c(x, gdata), na.rm=TRUE), main=NULL, xlab = NULL, ylab = '', auxdata=NULL, auxtitle=NULL, auxgdata=NULL, auxwhere=c('right', 'hover'), symbol='circle', col=colorspace::rainbow_hcl, legendgroup=NULL, axisat=NULL, axislabels=NULL, sort=TRUE, digits=4, dec=NULL, height=NULL, width=700, layoutattr=FALSE, showlegend=TRUE, ...)

summaryD(formula, data=NULL, fun=mean, funm=fun, groupsummary=TRUE, auxvar=NULL, auxtitle='', auxwhere=c('hover', 'right'), vals=length(auxvar) > 0, fmtvals=format, symbol=if(use.plotly) 'circle' else 21, col=if(use.plotly) colorspace::rainbow_hcl else 1:10, legendgroup=NULL, cex.auxdata=.7, xlab=v[1], ylab=NULL, gridevery=NULL, gridcol=gray(.95), sort=TRUE, ...)

summaryDp(formula, fun=function(x) c(Mean=mean(x, na.rm=TRUE), N=sum(! is.na(x))), overall=TRUE, xlim=NULL, xlab=NULL, data=NULL, subset=NULL, na.action=na.retain, ncharsmax=c(50, 30), digits=4, ...)

Value

the function returns invisibly

Arguments

x

a numeric vector or matrix

labels

labels for categories corresponding to rows of x. If not specified these are taken from row names of x.

groups,gdata,cex,pch,gpch,bg,color,gcolor,lcolor,xlim,main,xlab,ylab

see dotchart

auxdata

a vector of information to be put in the right margin, in the same order as x. May be numeric, character, or a vector of expressions containing plotmath markup. For dotchartp, auxdata may be a matrix to go along with the numeric x-axis variable, to result in point-specific hover text.

auxtitle

a column heading for auxdata

auxgdata

similar to auxdata but corresponding to the gdata argument. These usually represent overall sample sizes for each group of lines.

axisat

a vector of tick mark locations to pass to axis. Useful if transforming the data axis

axislabels

a vector of strings specifying axis tick mark labels. Useful if transforming the data axis

digits

number of significant digits for formatting numeric data in hover text for dotchartp and summaryDp

dec

for dotchartp only, overrides digits to specify the argument to round() for rounding values for hover labels

cex.labels

cex for labels

cex.group.labels

cex for group labels

cex.auxdata

cex for auxdata

groupfont

font number for group headings

auxwhere

for summaryD and dotchartp specifies whether auxdata and auxgdata are to be placed on the far right of the chart, or should appear as pop-up tooltips when hovering the mouse over the ordinary x data points on the chart. Ignored for dotchart3.

...

other arguments passed to some of the graphics functions, or to dotchart3 or dotchartp from summaryD. The auxwhere='hover' option is a useful argument to pass from summaryD to dotchartp. Also used to pass other arguments to dotchartpl from summaryDp.

layoutattr

set to TRUE to put plotly::layout information in a list as an attribute layout of the returned plotly object instead of running the plotly object through the layout function. This is useful if running dotchartp multiple times to later put together using plotly::subplot and only then running the result through plotly::layout.

showlegend

set to FALSE to suppress the plotly legend with dotchartp

formula

a formula with one variable on the left hand side (the variable to compute summary statistics on), and one or two variables on the right hand side. If there are two variables, the first is taken as the major grouping variable. If the left hand side variable is a matrix it has to be a legal R variable name, not an expression, and fun needs to be able to process a matrix. For summaryDp there may be more than two right-hand-side variables.

data

a data frame or list used to find the variables in formula. If omitted, the parent environment is used.

fun

a summarization function creating a single number from a vector. Default is the mean. For summaryDp, fun produces a named vector of summary statistics, with the default computing the Mean and N (number of non-missing values).

