R help - Oct 2015 - apply function across dataframe columns for non-exclusive groups

Hello all,

I've been banging my head over what must be a simple solution.  I would 
like to apply a function across columns of a dataframe for rows grouped 
across different columns.  These groups are not exclusive.  See below 
for an example.  Happy to use dplyr, data.table, or whatever.  Any 
guidance appreciated!

Thanks,
Allie


desired algorithm: calculate a/(a+b) for each TRUE and FALSE grouping of 
columns grp1 and grp2.

this_df = data.frame(a = c(1,2,3,4,5), b = c(7,8,9,10,11), grp1 = 
c(T,T,F,F,F), grp2 = c(F,T,F,T,F))

desired output (doesn't have to be exactly this format, but something 
along these lines):

grp1 T 0.166
grp1 F 0.286
grp2 T 0.25
grp2 F 0.25

The calculation appears to be sum(a)/(sum(a)+sum(b)).

library(dplyr)
library(tidyr)
result <- (   this_df
          %>% gather( group, truth, -c(a,b) )
          %>% group_by( group, truth )
          %>% summarise( calc = sum(a)/(sum(a)+sum(b)) )
          %>% as.data.frame
          )

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On October 21, 2015 1:30:46 PM GMT+02:00, Alexander Shenkin <ashenkin at
ufl.edu> wrote:
>Hello all,
>
>I've been banging my head over what must be a simple solution.  I would
>
>like to apply a function across columns of a dataframe for rows grouped
>
>across different columns.  These groups are not exclusive.  See below 
>for an example.  Happy to use dplyr, data.table, or whatever.  Any 
>guidance appreciated!
>
>Thanks,
>Allie
>
>
>desired algorithm: calculate a/(a+b) for each TRUE and FALSE grouping
>of 
>columns grp1 and grp2.
>
>this_df = data.frame(a = c(1,2,3,4,5), b = c(7,8,9,10,11), grp1 = 
>c(T,T,F,F,F), grp2 = c(F,T,F,T,F))
>
>desired output (doesn't have to be exactly this format, but something 
>along these lines):
>
>grp1 T 0.166
>grp1 F 0.286
>grp2 T 0.25
>grp2 F 0.25
>
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