Hello, I expected the code you posted to work just as you presumed it would, but without a reproducible example--I can only speculate as to why it didn't.
In the t1 dataframe, if indeed you only want to remove rows of the t1$sex_chromosome_aneuploidy_f22019_0_0 column which are undefined, you could try the following: > t11 <- t1[ !is.na(t1$sex_chromosome_aneuploidy_f22019_0_0), ] HTH, Bill. W. Michels, Ph.D. On Thu, Oct 3, 2019 at 11:59 AM Ana Marija <sokovic.anamar...@gmail.com> wrote: > > Hello, > > I have a dataframe (t1) with many columns, but the one I care about it this: > > unique(t1$sex_chromosome_aneuploidy_f22019_0_0) > [1] NA "Yes" > > it has these two values. > > I would like to remove from my dataframe t1 all rows which have "Yes" > in t1$sex_chromosome_aneuploidy_f22019_0_0 > > I tried selecting those rows with "Yes" via: > > t11=t1[t1$sex_chromosome_aneuploidy_f22019_0_0=="Yes",] > > but I got t11 which has the exact same number of rows as t1. > > If I do: > > table(t1$sex_chromosome_aneuploidy_f22019_0_0) > > Yes > 620 > > So there is for sure 620 rows which have "Yes". How to remove those > from my t1 data frame? > > Thanks > Ana > > ______________________________________________ > R-help@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. ______________________________________________ R-help@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.
