How can I make the output from tapply() into a data.frame
I have a data.frame in R that looks like this:
score rms template aln_id description
1 -261.410 4.951 2f22A.pdb 2F22A_1 S_00001_0000002_0
2 -231.987 21.813 1wb9A.pdb 1WB9A_开发者_C百科4 S_00002_0000002_0
3 -263.722 4.903 2f22A.pdb 2F22A_3 S_00003_0000002_0
4 -269.681 17.732 1wbbA.pdb 1WBBA_6 S_00004_0000002_0
5 -258.621 19.098 1rxqA.pdb 1RXQA_3 S_00005_0000002_0
6 -246.805 6.889 1rxqA.pdb 1RXQA_15 S_00006_0000002_0
7 -281.300 16.262 1wbdA.pdb 1WBDA_11 S_00007_0000002_0
8 -271.666 4.193 2f22A.pdb 2F22A_2 S_00008_0000002_0
9 -277.964 13.066 1wb9A.pdb 1WB9A_5 S_00009_0000002_0
10 -261.024 17.153 1yy9A.pdb 1YY9A_2 S_00001_0000003_0
I can calculate summary statistics on the data.frame like this:
> tapply( d$score, d$template, mean )
1rxqA.pdb 1wb9A.pdb 1wbbA.pdb 1wbdA.pdb 1yy9A.pdb 2f22A.pdb
-252.7130 -254.9755 -269.6810 -281.3000 -261.0240 -265.5993
Is there an easy way that I coerce this output back into a data.frame? I'd like for it to have these two columns:
d$template
mean
I love tapply, but right now I'm cutting and pasting the results from tapply into a text file and hacking it up a bit to get the summary statistics that I want with appropriate names. This feels very wrong, and I'd like to do something better!
There are a lot of different ways to transform the output from a tapply call into a data.frame.
But it's much simpler to avoid the call to tapply in the first place and substitute that with a call to a similar function that returns a data frame instead of a vector:
more specifically:
tapply returns a vector
aggregate returns a data frame
so just change your function call from tapply to aggregate, like so:
data(iris) # in 'datasets' just call 'data' and pass in 'iris' as an argument
tx = tapply(iris$Sepal.Length, list(iris$Species), mean)
# returns: versicolor virginica
5.94 6.59
class(tx)
# returns: vector
tx = aggregate(iris$Sepal.length, list(iris$Species), mean)
# returns:
Group.1 x
1 versicolor 5.94
2 virginica 6.59
class(tx)
# returns: data.frame
You can try this:
mn <- tapply(d$score,d$template,mean)
df <- data.frame(template=names(mn),mean=mn)
library(plyr)
ddply(d, "template", summarise, mean = mean(score))
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