funm

applies if there are two right hand variables and groupsummary=TRUE and the marginal summaries over just the first x variable need to be computed differently than the summaries that are cross-classified by both variables. funm defaults to fun and should have the same structure as fun.

groupsummary

By default, when there are two right-hand variables, summarize(..., fun) is called a second time without the use of the second variable, to obtain marginal summaries for the major grouping variable and display the results as a dot (and optionally in the right margin). Set groupsummary=FALSE to suppress this information.

auxvar

when fun returns more than one statistic and the user names the elements in the returned vector, you can specify auxvar as a single character string naming one of them. This will cause the named element to be written in the right margin, and that element to be deleted when plotting the statistics.

vals

set to TRUE to show data values (dot locations) in the right margin. Defaults to TRUE if auxvar is specified.

fmtvals

an optional function to format values before putting them in the right margin. Default is the format function.

symbol

a scalar or vector of pch values for ordinary graphics or a character vector or scalar of plotly symbols. These correspond to columns of x or elements produced by fun.

col

a function or vector of colors to assign to multiple points plotted in one line. If a function it will be evaluated with an argument equal to the number of groups/columns.

legendgroup

see plotly documentation; corresponds to column names/fun output for plotly graphs only

gridevery

specify a positive number to draw very faint vertical grid lines every gridevery x-axis units; for non-plotly charts

gridcol

color for grid lines; default is very faint gray scale

sort

specify sort=FALSE to plot data in the original order, from top to bottom on the dot chart. For dotchartp, set sort to 'descending' to sort in descending order of the first column of x, or 'ascending' to do the reverse. These do not make sense if groups is present.

height,width

height and width in pixels for dotchartp if not using plotly defaults. Ignored for dotchart3. If set to "auto" the height is computed using Hmisc::plotlyHeightDotchart.

overall

set to FALSE to suppress plotting of unstratified estimates

subset

an observation subsetting expression

na.action

an NA action function

ncharsmax

a 2-vector specifying the number of characters after which an html new line character should be placed, respectively for the x-axis label and the stratification variable levels

Author

Frank Harrell

See Also

dotchart,dotchart2,summarize, rlegend

Examples

Run this code
set.seed(135)
maj <- factor(c(rep('North',13),rep('South',13)))
g <- paste('Category',rep(letters[1:13],2))
n <- sample(1:15000, 26, replace=TRUE)
y1 <- runif(26)
y2 <- pmax(0, y1 - runif(26, 0, .1))
dotchart3(cbind(y1,y2), g, groups=maj, auxdata=n, auxtitle='n',
          xlab='Y', pch=c(1,17))
## Compare with dotchart function (no superpositioning or auxdata allowed):
## dotchart(y1, g, groups=maj, xlab='Y')

if (FALSE) {
dotchartp(cbind(y1, y2), g, groups=maj, auxdata=n, auxtitle='n',
          xlab='Y', gdata=cbind(c(0,.1), c(.23,.44)), auxgdata=c(-1,-2),
          symbol=c('circle', 'line-ns-open'))

summaryDp(sbp ~ region + sex + race + cut2(age, g=5), data=mydata)
}

## Put options(grType='plotly') to have the following use dotchartp
## (rlegend will not apply)
## Add argument auxwhere='hover' to summaryD or dotchartp to put
## aux info in hover text instead of right margin
summaryD(y1 ~ maj + g, xlab='Mean')
summaryD(y1 ~ maj + g, groupsummary=FALSE)
summaryD(y1 ~ g, fmtvals=function(x) sprintf('%4.2f', x))
Y <- cbind(y1, y2)   # summaryD cannot handle cbind(...) ~ ...
summaryD(Y  ~ maj + g, fun=function(y) y[1,], symbol=c(1,17))
rlegend(.1, 26, c('y1','y2'), pch=c(1,17))

summaryD(y1 ~ maj, fun=function(y) c(Mean=mean(y), n=length(y)),
         auxvar='n', auxtitle='N')

Run the code above in your browser using DataLab