R: Fast binning of numeric vector into equidistant bins

bin {MESS} | R Documentation

## Fast binning of numeric vector into equidistant bins

### Description

Fast binning of numeric vector into equidistant bins

### Usage

    bin(x, width, origin = 0, missinglast = FALSE)

### Arguments

`x` | A matrix of regressor variables. Must have the same number of rows as the length of y.
`width` | The width of the bins
`origin` | The starting point for the bins. Any number smaller than origin will be disregarded
`missinglast` | Boolean. Should the missing observations be added as a separate element at the end of the returned count vector.

### Details

Missing values (NA, Inf, NaN) are added at the end of the vector as the last bin returned if missinglast is set to TRUE

### Value

An list with elements counts (the frequencies), origin (the origin), width (the width), missing (the number of missings), and last_bin_is_missing (boolean) telling whether the missinglast is true or not.

### Author(s)

Hadley Wickham (from SO: https://stackoverflow.com/questions/13661065/superimpose-histogram-fits-in-one-plot-ggplot) - adapted here by Claus Ekstrøm <claus@rprimer.dk>

### Examples

    set.seed(1)
    x <- sample(10, 20, replace = TRUE)
    bin(x, 15)

[Package MESS version 0.5.6 Index]