car (version 2.0-20)

Boxplot: Boxplots With Point Identification

Description

Boxplot is a wrapper for the standard R

Usage

Boxplot(y, ...)

## S3 method for class 'default':
Boxplot(y, g, labels, id.method = c("y", "identify", "none"), 
    id.n=10, xlab, ylab, ...)

## S3 method for class 'formula':
Boxplot(formula, data = NULL, subset, na.action = NULL, labels., 
    id.method = c("y", "identify", "none"), xlab, ylab, ...)

Arguments

y
a numeric variable for which the boxplot is to be constructed.
g
a grouping variable, usually a factor, for constructing parallel boxplots.
labels, labels.
point labels; if not specified, Boxplot will use the row names of the data argument, if one is given, or observation numbers.
id.method
if "y" (the default), all outlying points are labeled; if "identify", points may be labeled interactive; if "none", no point identification is performed.
id.n
up to id.n high outliers and low outliers will be identified in each group, (default, 10).
xlab, ylab
text labels for the horizontal and vertical axes; if missing, Boxplot will use the variable names.
formula
a `model' formula, of the form ~ y to produce a boxplot for the variable y, or of the form y ~ g, y ~ g1*g2*..., or y ~ g1 + g2 + ... to produce parallel boxplots for y
data, subset, na.action
as for statistical modeling functions (see, e.g., lm).
...
further arguments, such as at, to be passed to boxplot.

References

Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage.

See Also

boxplot

Examples

Run this code
Boxplot(~income, data=Prestige, id.n=Inf) # identify all outliers
Boxplot(income ~ type, data=Prestige)
Boxplot(income ~ type, data=Prestige, at=c(1, 3, 2))
Boxplot(k5 + k618 ~ lfp*wc, data=Mroz)
with(Prestige, Boxplot(income, labels=rownames(Prestige)))
with(Prestige, Boxplot(income, type, labels=rownames(Prestige)))

Run the code above in your browser using DataCamp Workspace