Thank you all for the replies. BWS6 is a data frame, but actually the main problem in my code as Duncan points out is that the statement inside the parentheses modifies BWS6 anyway. I need to rework my code.
I coded my missing values for these data sets as -999.25 (a hangover from another piece of software that dumps out results). It's a rather dangerous thing to do, as in some cases I have discovered that when I write to csv, -999.25 is written as -999.2 or even -999 in some cases (haven't completely worked that out). Hence the awkward "< 998" expression. In respect of Duncan and Peter's solutions, I have found that R can be a troublesome pet at times, and this seems like one of them. Thanks for the help and warnings! Ben. On 9 September 2013 00:39, peter dalgaard <[email protected]> wrote: > > On Sep 8, 2013, at 16:09 , Duncan Murdoch wrote: > > > On 13-09-08 6:46 AM, Ben Harrison wrote: > >> Hello, > >> I wish to create a copy of a data frame, but with missing values > replaced > >> with NAs. > >> > >> I thought I should be able to do it in one step using parentheses to > group > >> the statements and force those inside the parens to execute first: > >> > >> df <- (BWS6[BWS6 < -998] <- NA) > >> > >> But all this does is assign NA to df, as described in ?"[" for the case > >> with no parens. > >> > >> Can I do this in some way? It's no great problem of course to have two > >> separate statements, just curious. > > > > This isn't an order of execution issue. Your parenthesized assignment > modifies BWS6, and that's not what you want to do. > > Also, the value of an assignment is always the right hand side, in this > case NA. > > The canonical way would be --- but There be Tygers There! --- this: > > df <- `[<-`(BWS6, BWS6 < -998, NA) > > The "Tygers" are that R sometimes cheats in order to avoid duplication and > assumes that `[<-` can destructively modify its argument. So you shouldn't > actually do the above. > > - Peter D. > > > > > If you convert BWS6 to a matrix instead of a dataframe, you could use > > > > res <- ifelse(BWS6 < -998, NA, BWS6) > > > > but ifelse doesn't work on dataframes in general. You can do it in one > long line with a dataframe using lapply, but it is ugly: > > > > df <- as.data.frame( lapply(BWS6, function(col) ifelse(col < -998, NA, > col))) > > > > Duncan Murdoch > > > > ______________________________________________ > > [email protected] mailing list > > 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. > > -- > Peter Dalgaard, Professor, > Center for Statistics, Copenhagen Business School > Solbjerg Plads 3, 2000 Frederiksberg, Denmark > Phone: (+45)38153501 > Email: [email protected] Priv: [email protected] > > > > > > > > > [[alternative HTML version deleted]] ______________________________________________ [email protected] mailing list 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.
