Another solution (ex #3) is to return a data frame with at least two columns
and then remove the dummy one using drop = FALSE:
# ex #1. error
iris.by <- by(iris, iris[,5, drop = FALSE], length)
do.call("rbind", iris.by)
# ex #2. ok but no column heading
iris.by <- by(iris, iris[,5, drop=FALSE], function(x)
data.frame(length = length(x)))
do.call("rbind", iris.by)
# ex #3. ok
iris.by <- by(iris, iris[,5, drop=FALSE], function(x) data.frame(1,
length = length(x)))
do.call("rbind", iris.by)[,-1,drop=FALSE]
On 3/7/06, Vivek Satsangi <
[hidden email]> wrote:
> I am writing to document the answer for the next poor sod who comes along.
>
> To get tmp_byRet() into a multi-dimentional matrix, copy the object
> using as.vector(), then copy the dim and dimnames from tmp_byRet into
> the new object. However, this may not be what you want, since you
> probably want the values of the factors within the object (i.e. it
> should be a dataframe, not a matrix).
>
> To get tmp_byRet into a dataframe, use unique() to create a dataframe
> with just the unique values of your factors. Add a new column to the
> dataframe, where you will store the summary stats. Use a loop to
> populate this vector. Then use reshape() on the dataframe to get it to
> the shape you want it in. It is difficult at best to vectorize this
> and avoid the loop -- and trying to do so will lead to probably less
> transparent code.
>
> Vivek
>
>
> On 3/7/06, Vivek Satsangi <
[hidden email]> wrote:
> > Folks,
> > I know that I can do the following using a loop. That's been a lot
> > easier for me to write and understand. But I am trying to force myself
> > to use more vectorized / matrixed code so that eventually I will
> > become a better R programmer.
> >
> > I have a dataframe that has some values by Year, Quarter and Ranking.
> > The variable of interest is the return (F3MRet), to be weighted
> > averaged within the year, quarter and ranking. At the end, we want to
> > end up with a table like this:
> > year quarter ranking1 ranking2 ... ranking10
> > 1987 1 1.33 1.45 ... 1.99
> > 1987 2 6.45 3.22 ... 8.33
> > .
> > .
> > 2005 4 2.22 3.33 ... 1.22
> >
> > The dataset is too large to post and I can't come up with a small
> > working example very easily.
> >
> > I tried the Reshape() package and also the aggregate and reshape
> > functions. Those don't work too well becuase of the need to pass
> > weighted.mean a weights vector. I tried the by() function, but now I
> > don't know how to coerce the returned object into a matrix so that I
> > can reshape it.
> >
> > > fvs_weighted.mean <- function(y) weighted.mean(y$F3MRet, y$IndexWeight, na.rm=T);
> > > tmp_byRet <- by(dfReturns,
> > list(dfReturns$Quarter,dfReturns$Year,dfReturns$Ranking),
> > fvs_weighted.mean);
> >
> > And various other ways to get the tmp_byRet object into a matrix were
> > tried, eg. unlist(), a loop like this:
> > dfRet <- data.frame(tmp_byRet);
> > for(i in 1:dim(dfRet)[2]){
> > dfRet[ ,i] <- as.vector(dfRet[ ,i]);
> > }
> > In each case, I got some error or the other.
> >
> > So, please help me get unstuck. How can I get the tmp_byRet() object
> > into a matrix or a dataframe?
> >
> > --
>
> ______________________________________________
>
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>
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