R help - May 2024 - dplyr, group_by and selective action according to each group

Dear RHelp-list,

 ?? Using dplyr and the group_by approach on a dataframe, I want to be 
able to apply a specific action according to the group name. The code 
bellow works, but I am not able to write it in a more esthetic way using 
dplyr. Can somebody help me to find a better solution ?

Thank you

Best regards

Laurent

df_test <- data.frame( x1=1:9, x2=1:9,
gr=rep(paste0("gr",1:3),each=3))
df_test? <-? df_test %>% dplyr::group_by(gr) %>%
 ? group_modify(.f=function(.x,.y){
 ??? print(paste0("Nom du groupe : ",.y[["gr"]]))
 ??? switch(as.character(.y[["gr"]])
 ?????????? , gr1 = {.x[,"x1"] <- .x[,"x1"]+1}
 ?????????? , gr2 = {.x[,"x1"] <- 0}
 ?????????? , gr3 = {.x[,"x1"] <- .x[,"x1"]+2}
 ?????????? , {stop(paste0('The group ',.y[["gr"]]," is
not taken into
account"))}
 ??? )
 ??? return(.x) }) %>% ungroup()

df_test

Laurent:
As I don't use dplyr, this won't help you, but I hope you and others may
find it entertaining anyway.

If I understand you correctly (and ignore this if I have not), there are a
ton of ways to do this in base R, including using switch() along the lines
you noted in your post. However, when the functions get sufficiently
complicated or numerous, it may be useful to store them in a named list and
use the names to call them in some sort of loop. Here I have just used your
anonymous functions in the list, but of course you could have used already
existing functions instead.

## your example
df_test <- data.frame( x1=1:9, x2=1:9,
gr=rep(paste0("gr",1:3),each=3))

## function list with the relevant names
funcs <- list(gr1 = \(x)x+1, gr2 = \(x)0, gr3 = \(x)x+2)
## Alternatively you could do this if you had many different functions:
## funcs <- list(\(x)x+1, \(x)0,  \(x)x+2)
## names(funcs) <- sort(unique(df_test$gr))
## note that sort() is unnecessary in your example, but I think that it
would
## be helpful if you had a lot of different groups and corresponding
functions
## to track.

##Now the little loop to call the functions
df_test$x1 <- with(df_test,{
   for(nm in names(funcs))
      x1[gr == nm] <- funcs[[nm]](x1[gr == nm])
   x1}
)

#################
Note that the above uses one of the features that I really like about R --
functions are full first class objects that can be thrown around and
handled just like any other "variables" . So funcs[[nm]](whatever)
seems to
me to be a natural way to choose and call the function you want. You may
disagree, of course.

Caveat: I make no claims about the efficiency or lack thereof of the above.

Cheers,
Bert

On Fri, May 24, 2024 at 12:35?PM Laurent Rhelp <laurentRHelp at free.fr>
wrote:
> Dear RHelp-list,
>
>     Using dplyr and the group_by approach on a dataframe, I want to be
> able to apply a specific action according to the group name. The code
> bellow works, but I am not able to write it in a more esthetic way using
> dplyr. Can somebody help me to find a better solution ?
>
> Thank you
>
> Best regards
>
> Laurent
>
> df_test <- data.frame( x1=1:9, x2=1:9,
gr=rep(paste0("gr",1:3),each=3))
> df_test  <-  df_test %>% dplyr::group_by(gr) %>%
>    group_modify(.f=function(.x,.y){
>      print(paste0("Nom du groupe : ",.y[["gr"]]))
>      switch(as.character(.y[["gr"]])
>             , gr1 = {.x[,"x1"] <- .x[,"x1"]+1}
>             , gr2 = {.x[,"x1"] <- 0}
>             , gr3 = {.x[,"x1"] <- .x[,"x1"]+2}
>             , {stop(paste0('The group ',.y[["gr"]],"
is not taken into
> account"))}
>      )
>      return(.x) }) %>% ungroup()
>
> df_test
>
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