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 unique 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, 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`

.

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.

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).

`.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, breaks = 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_result = 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) ))

[Package *base* version 4.1.0 Index]