On 01/11/2012 12:09 AM, iliketurtles wrote:
Ray, your solution works and is indeed faster than mine!
It looks like it's going to take a few days to to 400,000 rows, still, which
is unfortunate.
Steve, thanks for your help, I'll definitely self-teach plyr and data.table.
I added a column with the first two digits of the module
data$XX <- substr(L[,2], 1, 2)
then created a data frame that summarized the first module of each call
and the length of the phone call
df <- with(data,
data.frame(FirstModule=tapply(XX, `phone calls`, `[[`, 1),
Length=tapply(XX, `phone calls`, length)))
then summarized the length of the phone calls associated with each module
with(df, tapply(Length, FirstModule, mean))
resulting in
> with(df, tapply(Length, FirstModule, mean))
82 84 92 93 94 96 97
1.000000 2.000000 1.750000 1.666667 1.000000 1.222222 1.666667
Martin
-----
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Isaac
Research Assistant
Quantitative Finance Faculty, UTS
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