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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, …)# S3 method for default
cut(x, breaks, labels = NULL,
include.lowest = FALSE, right = TRUE, dig.lab = 3,
ordered_result = FALSE, …)
x is to be cut."(a,b]" interval notation. If
labels = FALSE, simple integer codes are returned instead of
a factor.right = FALSE) ‘breaks’
value should be included.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.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.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.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) ))
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