Hi Jim, The dataset has 4 variables (dos, patientinformation1, patientinformation2, patientinformation3). In dos variable ther are months (May 2006 to March 2007) when the surgeries were formed. I need to calculate the percentage of missing values for each variable (patientinformation1, patientinformation2, patientinformation3) for each month. I need a common script to calculate that for each variable.
Thanks, Shreyasee On Mon, Jan 26, 2009 at 9:46 AM, jim holtman <jholt...@gmail.com> wrote: > What does you data look like? You could use 'split' and then examine > the data in each range to count the number missing. Would have to > have some actual data to suggest a solution. > > On Sun, Jan 25, 2009 at 8:30 PM, Shreyasee <shreyasee.prad...@gmail.com> > wrote: > > Hi, > > > > I have imported one dataset in R. > > I want to calculate the percentage of missing values for each month (May > > 2006 to March 2007) for each variable. > > Just to begin with I tried the following code : > > > > *for(i in 1:length(dos)) > > for(j in 1:length(patientinformation1) > > if(dos[i]=="May-06" && patientinformation1[j]=="") > > a <- j+1 > > a* > > > > The above code was written to calculate the number of missing values for > May > > 2006, but I am not getting the correct results. > > Can anybody help me? > > > > Thanks, > > Shreyasee > > > > [[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. > > > > > > -- > Jim Holtman > Cincinnati, OH > +1 513 646 9390 > > What is the problem that you are trying to solve? > [[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.
