NMcalc (version 0.0.4)

quantbin: Bin observations by quantiles. Label by bin number or by interval.

Description

This is simple stuff, but I can never remember the exact quantile and findInterval/cut commands to use. quantbin finds quantiles using quantile and then assigns bins using either findInterval or cut.

Usage

quantbin(x, nbins, probs, label = "num", ...)

Value

If label="num", integers. If label="interval", factors.

Arguments

x

The observations

nbins

Number of bins to use

probs

Quantiles for construvtion of bins (optional). The default is to spread nbins quantiles equi-distantly across the observed values.

label

label="num" gives a numeric bin number (findInterval). label="interval" gives a character representation of the interval (cut).

...

additional arguments passed to quantile.

Details

quantbin uses stats::quantile for quantile estimation. Except for x and probs, all parameters can be controlled using na.rm and ... arguments. See ?stats::quantile for details.

na.rm na.rm=TRUE is needed for quantile to be able to estimate the distribution if x contains NA's. Notice, if na.rm=T, an NA element in x will still result in an NA element in return. If na.rm=F and there are NA's in x, all elements will be NA in result (quantiles cannot be determined, nor can the binning of x by those quantiles).

If data is not continuous, this method may not lead to balanced distributions.

Examples

set.seed(134)
library(data.table)
## CRAN requires examples to run on a single thread
data.table::setDTthreads(1)
dt1 <- data.table(x=rnorm(n=1000))
dt1[,bin:=quantbin(x,nbins=4,label="num")]
dt1[,int:=quantbin(x,nbins=4,label="interval")]
## perfect - flat distribution
dt1[,.N,keyby=.(bin,int)]

dt2 <- data.table(x=c(rnorm(n=100000),NA))
dt2[,bin:=quantbin(x,nbins=4,label="num",na.rm=TRUE)]
dt2[,int:=quantbin(x,nbins=4,label="interval",na.rm=TRUE)]
## perfect - flat distribution
dt2[,.N,keyby=.(bin,int)]
unique(dt2[,.(bin,int)])[order(bin)]


## we may not get a flat distribution in case of discrete observations
dt3 <- data.table(x=c(sample(1:3,100,replace=TRUE)))
dt3[,bin:=quantbin(x,nbins=2,label="num",na.rm=TRUE)]
dt3[,int:=quantbin(x,nbins=2,label="interval",na.rm=TRUE)]
## Not a flat distribution
dt3[,.N,keyby=.(x,bin,int)]