[R] Subsetting data frame problem....

[Simon Blomberg]

Or use complete.cases

df.complete <- df[complete.cases(df),]

Simon.

On Wed, 2008-01-02 at 13:21 +1000, Ross Darnell wrote:
> You could try 
> 
> 
> > complete.case.df <- na.omit(df)
> 
> 
> Ross Darnell
> 
> 
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
> On Behalf Of Marko Milicic
> Sent: Wednesday, 2 January 2008 11:50 AM
> To: r-help at r-project.org
> Subject: [R] Subsetting data frame problem....
> 
> Dear R users,
> 
> I'm new but already fascinated R user so please forgive for my
> ignorance. I have the problem, I read most of help pages but couldn't
> find the solution. The problem follows....
> 
> I have large data set 10,000 rows and more than 100 columns... Say
> something like
> 
> var1,var2,var2,var4.......var120
> -------------------------------------------
> 12,12,345,657,67,8.....
> 12,12,345,657,0,8.....
> NA,12,345,657,NA,8.....
> 12,12,NA,657,67,8.....
> 12,12,345,657,NA,8.....
> 
> I would like to select only rows where all variables are not NA.... so
> I can do something like
> 
> 
> df <- subset(
>                               df
>                               , !is.na(var1) & !is.na(var2) &
> !is.na(var3) & !is.na(var4) & !is.na(var5)......................
>                           );
> 
> 
> But that would be very bad solution because I have more than 100
> variables and if would be lengthy code to maintan..... also, it might
> be error prone programming style...Am I right?
> 
> my question is if there is some smarter way of doing this which would
> work even if I have 1000 variables???
> 
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 
> ______________________________________________
> 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.
-- 
Simon Blomberg, BSc (Hons), PhD, MAppStat. 
Lecturer and Consultant Statistician 
Faculty of Biological and Chemical Sciences 
The University of Queensland 
St. Lucia Queensland 4072 
Australia
Room 320 Goddard Building (8)
T: +61 7 3365 2506 
email: S.Blomberg1_at_uq.edu.au

Policies:
1.  I will NOT analyse your data for you.
2.  Your deadline is your problem.

The combination of some data and an aching desire for 
an answer does not ensure that a reasonable answer can 
be extracted from a given body of data. - John Tukey.