Hi,
May be this helps:
small - read.table(text=monthend_n ticker wgtdiff ret interval b1 b2 b3 b4 b5
b6
1 19990228 AA 0.7172 -2.58 0.33896 -0.5868 -0.24784 0.09112 0.43008 0.76904
1.108
2 19990228 AAPL -0.0828 -15.48 0.33896 -0.5868 -0.24784 0.09112 0.43008 0.76904
1.108
3 19990228 ABCW 0.0966 -7.36 0.33896 -0.5868 -0.24784 0.09112 0.43008 0.76904
1.108
705 19990331 AA 0.1932 1.7 0.31602 -0.7641 -0.44808 -0.13206 0.18396 0.49998
0.816
706 19990331 AAPL 0.033 3.23 0.31602 -0.7641 -0.44808 -0.13206 0.18396 0.49998
0.816
707 19990331 ABF 0.154 -20.51 0.31602 -0.7641 -0.44808 -0.13206 0.18396 0.49998
0.816
708 19990331 ABI 0.286 8.33 0.31602 -0.7641 -0.44808 -0.13206 0.18396 0.49998
0.816,sep=,header=TRUE,stringsAsFactors=FALSE)
res - mutate(small,bins=unlist(dlply(small,.(monthend_n),cutfunc)))
res$bins
#[1] 4 2 3 4 3 3 4
ddply(small,.(monthend_n),summarize,bins=cut(wgtdiff,breaks=unique(c(b1,b2,b3,b4,b5,b6)),labels=F))[,2]
#[1] 4 2 3 4 3 3 4
unlist(lapply(split(small,small$monthend_n),cutfunc),use.names=FALSE)
#[1] 4 2 3 4 3 3 4
A.K.
On Thursday, January 16, 2014 2:01 AM, Amitabh Dugar cleverc...@yahoo.com
wrote:
I have a dataframe small whch has 5,000 rows and contains data for several
tickers every month, as below:
monthend_n ticker wgtdiff ret interval b1 b2 b3 b4 b5 b6
1 19990228 AA 0.7172 -2.58 0.33896 -0.5868 -0.24784 0.09112 0.43008 0.76904
1.108
2 19990228 AAPL -0.0828 -15.48 0.33896 -0.5868 -0.24784 0.09112 0.43008 0.76904
1.108
3 19990228 ABCW 0.0966 -7.36 0.33896 -0.5868 -0.24784 0.09112 0.43008 0.76904
1.108
… …
705 19990331 AA 0.1932 1.7 0.31602 -0.7641 -0.44808 -0.13206 0.18396 0.49998
0.816
706 19990331 AAPL 0.033 3.23 0.31602 -0.7641 -0.44808 -0.13206 0.18396 0.49998
0.816
707 19990331 ABF 0.154 -20.51 0.31602 -0.7641 -0.44808 -0.13206 0.18396 0.49998
0.816
708 19990331 ABI 0.286 8.33 0.31602 -0.7641 -0.44808 -0.13206 0.18396 0.49998
0.816
etc.
Variables b1 through b6 are break points that I want to use in the cut
function and they vary each month according to the distribution of the variable
wgtdiff during that month.
To handle this I wrote a function as below:
cutfunc - function(df)
{
vec - df$wgtdiff
# need to apply unique function as break points within each month are same for
all tickers (b1-b6 values same in each within month)
breaks - c(unique(df$b1), unique(df$b2), unique(df$b3), unique(df$b4),
unique(df$b5), unique(df$b6))
bin - cut(vec, breaks,labels=F)
bin
}
Then I tried:
temp4 - ddply(small, .(monthend_n), summarize, bins=cutfunc(small))
I was expecting to get back a data frame with 5,000 rows with bins assignments
for each ticker, and if there are 6 break points the bin #s should range from 1
to 5.
However instead I get a data frame with 40,000 rows and bin # ranging from 1-
40, as below:
monthend_n bins
1 19990228 40
2 19990228 17
3 19990228 22
...
5000 19990228 17
5001 19990331 40
5002 19990331 17
5003 19990331 22
etc
It seems ddply doesn't pass in monthly pieces of the data frame small into my
cutfunc in the way I expect
Any guidance is appreciated.
Thanks
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
