Ted,
Based upon your code below, you might be better off using two lapply()
constructs to create the x and y results separately, taking advantage of
lapply()'s built-in ability to create lists 'on the fly', while returning a
NULL when the function will not be applied to the data based upon your
Thanks Marc
Part of the challenge here is that EVERYTHING is dynamic. New data is being
added to the DB all the time Each active ID makes a new sample very day or
at a minimum every week, and new IDs are added every week. So I can't hard
code anything. If, for a given ID, I had 50 weekly sampl
Ted,
I may not be completely clear on how you have your processes implemented, but
some thoughts:
If you will be creating multiple lists initially, where each list (say z1...z4)
contains 1 or more data frames and all of the data frames have the same column
structure, you can use:
do.call(rb
Thanks Marc
The next part of the question, though, involves the fact that there is a new
'z' list made in almost every iteration through the ID loop.
I guess there are two parts to the question. First, how would I make a list
containing all the data frames created by a call to rbind? I assume,
On Jul 15, 2010, at 2:18 PM, Ted Byers wrote:
> The data.frame is constructed by one of the following functions:
>
> funweek <- function(df)
> if (length(df$elapsed_time) > 5) {
>rv = fitdist(df$elapsed_time,"exp")
>rv$year = df$sale_year[1]
>rv$sample = df$sale_week[1]
>rv$granu
The data.frame is constructed by one of the following functions:
funweek <- function(df)
if (length(df$elapsed_time) > 5) {
rv = fitdist(df$elapsed_time,"exp")
rv$year = df$sale_year[1]
rv$sample = df$sale_week[1]
rv$granularity = "week"
rv
}
funmonth <- function(df)
if (
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