| cut {base} | R Documentation |
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.
cut(x, ...)
## Default S3 method:
cut(x, breaks, labels = NULL,
include.lowest = FALSE, right = TRUE, dig.lab = 3,
ordered_result = FALSE, ...)
x |
a numeric vector which is to be converted to a factor by cutting. |
breaks |
either a numeric vector of two or more cut points or a
single number (greater than or equal to 2) giving the number of
intervals into which |
labels |
labels for the levels of the resulting category. By default,
labels are constructed using |
.
include.lowest |
logical, indicating if an ‘x[i]’ equal to
the lowest (or highest, for |
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. |
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 that cover
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.
A factor is returned, unless labels = FALSE which
results in the mere integer level codes.
Instead of table(cut(x, br)), hist(x, br, plot = FALSE) is
more efficient and less memory hungry. Instead of cut(*,
labels = FALSE), findInterval() is more efficient.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
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), cut2 in package
Hmisc for a canned way to form quantile groups.
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) ))