Here's one way:
ans = reshape(stock.returns,idvar='Date',
+ varying=list(names(stock.returns)[-1]),
+ direction='long',
+ times=names(stock.returns)[-1],
+ v.names='Return',timevar='Ticker')
rownames(ans) = NULL
ans
Date Ticker Return
1 20110301 MSFT 0.05
2 20110302 MSFT 0.01
3 20110301 GOOG -0.01
4 20110302 GOOG 0.04
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Wed, 16 Mar 2011, chris99 wrote:
Hi group,
I am trying to convert the organization of a data frame so I can do some
correlations between stocks,
I have something like this:
stock.returns <-
data.frame(rbind(c("MSFT","20110301",0.05),c("MSFT","20110302",0.01),c("GOOG","20110301",-0.01),c("GOOG","20110302",0.04)))
colnames(stock.returns) <- c("Ticker","Date","Return")
stock.returns
Ticker Date Return
1 MSFT 20110301 0.05
2 MSFT 20110302 0.01
3 GOOG 20110301 -0.01
4 GOOG 20110302 0.04
And want to convert it to this:
stock.returns <-
data.frame(rbind(c("20110301",0.05,-0.01),c("20110302",0.01,0.04)))
colnames(stock.returns) <- c("Date","MSFT","GOOG")
stock.returns
Date MSFT GOOG
1 20110301 0.05 -0.01
2 20110302 0.01 0.04
Can anyone offer any suggestions?
Thanks,
Chris
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