R: Classify univariate vector to interval

Classify Intervals {classInt} | R Documentation

## Classify univariate vector to interval

### Description

Given a numeric vector classify into numeric intervals. `classify_intervals()` is a wrapper of both `classIntervals()` and `findCols()`.

### Usage

    classify_intervals(var, n, style = "quantile", rtimes = 3, ...,
     intervalClosure = c("left", "right"), dataPrecision = NULL,
     warnSmallN = TRUE, warnLargeN = TRUE, largeN = 3000L, samp_prop = 0.1,
     gr = c("[", "]"), factor = TRUE)

### Arguments

`var` | a continuous numerical variable
`n` | number of classes required, if missing, `nclass.Sturges` is used; see also the "dpih" and "headtails" styles for automatic choice of the number of classes
`style` | chosen style: one of "fixed", "sd", "equal", "pretty", "quantile", "kmeans", "hclust", "bclust", "fisher", "jenks", "dpih", "headtails", or "maximum"
`rtimes` | number of replications of var to catenate and jitter; may be used with styles "kmeans" or "bclust" in case they have difficulties reaching a classification
`intervalClosure` | default “left”, allows specification of whether partition intervals are closed on the left or the right (added by Richard Dunlap). Note that the sense of interval closure is hard-coded as “right”-closed when`style="jenks"` (see Details below).
`dataPrecision` | default NULL, permits rounding of the interval endpoints (added by Richard Dunlap). The data precision used for printing interval values in the legend returned by `findColours`, and in the `print` method for classIntervals objects. If intervalClosure is “left”, the value returned is `ceiling` of the data value multiplied by 10 to the dataPrecision power, divided by 10 to the dataPrecision power. The argument does not round `var`, the input variable.
`warnSmallN` | default TRUE, if FALSE, quietens warning for n >= nobs
`warnLargeN` | default TRUE, if FALSE large data handling not used
`largeN` | default 3000L, the QGIS sampling threshold; over 3000, the observations presented to "fisher" and "jenks" are either a `samp_prop=` sample or a sample of 3000, whichever is larger
`samp_prop` | default 0.1, QGIS 10% sampling proportion
`gr` | default `c("[", "]")`, if the units package is available, `units::units_options("group")` may be used directly to give the enclosing bracket style
`...` | arguments to be passed to the functions called in each style
`factor` | default "TRUE", if "TRUE" returns cols as a factor with intervals as labels rather than integers

### Value

A vector of same length as `var`. When `factor = FALSE` returns a factor where the levels are the interval of the observation.

### See Also

`classIntervals()`, `findCols()`

### Examples

    xvar <- c(22361, 9573, 4836, 5309, 10384, 4359, 11016, 4414, 3327, 3408,
      17816, 6909, 6936, 7990, 3758, 3569, 21965, 3605, 2181, 1892,
      2459, 2934, 6399, 8578, 8537, 4840, 12132, 3734, 4372, 9073,
      7508, 5203)
    classIntervals(xvar, 5, "sd")
    classify_intervals(xvar, 5, "sd", factor = FALSE)
    classify_intervals(xvar, 5, "sd", factor = TRUE)

    if (!require("spData", quietly=TRUE)) {
      message("spData package needed for examples")
      run <- FALSE
    } else {
      run <- TRUE
    }

    if (run) {
      data("jenks71", package = "spData")
      x <- jenks71$jenks71
      classify_intervals(x, n = 5, style = "fisher")
    }

[Package classInt version 0.4-7 Index]