base (version 3.5.0)

cut: Convert Numeric to Factor

Description

cut divides the range of x into intervals and codes the values in x according to which interval they fall. The leftmost interval corresponds to level one, the next leftmost to level two and so on.

Usage

cut(x, …)
# S3 method for default
cut(x, breaks, labels = NULL,
    include.lowest = FALSE, right = TRUE, dig.lab = 3,
    ordered_result = FALSE, …)

Arguments

x

a numeric vector which is to be converted to a factor by cutting.

breaks

either a numeric vector of two or more unique cut points or a single number (greater than or equal to 2) giving the number of intervals into which x is to be cut.

labels

labels for the levels of the resulting category. By default, labels are constructed using "(a,b]" interval notation. If labels = FALSE, simple integer codes are returned instead of a factor.

include.lowest

logical, indicating if an ‘x[i]’ equal to the lowest (or highest, for right = FALSE) ‘breaks’ value should be included.

right

logical, indicating if the intervals should be closed on the right (and open on the left) or vice versa.

dig.lab

integer which is used when labels are not given. It determines the number of digits used in formatting the break numbers.

ordered_result

logical: should the result be an ordered factor?

…

further arguments passed to or from other methods.

Value

A factor is returned, unless labels = FALSE which results in an integer vector of level codes.

Values which fall outside the range of breaks are coded as NA, as are NaN and NA values.

Details

When breaks is specified as a single number, the range of the data is divided into breaks pieces of equal length, and then the outer limits are moved away by 0.1% of the range to ensure that the extreme values both fall within the break intervals. (If x is a constant vector, equal-length intervals are created, one of which includes the single value.)

If a labels parameter is specified, its values are used to name the factor levels. If none is specified, the factor level labels are constructed as "(b1, b2]", "(b2, b3]" etc. for right = TRUE and as "[b1, b2)", … if right = FALSE. In this case, dig.lab indicates the minimum number of digits should be used in formatting the numbers b1, b2, …. A larger value (up to 12) will be used if needed to distinguish between any pair of endpoints: if this fails labels such as "Range3" will be used. Formatting is done by formatC.

The default method will sort a numeric vector of breaks, but other methods are not required to and labels will correspond to the intervals after sorting.

As from R 3.2.0, getOption("OutDec") is consulted when labels are constructed for labels = NULL.

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

See Also

split for splitting a variable according to a group factor; factor, tabulate, table, findInterval.

quantile for ways of choosing breaks of roughly equal content (rather than length).

.bincode for a bare-bones version.

Examples

# NOT RUN {
Z <- stats::rnorm(10000)
table(cut(Z, breaks = -6:6))
sum(table(cut(Z, breaks = -6:6, labels = FALSE)))
sum(graphics::hist(Z, breaks = -6:6, plot = FALSE)$counts)

cut(rep(1,5), 4) #-- dummy
tx0 <- c(9, 4, 6, 5, 3, 10, 5, 3, 5)
x <- rep(0:8, tx0)
stopifnot(table(x) == tx0)

table( cut(x, b = 8))
table( cut(x, breaks = 3*(-2:5)))
table( cut(x, breaks = 3*(-2:5), right = FALSE))

##--- some values OUTSIDE the breaks :
table(cx  <- cut(x, breaks = 2*(0:4)))
table(cxl <- cut(x, breaks = 2*(0:4), right = FALSE))
which(is.na(cx));  x[is.na(cx)]  #-- the first 9  values  0
which(is.na(cxl)); x[is.na(cxl)] #-- the last  5  values  8


## Label construction:
y <- stats::rnorm(100)
table(cut(y, breaks = pi/3*(-3:3)))
table(cut(y, breaks = pi/3*(-3:3), dig.lab = 4))

table(cut(y, breaks =  1*(-3:3), dig.lab = 4))
# extra digits don't "harm" here
table(cut(y, breaks =  1*(-3:3), right = FALSE))
#- the same, since no exact INT!

## sometimes the default dig.lab is not enough to be avoid confusion:
aaa <- c(1,2,3,4,5,2,3,4,5,6,7)
cut(aaa, 3)
cut(aaa, 3, dig.lab = 4, ordered = TRUE)

## one way to extract the breakpoints
labs <- levels(cut(aaa, 3))
cbind(lower = as.numeric( sub("\\((.+),.*", "\\1", labs) ),
      upper = as.numeric( sub("[^,]*,([^]]*)\\]", "\\1", labs) ))
# }