Question

This is my dataframe SHORT:

ID    IDaxis    Y   Date-Time       Tdiff  
1   1   5   2012-06-11 13:10:30 0.00    
1   1   10  2012-06-11 15:10:30 2.00    
1   1   20  2012-06-11 17:10:30 2.00    
1   3   15  2012-06-11 13:20:30 0.00    
1   3   30  2012-06-11 14:20:30 1.00    
1   3   45  2012-06-11 17:20:30 3.00    
1   6   9   2012-06-11 13:35:30 0.00        
1   6   15  2012-06-11 15:35:30 2.00    
1   6   30  2012-06-11 18:35:30 3.00    
3   2   8   2012-06-11 13:50:30 0.00  
3   2   14  2012-06-11 14:55:30 1.083   
3   2   20  2012-06-11 16:55:30 2.00    
3   2   30  2012-06-11 19:00:30 2.083   
3   5   10  2012-06-11 13:40:30 0.00    
3   5   15  2012-06-11 16:45:30 3.083   

ID – plant
IDaxis – plant leaf
Y – length of leaf
Date – Time – date and time of measurement
Tdiff – time(h) interval between measurement

I want to do (Example SHORT1):
1) sum up Tdiff for IDaxis in column SHORT$Ttot
2) calculate difference between row in Y for IDaxis in column SHORT$Ydiff
3) sum up Ydiff for IDaxis in column SHORT$Ytot

Example SHORT1:

Ydiff – length interval between measurement
Ytot – sum of length interval from measurement to measurement
Ttot – sum of time interval from measurement to measurement

I know how to calculate this for IDaxis if I split dataframe. My problem is that I have three dataframe each 700 ID, each have 100 IDaxis. I don’t know how to do it automaticly for whole dataframe. Thank You in advance.

Answer 1

You can use ave:

SHORT$Ttot  <- ave(SHORT$Tdiff, SHORT$IDaxis, FUN = cumsum),
SHORT$Ydiff <- ave(SHORT$Y,     SHORT$IDaxis, FUN = diff),
SHORT$Ytot  <- ave(SHORT$Ydiff, SHORT$IDaxis, FUN = cumsum),

(if you don’t like the repeated SHORT$, look at functions like transform.)

You can also use the convenient plyr package:

library(plyr)
ddply(SHORT, "IDaxis", transform, Ttot  = cumsum(Tdiff),
                                  Ydiff = diff(Y),
                                  Ytot  = cumsum(Ydiff))