# fct_lump: Lump together least/most common factor levels into "other" In forcats: Tools for Working with Categorical Variables (Factors)

## Description

Lump together least/most common factor levels into "other"

## Usage

 ```1 2``` ```fct_lump(f, n, prop, w = NULL, other_level = "Other", ties.method = c("min", "average", "first", "last", "random", "max")) ```

## Arguments

 `f` A factor (or character vector). `n, prop` If both `n` and `prop` are missing, `fct_lump` lumps together the least frequent levels into "other", while ensuring that "other" is still the smallest level. It's particularly useful in conjunction with `fct_inorder()`. Positive `n` preserves the most common `n` values. Negative `n` preserves the least common `-n` values. It there are ties, you will get at least `abs(n)` values. Positive `prop` preserves values that appear at least `prop` of the time. Negative `prop` preserves values that appear at most `-prop` of the time. `w` An optional numeric vector giving weights for frequency of each value (not level) in f. `other_level` Value of level used for "other" values. Always placed at end of levels. `ties.method` A character string specifying how ties are treated. See `rank()` for details.

`fct_other()` to convert specified levels to other.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25``` ```x <- factor(rep(LETTERS[1:9], times = c(40, 10, 5, 27, 1, 1, 1, 1, 1))) x %>% table() x %>% fct_lump() %>% table() x %>% fct_lump() %>% fct_inorder() %>% table() x <- factor(letters[rpois(100, 5)]) x table(x) table(fct_lump(x)) # Use positive values to collapse the rarest fct_lump(x, n = 3) fct_lump(x, prop = 0.1) # Use negative values to collapse the most common fct_lump(x, n = -3) fct_lump(x, prop = -0.1) # Use weighted frequencies w <- c(rep(2, 50), rep(1, 50)) fct_lump(x, n = 5, w = w) # Use ties.method to control how tied factors are collapsed fct_lump(x, n = 6) fct_lump(x, n = 6, ties.method = "max") ```