Hi Rui:
How about this dataset, please see below. I included a few outliers in each
column, as you can see in the printed dataset; please see below.
Once again, thank you very much, and sorry if I bothered you all.
abou
> dput(datafortest)
structure(list(factor1 = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, NA, NA, NA, NA), levels = c("1", "2",
"3"), class = "factor"),
X = c(994455.077, 4348.031, 9999.789, 3813.139, 12.65, 5642.667,
876684.386, 5165.731, NA, 3259.241, 8.383, 1997.878, 99990.608,
2655.977, 9.49, 1826.851, 4386.002, 883295.091, 2120.902,
NA, 2056.123, 5.088, NA, 92539.873, NA, NA, NA, NA), Y = c(76888L,
333L, 618L, 10L, 344L, NA, 3L, 86999L, 265L, 557L, 77777L,
383L, NA, NA, 87777L, 287L, 352L, 308L, 999526L, 489L, 2L,
444L, 9L, 333L, NA, NA, NA, NA), factor2 = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), levels = c("1",
"2", "3"), class = "factor"), Z = c(54999L,
475L, 15L, 603L,
442L, 79486L, 927L, 971L, 388L, 888L, 514L, 409L, 546L, 523L,
313L, 296L, 320L, 388L, 79999L, 677L, 555L, NA, 479L, 257L,
313L, 21L, 320L, 4L), U = c(NA, NA, 1.5, 332, 216, 217, 1000,
10, 9999, 444, NA, 5, 327, 58888, 456, 412, 251, 6, 398,
438, 428, 15, NA, 406, 334, 465, 180, 88999), V = c(12, 240,
9000, 265, NA, 99999, 1, 562, 13, 777, 322, NA, 99988, 653,
450, 576, NA, 396.5, 91888, 5, 219, NA, 321, 417, 409, 999999,
523, 10)), row.names = c(NA, -28L), class =
"data.frame")>
> datafortest
factor1 X Y factor2 Z U V
1 1 994455.077 76888 1 54999 NA 12.0
2 1 4348.031 333 1 475 NA 240.0
3 1 9999.789 618 1 15 1.5 9000.0
4 1 3813.139 10 1 603 332.0 265.0
5 1 12.650 344 1 442 216.0 NA
6 1 5642.667 NA 1 79486 217.0 99999.0
7 1 876684.386 3 1 927 1000.0 1.0
8 2 5165.731 86999 1 971 10.0 562.0
9 2 NA 265 1 388 9999.0 13.0
10 2 3259.241 557 2 888 444.0 777.0
11 2 8.383 77777 2 514 NA 322.0
12 2 1997.878 383 2 409 5.0 NA
13 2 99990.608 NA 2 546 327.0 99988.0
14 2 2655.977 NA 2 523 58888.0 653.0
15 3 9.490 87777 2 313 456.0 450.0
16 3 1826.851 287 2 296 412.0 576.0
17 3 4386.002 352 2 320 251.0 NA
18 3 883295.091 308 2 388 6.0 396.5
19 3 2120.902 999526 3 79999 398.0 91888.0
20 3 NA 489 3 677 438.0 5.0
21 3 2056.123 2 3 555 428.0 219.0
22 3 5.088 444 3 NA 15.0 NA
23 3 NA 9 3 479 NA 321.0
24 3 92539.873 333 3 257 406.0 417.0
25 <NA> NA NA 3 313 334.0 409.0
26 <NA> NA NA 3 21 465.0 999999.0
27 <NA> NA NA 3 320 180.0 523.0
28 <NA> NA NA 3 4 88999.0
10.0>
with many thanks
abou
______________________
*AbouEl-Makarim Aboueissa, PhD*
*Professor, Mathematics and Statistics*
*Graduate Coordinator*
*Department of Mathematics and Statistics*
*University of Southern Maine*
On Sat, Apr 29, 2023 at 8:05?AM Rui Barradas <ruipbarradas at sapo.pt>
wrote:
> ?s 14:09 de 28/04/2023, AbouEl-Makarim Aboueissa escreveu:
> > *R: *Grubbs Test to detect all outliers Per group for all columns in a
> data
> > frame
> >
> >
> >
> > Dear All: good morning
> >
> > I have a dataset (as an example) with two column factors (factor1 and
> > factor2) and 5 numerical columns (X,Y,Z,U,V). The X and Y columns have
> same
> > length as factor1; and Z, U, and V have same length as factor2. Please
> see
> > dataset is copied below. Please note that all dataset columns have NAs
> > values.
> >
> > *Need help on this:*
> >
> >
> > Can we use the grubbs.test() function to detect all outliers and
replace
> it
> > by NA in X and Y datasets per group in factor1; and in Z, U, and V
> datasets
> > per group in factor2. Columns in the dataframe have different lengths,
> but
> > when I read the .csv file, R added NA values for the shorter columns.
