Hmisc (version 4.1-0)

cut2: Cut a Numeric Variable into Intervals

Description

Function like cut but left endpoints are inclusive and labels are of the form [lower, upper), except that last interval is [lower,upper]. If cuts are given, will by default make sure that cuts include entire range of x. Also, if cuts are not given, will cut x into quantile groups (g given) or groups with a given minimum number of observations (m). Whereas cut creates a category object, cut2 creates a factor object.

Usage

cut2(x, cuts, m, g, levels.mean, digits, minmax=TRUE, oneval=TRUE, onlycuts=FALSE)

Arguments

x

numeric vector to classify into intervals

cuts

cut points

m

desired minimum number of observations in a group. The algorithm does not guarantee that all groups will have at least m observations.

g

number of quantile groups

levels.mean

set to TRUE to make the new categorical vector have levels attribute that is the group means of x instead of interval endpoint labels

digits

number of significant digits to use in constructing levels. Default is 3 (5 if levels.mean=TRUE)

minmax

if cuts is specified but min(x)<min(cuts) or max(x)>max(cuts), augments cuts to include min and max x

oneval

if an interval contains only one unique value, the interval will be labeled with the formatted version of that value instead of the interval endpoints, unless oneval=FALSE

onlycuts

set to TRUE to only return the vector of computed cuts. This consists of the interior values plus outer ranges.

Value

a factor variable with levels of the form [a,b) or formatted means (character strings) unless onlycuts is TRUE in which case a numeric vector is returned

See Also

cut, quantile

Examples

# NOT RUN {
set.seed(1)
x <- runif(1000, 0, 100)
z <- cut2(x, c(10,20,30))
table(z)
table(cut2(x, g=10))      # quantile groups
table(cut2(x, m=50))      # group x into intevals with at least 50 obs.
# }