On Aug 28, 2012, at 9:20 PM, R. Michael Weylandt wrote:
On Tue, Aug 28, 2012 at 9:01 PM, Yi <liuyi.fe...@gmail.com> wrote:
Dear all,
Suppose my data frame is as follows:
id price distance
1 2 4
1 3 5
...
2 4 8
2 5 9
...
n 3 7
n 8 9
I would like to calculate the rank-order correlation between price
and
distance for each id.
cor(price,distance,method = "spearman") calculate a correlation for
all.
Then I tried to use
apply(data,list='id',cor(price , distance , method = "spearman"))
to
You seem to have been cut off mid-thought, but I'm guessing you want
something more like:
tapply(data, data$id, function(x), cor(x$price, x$distance, method =
"spearman"))
I am dubious. tapply takes an atomic vector rather than a dataframe as
its first argument. Generally one needs to use an lapply(split()) or
by() for such group operations involving more than one vector:
Here's my guess:
lapply( split(data, data$id), function(dfrm)
{ cor(x=dfrm[["price"]], y=dfrm[["distance"]], method =
"spearman") } )
OR:
by(data, data$id, function(dfrm) cor( x=dfrm[["price"]],
y=dfrm[["distance"]] , , method = "spearman") )
--
David Winsemius, MD
Alameda, CA, USA
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