I'm an R newbie and I'm having a lot of trouble doing something that is probably very simple. I have a big dataset split up into groups by country code, and I want to take a 3-month rolling average of a price index, by country, and then put it into a new column that matches up to the appropriate month. I've been trying to use rollmean like this with no success (code and error messages below):
> leader$last3<-tapply(leader, leader$ccode,
function(x) rollmean(leader$GI_delta, 3, na.pad=T))
Error in tapply(leader, leader$ccode, function(x) rollmean(leader$GI_delta, :
arguments must have same length
> leader$last3<-ddply(leader, .(ccode),
rollmean(GI_delta, 3, na.pad=T))
Error in llply(.data = .data, .fun = .fun, ..., .progress = .progress, :
.fun is not a function.
Any help would be much appreciated!
If you want to make a new column, then try using ave
. It resembles tapply
but returns a vector of the same length as its first argument. My experience is that it is a lot faster than ddply
:
require(zoo)
leader$last3<-ave(leader$GI_delta, leader$ccode,
FUN= function(x) rollmean(x, k=3, na.pad=T) )
In your first attempt, your function does not use its x
argument,
and always returns the same thing (a vector with the wrong size).
In addition, the first argument, should be a vector.
Lastly, tapply
returns a list of vectors:
you cannot put the result directly into a data.frame.
library(zoo)
n <- 10
leader <- data.frame(
ccode = rep(LETTERS[1:3],each=n),
GI_delta = rnorm(3*n)
)
tapply(
leader$GI_delta,
leader$ccode,
function(x) rollmean(x, 3, na.pad=TRUE)
)
In your second example, the third argument of plyr
should be a function, not an expression.
If you want to use an expression, you can use summarize
or transform
as a function (summarize
returns a 1-row data.frame
for each value of ccode
, while transform
keeps the number of rows unchanged),
and put the expressions as further arguments.
library(plyr)
ddply(
leader, "ccode",
transform,
last3 = rollmean( GI_delta, 3, align="right", na.pad=TRUE )
)
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