R help - Nov 2010 - more flexible "ave"

Hi all,

I would like to calculate the percent of the total per group for this 
data.frame:

df <- data.frame(site = c("a", "a", "a",
"b", "b", "b"),
                  gr = c("total", "x1", "x2",
"x1", "total","x2"),
                  value1 = c(212, 56, 87, 33, 456, 213))
df

calcPercent <- function(df) {

     df <- transform(df, pct_val1 = ave(df[, -c(1:2)], df$gr,
                               FUN = function(x)
                               x/df[df$gr == "total",
"value1"]) )
}

# This works as intended...
w <- lapply(split(df, df$site), calcPercent)
w <- do.call(rbind, w)
w

# ... but when I add a new column
df$value2 <- c(1546, 560, 543, 234, 654, 312)

# the result is not what I want...
w <- lapply(split(df, df$site), calcPercent)
w <- do.call(rbind, w)
w

Clearly I have to change the function, (particularly "value1") - but 
how... I've also played around with "apply" but without any
success.

Thanks for any help!
Patrick

Here is a possible solution using sweep instead of ave:

   df <- data.frame(site = c("a", "a", "a",
"b", "b", "b"),
                    gr = c("total", "x1", "x2",
"x1", "total","x2"),
                    value1 = c(212, 56, 87, 33, 456, 213),
                    value2 = c(1546, 560, 543, 234, 654, 312) )

   sdf <- split(df, df$site)

   out <- lapply( sdf, function(mat){

     small.mat <- mat[ , -c(1,2)]
     totals    <- mat[ which( mat[ , "gr"] == "total" ),
-c(1,2) ]
     totals    <- as.numeric(totals)

     percent=sweep( small.mat, MARGIN=2, STATS=totals, FUN="/" )
     colnames(percent) <- paste("percent_", colnames(percent),
sep="")
     return( cbind(mat, percent) )
   } )

   do.call("rbind", out)

       site    gr value1 value2 percent_value1 percent_value2
   a.1    a total    212   1546     1.00000000      1.0000000
   a.2    a    x1     56    560     0.26415094      0.3622251
   a.3    a    x2     87    543     0.41037736      0.3512290
   b.4    b    x1     33    234     0.07236842      0.3577982
   b.5    b total    456    654     1.00000000      1.0000000
   b.6    b    x2    213    312     0.46710526      0.4770642

Also I think it might be more efficient to replace your "gr" variable 
with a binary 0,1 where 1 indicates the total. That way you don't have 
to generate x1, x2, x3, ....

Regards, Adai


On 30/11/2010 14:42, Patrick Hausmann wrote:
> Hi all,
>
> I would like to calculate the percent of the total per group for this
> data.frame:
>
> df<- data.frame(site = c("a", "a", "a",
"b", "b", "b"),
>                    gr = c("total", "x1",
"x2", "x1", "total","x2"),
>                    value1 = c(212, 56, 87, 33, 456, 213))
> df
>
> calcPercent<- function(df) {
>
>       df<- transform(df, pct_val1 = ave(df[, -c(1:2)], df$gr,
>                                 FUN = function(x)
>                                 x/df[df$gr == "total",
"value1"]) )
> }
>
> # This works as intended...
> w<- lapply(split(df, df$site), calcPercent)
> w<- do.call(rbind, w)
> w
>
> # ... but when I add a new column
> df$value2<- c(1546, 560, 543, 234, 654, 312)
>
> # the result is not what I want...
> w<- lapply(split(df, df$site), calcPercent)
> w<- do.call(rbind, w)
> w
>
> Clearly I have to change the function, (particularly "value1") -
but
> how... I've also played around with "apply" but without any
success.
>
> Thanks for any help!
> Patrick
>
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