Hello,
I have a large data frame and am aiming to create a summary data frame in
order to plot quarterly means by age. However, it seems as though I am
taking a very long winded approach to this - can anybody point me in the
direction of something neater?
#original table is dat2,
dat5<- tapply (dat2$col1, INDEX=list(dat2$Age, dat2$Quarter), FUN=mean)
dat5 <- data.frame(dat5)
names(dat5) <- c("qt1", "qt2", "qt3", "qt4")
dat6 <- data.frame(age=row.names(dat5), dat5)
#transform rownames / 1st column from factor to variables
dat7 <- as.numeric (as.character(dat6$age))
#create new table with 5 columns
dat8 <- cbind (dat7, dat6$qt1, dat6$qt2, dat6$qt3, dat6$qt4)
#still need to add column names to this new table...
I am using R2.0.0 on W2K.
Thanks
Louize
neater way to create data frame?
2 messages · Louize Hill, PIKAL Petr
Hi Louize
On 8 Nov 2004 at 22:58, Louize Hill wrote:
Hello, I have a large data frame and am aiming to create a summary data frame in order to plot quarterly means by age. However, it seems as though I am taking a very long winded approach to this - can anybody point me in the direction of something neater? #original table is dat2, dat5<- tapply (dat2$col1, INDEX=list(dat2$Age, dat2$Quarter), FUN=mean)
Maybe better approach would be to use aggregate dat5<- aggregate (dat2$col1, list(Age=dat2$Age, Quarter=dat2$Quarter) With it you will get data frame with 3 columns (first two will be factors). and reshape the result, if necessary. Cheers Petr
dat5 <- data.frame(dat5)
names(dat5) <- c("qt1", "qt2", "qt3", "qt4")
dat6 <- data.frame(age=row.names(dat5), dat5)
#transform rownames / 1st column from factor to variables
dat7 <- as.numeric (as.character(dat6$age))
#create new table with 5 columns
dat8 <- cbind (dat7, dat6$qt1, dat6$qt2, dat6$qt3, dat6$qt4)
#still need to add column names to this new table...
I am using R2.0.0 on W2K.
Thanks
Louize
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