Is there a function to replace outliers?

[Visiting]

I have a big dataset need to replace outliers with mean of the variable, is there a function to do that? lets take a example with the small dataset below:
data <- airquality
View(data)

library(outliers)
outlier(data)
following outlier can be found
Ozone Solar.R Wind Temp Month Day
168.0 7.0 20.7 56.0 9.0 31.0

How to replace them with column mean? Thank you!

[nirgrahamuk]

The first step must be to calculate the column means. Would you calculate from the whole dataset or from the non outliers?

[Leon]

Try looking at this small example:

set.seed(850692)
s <- c(rnorm(90), rnorm(10, sd = 10))
b <- boxplot(s, plot = FALSE)
s1 <- s
s1[which(s %in% b$out)] <- mean(s)
par(mfrow=c(1,2))
boxplot(s)
boxplot(s1)

Hope it helps

[Visiting]

Mean for non outliers, if mean for non-outliers not easy to be calculated, mean for entire column also ok, may replace outliers with median. thank you!

[Visiting]

Is it possible to apply to a dataset (multiple columns)? Thank you!

[nirgrahamuk]

do_col <- function(c){
b <- boxplot(c, plot = FALSE)
s1 <- c
s1[which(c %in% b$out)] <- mean(c[which(! c %in% b$out)],na.rm=TRUE)
return(s1)
}

# (testvec <- c(rep(1,9),100))
# do_col(testvec)
library(tidyverse)
columns_to_do <- names(select_if(iris,is.numeric))

purrr::map_dfc(columns_to_do,
           ~do_col(iris[[.]])) %>% set_names(columns_to_do)

[Visiting]

Thank you !

do_col <- function(c){
b <- boxplot(c, plot = FALSE)
s1 <- c
s1[which(c %in% b$out)] <- mean(c[which(! c %in% b$out)],na.rm=TRUE)
return(s1)
}

# (testvec <- c(rep(1,9),100))
# do_col(testvec)
library(tidyverse)
columns_to_do <- names(select_if(iris,is.numeric))

purrr::map_dfc(columns_to_do,
           ~do_col(iris[[.]])) %>% set_names(columns_to_do)