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DescTools (version 0.99.52)

CutQ: Create a Factor Variable Using the Quantiles of a Continuous Variable

Description

Create a factor variable using the quantiles of a continous variable.

Usage

CutQ(x, breaks = quantile(x, seq(0, 1, by = 0.25), na.rm = TRUE), 
     labels = NULL, na.rm = FALSE, ...)

Value

Factor variable with one level for each quantile interval given by q.

Arguments

x

continous variable.

breaks

the breaks for creating groups. By default the quartiles will be used, say quantile seq(0, 1, by = 0.25) quantiles. See quantile for details. If breaks is given as a single integer it is interpreted as the intended number of groups, e.g. breaks=10 will return x cut in deciles.

labels

labels for the levels of the resulting category. By default, labels are defined as Q1, Q2 to the length of breaks - 1. The parameter ist passed to cut, so if labels are set to FALSE, simple integer codes are returned instead of a factor.

na.rm

Boolean indicating whether missing values should be removed when computing quantiles. Defaults to TRUE.

...

Optional arguments passed to cut.

Author

Gregory R. Warnes <greg@warnes.net>, some slight modifications Andri Signorell <andri@signorell.net>

Details

This function uses quantile to obtain the specified quantiles of x, then calls cut to create a factor variable using the intervals specified by these quantiles.

It properly handles cases where more than one quantile obtains the same value, as in the second example below. Note that in this case, there will be fewer generated factor levels than the specified number of quantile intervals.

See Also

Examples

Run this code
# create example data
set.seed(1234)
x <- rnorm(1000)

# cut into quartiles
quartiles <- CutQ(x)
table(quartiles)

# cut into deciles
deciles <- CutQ(x, breaks=10, labels=NULL)
table(deciles)

# show handling of 'tied' quantiles.
x <- round(x)  # discretize to create ties
stem(x)        # display the ties
deciles <- CutQ(x, breaks=10)

table(deciles) # note that there are only 5 groups (not 10) 
               # due to duplicates

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