> >
> > If you need the .csv data file, please let me know.
> >
> >
> > Thank you very much for your help in advance.
> >
> >
> >
> >
> > install.packages("outliers")
> > library(outliers)
> >
> > datafortest<-read.csv("G:/data_for_test.csv",
header=TRUE)
> > datafortest
> >
> > datafortest<-data.frame(datafortest)
> >
> > datafortest$factor1<-as.factor(datafortest$factor1)
> > datafortest$factor2<-as.factor(datafortest$factor2)
> >
> > str(datafortest)
> >
> > ##### tried to use grubbs.test() on a single column of the dataframe,
but
> > still not working
> > tests.for.outliers.X<- grubbs.test(datafortest$X, na.rm = TRUE,
type=11)
> >
> >
> > ####################################
> >
> > *grubbs.test() on a single dataset: but this can only detect if the
min
> and
> > the max are outliers.*
> >
> >
> > xx999<-c(0.088,1,2,3,4,5,6,7,8,9,88,98,99)
> > grubbs.test(xx999, type=11)
> >
> >
> >
> >
> > With many thanks
> >
> > Abou
> >
> >
> >
> > factor1 X Y factor2 Z U
> > V
> > 1 4455.077 888 1 999 NA 999
> > 1 4348.031 333 1 475 NA 240
> > 1 9999.789 618 1 507 252 394
> > 1 3813.139 417 1 603 332 265
> > 1 7512.65 344 1 442 216 NA
> > 1 5642.667 NA 1 486 217 275
> > 1 6684.386 341 1 927 698 479
> > 2 5165.731 999 1 971 311 562
> > 2 NA 265 1 388 999 512
> > 2 3259.241 557 2 888 444 777
> > 2 3288.383 234 2 514 NA 322
> > 2 1997.878 383 2 409 311 NA
> > 2 99990.61 NA 2 546 327 728
> > 2 2655.977 NA 2 523 228 653
> > 3 3189.49 7777 2 313 456 450
> > 3 1826.851 287 2 296 412 576
> > 3 4386.002 352 2 320 251 NA
> > 3 3295.091 308 2 388 888 396.5
> > 3 2120.902 526 3 9999 398 888
> > 3 NA 489 3 677 438 307
> > 3 2056.123 291 3 555 428 219
> > 3 1995.088 444 3 NA 319 NA
> > 3 NA 349 3 479 NA 321
> > 3 2539.873 333 3 257 406 417
> > 3 313 334 409
> > 3 296 465 546
> > 3 320 180 523
> > 3 388 999 313
> >
> >
> >
> > ______________________
> >
> >
> > *AbouEl-Makarim Aboueissa, PhD*
> >
> > *Professor, Mathematics and Statistics*
> > *Graduate Coordinator*
> >
> > *Department of Mathematics and Statistics*
> > *University of Southern Maine*
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at r-project.org 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.
> Hello,
>
> With the data file you have attached I cannot reproduce any errors, all
> went well at the first try.
>
>
> library(outliers)
>
> fl <- "~/data_for_test.csv"
> datafortest <- read.csv(fl)
>
> # these are not needed to run the test
> datafortest$factor1 <- as.factor(datafortest$factor1)
> datafortest$factor2 <- as.factor(datafortest$factor2)
> str(datafortest)
> #> 'data.frame': 28 obs. of 7 variables:
> #> $ factor1: Factor w/ 3 levels
"1","2","3": 1 1 1 1 1 1 1 2 2 2 ...
> #> $ X : num 4455 4348 10000 3813 7513 ...
> #> $ Y : int 888 333 618 417 344 NA 341 999 265 557 ...
> #> $ factor2: Factor w/ 3 levels
"1","2","3": 1 1 1 1 1 1 1 1 1 2 ...
> #> $ Z : int 999 475 507 603 442 486 927 971 388 888 ...
> #> $ U : int NA NA 252 332 216 217 698 311 999 444 ...
> #> $ V : num 999 240 394 265 NA 275 479 562 512 777 ...
> head(datafortest)
> #> factor1 X Y factor2 Z U V
> #> 1 1 4455.077 888 1 999 NA 999
> #> 2 1 4348.031 333 1 475 NA 240
> #> 3 1 9999.789 618 1 507 252 394
> #> 4 1 3813.139 417 1 603 332 265
> #> 5 1 7512.650 344 1 442 216 NA
> #> 6 1 5642.667 NA 1 486 217 275
>
> ##### tried to use grubbs.test() on a single column of the dataframe, but
> ##### still not working
> grubbs.test(datafortest$X, type = 11)
> #>
> #> Grubbs test for two opposite outliers
> #>
> #> data: datafortest$X
> #> G = 4.6640014, U = 0.0091756, p-value = 0.02867
> #> alternative hypothesis: 1826.851 and 99990.608 are outliers
>
>
>
> Hope this helps,
>
> Rui Barradas
>
>
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