Dear All: the attached file in the .txt format
*Re:* detect and replace outliers by the average
The dataset, please see attached, contains a group factoring column “
*factor*” and two columns of data “x1” and “x2” with some NA values. I need
some help to detect the outliers and replace it and the NAs with the
average within each level (0,1,2) for each variable “x1” and “x2”.
I tried the below code, but it did not accomplish what I want to do.
The average within each level should be computed after discard the outliers.
data<-read.csv("G:/20-Spring_2023/Outliers/data.csv", header=TRUE)
data
replace_outlier_with_mean <- function(x) {
replace(x, x %in% boxplot.stats(x)$out, mean(x, na.rm=TRUE)) #### ,
na.rm=TRUE NOT working
}
data[] <- lapply(data, replace_outlier_with_mean)
Thank you all very much for your help in advance.
with many thanks
abou
______________________
*AbouEl-Makarim Aboueissa, PhD*
*Professor, Mathematics and Statistics*
*Graduate Coordinator*
*Department of Mathematics and Statistics*
*University of Southern Maine*
factor x1 x2
0 700 700
0 700 500
0 470 470
0 710 560
0 5555 520
0 610 720
0 710 670
0 610 9999
1 690 620
1 580 540
1 690 690
1 NA 401
1 450 580
1 700 700
1 400 8888
1 6666 600
1 500 400
1 680 650
2 117 63
2 120 68
2 130 73
2 120 69
2 125 54
2 999 70
2 165 62
2 130 987
2 123 70
2 78
2 98
2 5
2 321 NA
______________________________________________
[email protected] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
