Greetings listeRs - 

 

Given a data frame such as 

 

times

       time1    time2     time3    time4

1  70.408543 48.92378  7.399605 95.93050

2  17.231940 27.48530 82.962916 10.20619

3  20.279220 10.33575 66.209290 30.71846

4         NA 53.31993 12.398237 35.65782

5   9.295965       NA 48.929201       NA

6  63.966518 42.16304  1.777342       NA

 

one can use "transform" to total all or some columns, thus,

 

times2 <- transform(times,totaltime=time1+time2+time3+time4)

 

> times2

       time1    time2     time3    time4 totaltime

1  70.408543 48.92378  7.399605 95.93050  222.6624

2  17.231940 27.48530 82.962916 10.20619  137.8863

3  20.279220 10.33575 66.209290 30.71846  127.5427

4         NA 53.31993 12.398237 35.65782        NA

5   9.295965       NA 48.929201       NA        NA

6  63.966518 42.16304  1.777342       NA        NA

 

I cannot, however, find a way, other than "for" looping,

to use statistical functions, such as mean or sd, to 

compute the new column.  For example,

 

>
times2<-transform(times,meantime=(mean(c(time1,time2,time3,time4),na.rm=
TRUE)))

 

> times2

 

 time1    time2     time3    time4 meantime

1  70.408543 48.92378  7.399605 95.93050 45.54178

2  17.231940 27.48530 82.962916 10.20619 45.54178

3  20.279220 10.33575 66.209290 30.71846 45.54178

4         NA 53.31993 12.398237 35.65782 45.54178

5   9.295965       NA 48.929201       NA 45.54178

6  63.966518 42.16304  1.777342       NA 45.54178

 

How can this be done?  And, generally, what is the recommended method 

for creating computed new columns in data frames when "for" loops take 

too long?

 

With thanks for any suggestions,

 

Ben Fairbank

 

Using version 2.4.1 on a Windows XP professional operating system.

 


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