Chop common values into singleton intervals

chop_spikes() lets you chop common values of x into their own singleton intervals. This can help make unusual values visible.

Usage

chop_spikes(x, breaks, ..., n = NULL, prop = NULL)

brk_spikes(breaks, n = NULL, prop = NULL)

tab_spikes(x, breaks, ..., n = NULL, prop = NULL)

Arguments

x

A vector.

breaks

A numeric vector of cut-points or a call to a brk_* function. The resulting breaks object will be modified to add singleton breaks.

...

Passed to chop().

n, prop

Scalar. Provide either n, a number of values, or prop, a proportion of length(x). Values of x which occur at least this often will get their own singleton break.

Value

chop_* functions return a factor of the same length as x.

brk_* functions return a function to create breaks.

tab_* functions return a contingency table().

Details

This function is .

See also

dissect() for a different approach.

Other chopping functions: chop(), chop_equally(), chop_evenly(), chop_fn(), chop_mean_sd(), chop_n(), chop_proportions(), chop_quantiles(), chop_width(), fillet()

Examples

x <- c(1:4, rep(5, 5), 6:10)
chop_spikes(x, c(2, 7), n = 5)
#>  [1] [1, 2)  [2, 5)  [2, 5)  [2, 5)  {5}     {5}     {5}     {5}     {5}    
#> [10] (5, 7)  [7, 10] [7, 10] [7, 10] [7, 10]
#> Levels: [1, 2) [2, 5) {5} (5, 7) [7, 10]
chop_spikes(x, c(2, 7), prop = 0.25)
#>  [1] [1, 2)  [2, 5)  [2, 5)  [2, 5)  {5}     {5}     {5}     {5}     {5}    
#> [10] (5, 7)  [7, 10] [7, 10] [7, 10] [7, 10]
#> Levels: [1, 2) [2, 5) {5} (5, 7) [7, 10]
chop_spikes(x, brk_width(5), n = 5)
#>  [1] [1, 5)  [1, 5)  [1, 5)  [1, 5)  {5}     {5}     {5}     {5}     {5}    
#> [10] [6, 11] [6, 11] [6, 11] [6, 11] [6, 11]
#> Levels: [1, 5) {5} [6, 11]

set.seed(42)
x <- runif(40, 0, 10)
x <- sample(x, 200, replace = TRUE)
tab_spikes(x, brk_width(2, 0), prop = 0.05)
#>      [0, 2)      [2, 4)      [4, 6)      [6, 8)  [8, 9.057)     {9.057} 
#>          30          24          36          40          22          11 
#> (9.057, 10] 
#>          37