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r - dplyr - using mutate() like rowmeans()

I can't find the answer anywhere.

I would like to calculate new variable of data frame which is based on mean of rows.

For example:

data <- data.frame(id=c(101,102,103), a=c(1,2,3), b=c(2,2,2), c=c(3,3,3))

I want to use mutate to make variable d which is mean of a,b and c. And I would like to be able to make that by selecting columns in way d=mean(a,b,c), and also I need to use range of variables (like in dplyr) d=mean(a:c).

And of course

mutate(data, c=mean(a,b)) 

or

mutate(data, c=rowMeans(a,b)) 

doesn't work.

Can you give me some tip?

Regards

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by (71.8m points)

You're looking for

data %>% 
    rowwise() %>% 
    mutate(c=mean(c(a,b)))

#      id     a     b     c
#   (dbl) (dbl) (dbl) (dbl)
# 1   101     1     2   1.5
# 2   102     2     2   2.0
# 3   103     3     2   2.5

or

library(purrr)
data %>% 
    rowwise() %>% 
    mutate(c=lift_vd(mean)(a,b))

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