As the footer says, "provide commented, _minimal_, self-contained,
reproducible code."
This is hardly "minimal" or reproducible.
Anyway, this probably ought to qualify as a plyr FAQ of some sort: don't use
the summarise function as the FUN argument within a function. Define a named or
anonymous function of your own as the help page for ddply describes. Too many
layers of syntactic sugar are involved for summarise to work within a function.
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Sent from my phone. Please excuse my brevity.
Franckx Laurent <laurent.franckx at vito.be> wrote:
>Dear all,
>
>I am encountering problems with the application of ddply within the
>body of a self-defined function.
>
>The script is the following:
>
>
>moncostcarmoto <- function(costtype){
> costaux_result <- data.frame()
> for (purp in PURPcount){for (per in PERcount){
> costcarin =
paste(c("CS_",costtype,"CAR"),collapse="")
> costmotoin =
paste(c("CS_",costtype,"MOTO"),collapse="")
> browser()
>COSTaux_AVCAR <-
>ddply(CARaux,c("SC","YEAR"),summarize,costcsolo
>sum(CARaux[[costcarin]]))
>COSTaux_AVMOTO <-
>ddply(CARaux,c("SC","YEAR"),summarize,costmoto>sum(CARaux[[costmotoin]]
))
>COSTaux <-
>join(COSTaux_AVCAR,COSTaux_AVMOTO,by=c("SC","YEAR"))
> COSTaux[ ,"PURP"] <-
as.factor(purp)
> COSTaux[ ,"PER"] <-
as.factor(per)
> costaux_result <- rbind(costaux_result,COSTaux)
> }}
>
> return(costaux_result)
>}
>
>Summarizing what it is supposed to do:
>
>
>* In previous step of our analysis, we have constructed a
>dataframe, CARaux. CARaux represents different cost categories (fuel
>prices, taxes, maintenance) etc for cars and motorcycles. The costs are
>differentiated according to the projection year ("YEAR")
considered,
>the policy scenario considered ("SC") and the car type considered.
>
>* The function moncostcarmoto takes as only argument one of
>four possible aggregate cost types: "MONCOST_EXCLTAX",
>"TAX",""FUELCOST" and
"MONCOST_INCLTAX"".
>
>* The output of the function is a summary of the costs per
>YEAR and SCENARIO, represented for all possible trip purposes
>(enumerated in PURPcount) and period of the day (enumerated in
>PERcount). Note that these costs do not depend on PURP and PER in the
>base scenario, but this is something I may want to modify in the future
>(and which explains why I iterate over these categories).
>
>The function fails in the following line:
>
>COSTaux_AVCAR <-
>ddply(CARaux,c("SC","YEAR"),summarize,costcsolo
>sum(CARaux[[costcarin]]))
>
>With the following error message:
>
>Error in (function(x, i, exact) if (is.matrix(i)) as.matrix(x)[[i]]
>else .subset2(x, :
> object 'costcarin' not found
>
>When I debugged the function, I found the following:
>
>Browse[1]> costcarin
>[1] "CS_MONCOST_EXCLTAXCAR"
>Browse[1]> summary(CARaux[[costcarin]])
> Min. 1st Qu. Median Mean 3rd Qu. Max.
>0.0000000 0.0000000 0.0001605 0.0166700 0.0048570 0.1633000
>Browse[1]> COSTaux_AVCAR <-
>ddply(CARaux,c("SC","YEAR"),summarize,costcsolo
>sum(CARaux[["CS_MONCOST_EXCLTAXCAR"]]))
>Browse[1]> summary(COSTaux_AVCAR)
> SC YEAR costcsolo
> BAU:31 Min. :2000 Min. :6.202
> 1st Qu.:2008 1st Qu.:6.202
> Median :2015 Median :6.202
> Mean :2015 Mean :6.202
> 3rd Qu.:2022 3rd Qu.:6.202
> Max. :2030 Max. :6.202
>Browse[1]> COSTaux_AVCAR <-
>ddply(CARaux,c("SC","YEAR"),summarize,costcsolo
>sum(CARaux[[costcarin]]))
>Error in (function(x, i, exact) if (is.matrix(i)) as.matrix(x)[[i]]
>else .subset2(x, :
> object 'costcarin' not found
>
>
>Thus, providing CARaux[["CS_MONCOST_EXCLTAXCAR"]] as an argument
to
>ddply() works, but CARaux[[costcarin]] does not, although costcarin
>"CS_MONCOST_EXCLTAXCAR".
>
>
>Best regards
>Laurent
>
>
>
>
>
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