Custom Function on Multiple Variables

Question

I am calculating the average after centering a variable. By centering it implies subtracting the mean of the variable from its original variable. I am using dplyr package. I am able to do it for one variable via mutate() function. How can I do the same for multiple variables using mutate?

set.seed(1)      # for reproducible example
train <- data.frame(X1=sample(1:100,100),
                 X2=1e6*sample(1:100,100),
                 X3=1e-6*sample(1:100,100))

library(dplyr)
train %>%  mutate(center = X1-mean(X1)) %>% 
  summarise(round(mean(center),4))

I am unable to get rid of X1 in the function. Thanks in advance! — Ujjawal Bhandari
– Ujjawal Bhandari, Commented Apr 6, 2017 at 11:55
Not sure if you are giving a fake example, but mean(x-mean(x)) is obviously 0 (regardless of x) and can give a different value only for floating point precision. — nicola
– nicola, Commented Apr 6, 2017 at 12:14

joel.wilson · Accepted Answer · 2017-04-06 12:05:59Z

3

Hope this is what you are looking for : (add na.rm = TRUE is required inside mean()

library(dplyr)
train %>% summarise_all(function(x) mean(x - mean(x)))
#  X1 X2            X3
#   0  0 -3.251647e-21

answered Apr 6, 2017 at 12:05

joel.wilson

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Comments

Ranjan Raj · Accepted Answer · 2017-04-07 05:47:31Z

0

train %>% mutate_each(funs(((function(x){x-mean(x)})(.)))) %>% 
summarise_each(funs(mean(.), na.rm = TRUE)))

edited Apr 7, 2017 at 5:47

answered Apr 6, 2017 at 12:05

Ranjan Raj

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