cut
Convert Numeric to Factor
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.
- Keywords
- category
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. Iflabels = 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.
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
.
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.
Note
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.
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
library(base)
# 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) ))
# }
Community examples
[Example file for linkedin learning](https://linkedin-learning.pxf.io/rweekly_cut) ```r # Description: cut to set intervals numericVector <- runif(100, min = 1, max = 256 ) cut(numericVector, 3) cut(numericVector, 3, labels = c("low","med","high")) cut(numericVector, 3, labels = FALSE) cut(numericVector,breaks = c(1,100,200,256)) ```
## Cut with custom labels Cut specifies ```labels``` formated with [formatC](https://www.rdocumentation.org/packages/base/versions/3.3.1/topics/formatC?) (eg. "[b1, b2)" ). It is not always convenient, so you can add the ```labels``` argument to give your own levels. Unfortunately, no exemples are provided in the base documentation. As Josh O'Brien says in his [answer](http://stackoverflow.com/a/13061832/6947799) on stackoverflow, 11 ```breaks``` delimit 10 levels which will require only 10 ```labels```. Setting our own levels using the base exemple Z variable, with three cuts: - the minimum - the mean - the maximum The variable will be cut in two levels: - any value below or equal to the mean - any value above the mean See interactive R block: ```r Z <- stats::rnorm(10000) a= cut(Z, breaks = c(min(Z), mean(Z), max(Z)), labels= c("Mean_or_Below", "Above")) print(head(a)) ``` we made a new factor ```a``` that is easier to use afterwards.