is.na(df2) is not doing what you think it is doing. Perhaps you should read ?na.omit. --------------------------------------------------------------------------- Jeff Newmiller The ..... ..... Go Live... DCN:<jdnew...@dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/Batteries O.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --------------------------------------------------------------------------- Sent from my phone. Please excuse my brevity.
raphael.fel...@art.admin.ch wrote: >Good morning! > >I have the following data frame (df): > >X.outer Y.outer X.PAD1 Y.PAD1 X.PAD2 Y.PAD2 X.PAD3 Y.PAD3 >X.PAD4 Y.PAD4 >73 574690.0 179740.0 574690.2 179740.0 574618.3 179650 574729.2 179674 >574747.1 179598 >74 574680.6 179737.0 574693.4 179740.0 574719.0 179688 574831.8 179699 >574724.9 179673 >75 574671.0 179734.0 574696.2 179740.0 574719.0 179688 574807.8 179787 >574729.2 179674 >76 574663.6 179736.0 574699.1 179734.0 574723.5 179678 574703.4 179760 >574831.8 179699 >77 574649.9 179734.0 574704.7 179724.0 574724.9 179673 574702.4 179755 >574852.3 179626 >78 574647.3 179742.0 574706.9 179719.0 574747.1 179598 574702.0 179754 >574747.1 179598 >79 574633.6 179739.0 574711.4 179710.0 574641.8 179570 574698.0 179747 > NA NA >80 574634.9 179732.0 574716.6 179698.0 574639.6 179573 574700.2 179738 > NA NA >81 574616.5 179728.6 574716.7 179695.0 574618.3 179650 574704.4 179729 > NA NA >82 574615.4 179731.0 574718.2 179690.0 NA NA 574708.1 179724 > NA NA >83 574614.4 179733.6 574719.1 179688.0 NA NA 574709.3 179720 > NA NA >... > >44 574702.0 179754.0 NA NA NA NA NA NA > NA NA > >45 574695.1 179751.0 NA NA NA NA NA NA > NA NA > >46 574694.4 179752.0 NA NA NA NA NA NA > NA NA > >Which I subset to > >df2 <- df[,c("X.PAD2","Y.PAD2")] > >df2 > > X.PAD2 Y.PAD2 > >73 574618.3 179650 > >74 574719.0 179688 > >75 574719.0 179688 > >76 574723.5 179678 > >77 574724.9 179673 > >78 574747.1 179598 > >79 574641.8 179570 > >80 574639.6 179573 > >81 574618.3 179650 > >82 NA NA > >83 NA NA > >... > >44 NA NA > >45 NA NA > >46 NA NA > > > > > >followed by removing the NA's using > > > >df2 <- df2[!is.na(df2),] > > > >If I now call df2, I get: > > > > X.PAD2 Y.PAD2 > >73 574618.3 179650 > >74 574719.0 179688 > >75 574719.0 179688 > >76 574723.5 179678 > >77 574724.9 179673 > >78 574747.1 179598 > >79 574641.8 179570 > >80 574639.6 179573 > >81 574618.3 179650 > >NA NA NA > >NA.1 NA NA > >NA.2 NA NA > >NA.3 NA NA > >NA.4 NA NA > >NA.5 NA NA > >NA.6 NA NA > >NA.7 NA NA > >NA.8 NA NA > > > >It seems there are still NA's in my data frame. How can I get rid of >them? What is the meaning of the rows numbered NA, NA.1 and so on? > > > >Thanks for any hints. > > > >Best regards > > > >Raphael Felber > > > [[alternative HTML version deleted]] > >______________________________________________ >R-help@r-project.org 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. ______________________________________________ R-help@r-project.org 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.