[R] remove NA in df results in NA, NA.1 ... rows

[Jeff Newmiller]

is.na(df2) is not doing what you think it is doing. Perhaps you should read ?na.omit.
---------------------------------------------------------------------------
Jeff Newmiller                        The     .....       .....  Go Live...
DCN:<jdnewmil at 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.felber at 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 at 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.