Maybe this is simple but I can't find answer on web. I have problem with mean calculation by factors by level. My data looks typicaly:

factor, value
a,1
a,2
b,1
b,1
b,1
c,1

I want to get vector A contains mean only for level "a" If I type A on consol I want to get 1.5 And this method for calculating mean, must use factors.

Thank you in advance for help.

有帮助吗?

解决方案 4

Just for fun posting the data.table solution although you probably should do what @lukeA suggested

library(data.table) 
A <- setDT(df)[factor == "a", mean(value)]
## [1] 1.5

其他提示

take a look at tapply, which lets you break up a vector according to a factor(s) and apply a function to each subset

> dat<-data.frame(factor=sample(c("a","b","c"), 10, T), value=rnorm(10))
> r1<-with(dat, tapply(value, factor, mean))
> r1
         a          b          c
 0.3877001 -0.4079463 -1.0837449
> r1[["a"]]
[1] 0.3877001

You can access your results using r1[["a"]] etc.

Alternatively, one of the popular R packages (plyr) has very nice ways of doing this.

> library(plyr)
> r2<-ddply(dat, .(factor), summarize, mean=mean(value))
> r2
  factor       mean
1      a  0.3877001
2      b -0.4079463
3      c -1.0837449
> subset(r2,factor=="a",select="mean")
       mean
1 0.3877001

You can also use dlply instead (which takes a dataframe and returns a list instead)

> dlply(dat, .(factor), summarize, mean=mean(value))$a
       mean
1 0.3877001

The following code asks for the mean of value when factor = a:

mean(data$value[data$factor == "a"])

Another simple possibilty would be the "by" function:

by(value, factor, mean)

You can get the mean of factor level "a" by:

factor_means <- by(value, factor, mean)
factor_means[attr(factor_means, "dimnames")$factor=="a"]

You can use ddply and pass summary as the function.

library(plyr) # import library
ddply(nameOfTheDataframe, ~ factor, function(data) summary(data$value))
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