| 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, ...)
x |
a numeric vector which is to be converted to a factor by cutting. |
breaks |
either a vector of cut points or number
giving the number of intervals which x is to be cut into. |
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. |
... |
further arguments passed to or from other methods. |
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 how many digits should be used in
formatting the numbers b1, b2, ....
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().
Z <- rnorm(10000) table(cut(Z, br = -6:6)) sum(table(cut(Z, br = -6:6, labels=FALSE))) sum( hist (Z, br = -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, br = 3*(-2:5))) table( cut(x, br = 3*(-2:5), right = FALSE)) ##--- some values OUTSIDE the breaks : table(cx <- cut(x, br = 2*(0:4))) table(cxl <- cut(x, br = 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 <- 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!