Convert table into matrix by column names [duplicate]
I have data frame that looks like the following
models cores time
1 4 1 0.000365
2 4 2 0.000259
3 4 3 0.000239
4 4 4 0.000220
5 8 1 0.000259
6 8 2 0.000249
7 8 3 0.000251
8 8 4 0.000258
... etc
I would like to convert it into a table/matrix with #models for rows labels, the #cores for the columns labels and time as the data entries
e.g.
1 2 3 4 5 6 7 8
1 time data
4 time data
开发者_如何学运维currently I'm using for loops to convert it into this structure, though I am wondering if there was a better method?
Check method cast from reshape package
# generate test data
x <- read.table(textConnection('
models cores time
4 1 0.000365
4 2 0.000259
4 3 0.000239
4 4 0.000220
8 1 0.000259
8 2 0.000249
8 3 0.000251
8 4 0.000258'
), header=TRUE)
library(reshape)
cast(x, models ~ cores)
results:
models 1 2 3 4
1 4 0.000365 0.000259 0.000239 0.000220
2 8 0.000259 0.000249 0.000251 0.000258
Here is a version using the base function reshape
:
y <- reshape(x, direction="wide", v.names="time", timevar="cores",
idvar="models")
with the output
models time.1 time.2 time.3 time.4
1 4 0.000365 0.000259 0.000239 0.000220
5 8 0.000259 0.000249 0.000251 0.000258
With the hard work of reshaping done, you can extract the part you want:
res <- data.matrix(subset(y, select=-models))
rownames(res) <- y$models
colnames(res) <- substr(colnames(res),6,7)
And you get the matrix:
1 2 3 4
4 0.000365 0.000259 0.000239 0.000220
8 0.000259 0.000249 0.000251 0.000258
You don't need the reshape package, there's a builtin function reshape
which can do it.
> reshape(x,idvar="models",timevar="cores",direction="wide")
models time.1 time.2 time.3 time.4
1 4 0.000365 0.000259 0.000239 0.000220
5 8 0.000259 0.000249 0.000251 0.000258
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