On Aug 16, 2011, at 3:37 PM, Sam Albers wrote:
## Hello there,
## I have an issue where I need to use the value of column names to
multiply with the individual values in a column and I have many
columns to do this over. I have data like this where the column names
are numbers:
mydf <- data.frame(`2.72`=runif(20, 0, 125),
`3.2`=runif(20, 50, 75),
`3.78`=runif(20, 0, 100),
yy= head(letters,2), check.names=FALSE)
> mydf
2.72 3.2 3.78 yy
1 31.07874 74.48555 89.306591 a
2 123.68290 74.30030 11.943576 b
3 89.64024 68.26378 97.627211 a
4 81.46604 59.79607 91.005217 b
## I had been doing something like this but this seems rather tedious
and clunky. These append the correct values to my dataframe but is
there any way that I can do this generally over each column, also
using each column name as the multiplier for that column?
mydf$vd2.72 <- mydf$'2.72'*2.72
mydf$vd3.2 <- mydf$'3.2'*3.2
mydf$vd3.78 <- mydf$'3.78'*3.78
## So can I get to this point with a more generalized solution? For
now, I would also prefer to keep this in wide format and I am aware
(thanks to the list!) that I could use melt() to get the values I
want.
You will get the warning that last last column is not "going right"
but otherwise this returns what you asked for:
sapply(1:length(mydf), function(i) mydf[[i]]* as.numeric(names(mydf)
[i]) )
[,1] [,2] [,3] [,4]
[1,] 84.53416 238.3538 337.57891 NA
[2,] 336.41748 237.7610 45.14672 NA
[3,] 243.82145 218.4441 369.03086 NA
[4,] 221.58762 191.3474 343.99972 NA
[5,] 81.78911 213.0770 97.90072 NA
snipped remainder
--
David Winsemius, MD
West Hartford, CT
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