Às 19:46 de 20/04/2023, AbouEl-Makarim Aboueissa escreveu:
Hi Rui:
here is the dataset
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
with many thanks
abou
______________________
*AbouEl-Makarim Aboueissa, PhD*
*Professor, Mathematics and Statistics*
*Graduate Coordinator*
*Department of Mathematics and Statistics*
*University of Southern Maine*
On Thu, Apr 20, 2023 at 2:44 PM Rui Barradas <ruipbarra...@sapo.pt> wrote:
Às 19:36 de 20/04/2023, AbouEl-Makarim Aboueissa escreveu:
Dear All:
*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.
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*
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Hello,
There is no data set attached, see the posting guide on what file
extensions are allowed as attachments.
As for the question, try to compute mean(x, na.rm = TRUE) first, then
use this value in the replace instruction. Without data I'm just guessing.
Hope this helps,
Rui Barradas
Hello,
Here is a way. It uses ave in the function to group the data by the factor.
df1 <- "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 NA
2 98 NA
2 5 NA
2 321 NA"
df1 <- read.table(text = df1, header = TRUE,
colClasses = c("factor", "numeric", "numeric"))
replace_outlier_with_mean <- function(x, f) {
ave(x, f, FUN = \(y) {
i <- is.na(y) | y %in% boxplot.stats(y, do.conf = FALSE)$out
y[i] <- mean(y, na.rm = TRUE)
y
})
}
lapply(df1[-1], replace_outlier_with_mean, f = df1$factor)
#> $x1
#> [1] 700.0000 700.0000 470.0000 710.0000 1258.1250 610.0000
710.0000
#> [8] 610.0000 690.0000 580.0000 690.0000 1261.7778 450.0000
700.0000
#> [15] 400.0000 1261.7778 500.0000 680.0000 117.0000 120.0000
130.0000
#> [22] 120.0000 125.0000 194.6923 194.6923 130.0000 123.0000
194.6923
#> [29] 98.0000 194.6923 194.6923
#>
#> $x2
#> [1] 700.0000 500.0000 470.0000 560.0000 520.0000 720.0000
670.0000
#> [8] 1767.3750 620.0000 540.0000 690.0000 401.0000 580.0000
700.0000
#> [15] 1406.9000 600.0000 400.0000 650.0000 63.0000 68.0000
73.0000
#> [22] 69.0000 54.0000 70.0000 62.0000 168.4444 70.0000
168.4444
#> [29] 168.4444 168.4444 168.4444
Hope this helps,
Rui Barradas
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R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
