R column mean by factor

Question

I have data set like this

data
name v1  v2  v3  v4  v5
a    1   2   7   9   3
b    3   8   6   4   8
c    2   5   0   1   9
a    6   0   6   2   1
c    3   9   4   7   5

name is a factor variable. I want to calculate mean of v2,v3,v4,v5 by the factor data$name. I used following command, but it did not work.

tapply(data[,3:6],data$name,mean)

Now, I used following code

newdata<-0
for (name in unique(data$name)){
    rowIndex <- which(data$name == name)
    result <- colMeans(data[rowIndex,])
    newdata[name,]<-result
}

The required result is obtained. But I want to know if there is some sleek method to do this.

Answer 1

Here's another way

library(data.table)
cols <- paste0("v", 2:5) # set the columns you want to operate on
setDT(data)[, Sums := rowSums(.SD), .SDcols = cols]
data[, list(Means = sum(Sums)/(.N*length(cols))), by = name]
##    name Means
## 1:    a  3.75
## 2:    b  6.50
## 3:    c  5.00

Edit

Per @Aruns suggestion, that would be probably much better

setDT(data)[, mean(c(v2,v3,v4,v5)), by=name]
##    name   V1
## 1:    a 3.75
## 2:    b 6.50
## 3:    c 5.00

Or per @Anandas suggestion

library(reshape2)
melt(setDT(data), id.vars = "name", measure.vars = cols)[, mean(value), by = name]
##    name   V1
## 1:    a 3.75
## 2:    b 6.50
## 3:    c 5.00

Answer 2

This can be done with a combination of the dplyr and tidyr packages:

library(dplyr)
library(tidyr)

data %>% gather(name, value, v2:v5) %>%
    group_by(name) %>% summarize(average=mean(value))
#   name average
# 1    a    3.75
# 2    b    6.50
# 3    c    5.00

---

This works because gather brings the v2:v5 columns together into a single column where they can be intuitively grouped:

data %>% gather(name, value, v2:v5)
#    name v1 name value
# 1     a  1   v2     2
# 2     b  3   v2     8
# 3     c  2   v2     5
# 4     a  6   v2     0
# 5     c  3   v2     9
# 6     a  1   v3     7
# ...