cut {base} R Documentation

## 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, ...)

## Default S3 method:
cut(x, breaks, labels = NULL,
include.lowest = FALSE, right = TRUE, dig.lab = 3, ...)
```

### Arguments

 `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.

### Details

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.

### Value

A `factor` is returned, unless `labels = FALSE` which results in the mere integer level codes.

### 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.

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

### Examples

```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!

## 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)
```

[Package base version 2.2.1 Index]