Fast Removal of Unused Factor Levels

A substantially faster replacement for droplevels.

Usage

fdroplevels(x, ...)

# S3 method for class 'factor'
fdroplevels(x, ...)

# S3 method for class 'data.frame'
fdroplevels(x, ...)

Arguments

x

a factor, or data frame / list containing one or more factors.

...

not used.

Details

droplevels passes a factor from which levels are to be dropped to factor, which first calls unique and then match to drop unused levels. Both functions internally use a hash table, which is highly inefficient. fdroplevels does not require mapping values at all, but uses a super fast boolean vector method to determine which levels are unused and remove those levels. In addition, if no unused levels are found, x is simply returned. Any missing values found in x are efficiently skipped in the process of checking and replacing levels. All other attributes of x are preserved.

Value

x with unused factor levels removed.

Note

If x is malformed e.g. has too few levels, this function can cause a segmentation fault terminating the R session, thus only use with ordinary / proper factors.

See also

qF, funique, Fast Grouping and Ordering, Collapse Overview

Examples

f <- iris$Species[1:100]
fdroplevels(f)
#>   [1] setosa     setosa     setosa     setosa     setosa     setosa    
#>   [7] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [13] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [19] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [25] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [31] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [37] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [43] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [49] setosa     setosa     versicolor versicolor versicolor versicolor
#>  [55] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [61] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [67] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [73] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [79] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [85] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [91] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [97] versicolor versicolor versicolor versicolor
#> Levels: setosa versicolor
identical(fdroplevels(f), droplevels(f))
#> [1] TRUE

fNA <- na_insert(f)
fdroplevels(fNA)
#>   [1] setosa     setosa     setosa     setosa     setosa     setosa    
#>   [7] setosa     setosa     setosa     <NA>       <NA>       setosa    
#>  [13] setosa     setosa     setosa     setosa     setosa     <NA>      
#>  [19] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [25] setosa     <NA>       setosa     setosa     setosa     setosa    
#>  [31] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [37] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [43] setosa     setosa     setosa     setosa     setosa     setosa    
#>  [49] <NA>       setosa     versicolor versicolor versicolor versicolor
#>  [55] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [61] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [67] <NA>       versicolor versicolor <NA>       versicolor versicolor
#>  [73] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [79] versicolor versicolor versicolor versicolor versicolor versicolor
#>  [85] versicolor versicolor versicolor versicolor versicolor <NA>      
#>  [91] versicolor versicolor versicolor <NA>       versicolor versicolor
#>  [97] <NA>       versicolor versicolor versicolor
#> Levels: setosa versicolor
identical(fdroplevels(fNA), droplevels(fNA))
#> [1] TRUE

identical(fdroplevels(ss(iris, 1:100)), droplevels(ss(iris, 1:100)))
#> [1] TRUE