Applying function to multiple dataframe columns in R

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So I have a function that I want to apply to a range of columns in my dataframe

My dataframe has 111 columns and I want to de-mean each column based on its ID number.

I have the following code for the column named esgscore

demeaned_df <- df %>%
group_by(ID) %>%
mutate(avg_esgscore = mean(esgscore)) %>%
mutate(demeaned_esgscore = esgscore - avg_esgscore)

This does exactly what I want so I am happy with it but I essentially want to apply this function to columns 3:111 in my dataframe (df) and put these into a new dataframe called demeaned_df

Any help would be greatly appreciated

dplyr r for-loop function loops
1 Answers

Here is one idea. We can use across to apply the function to multiple columns. In this example, I applied the demean operation to columns from disp to carb.

library(dplyr)

mtcars2 <- mtcars %>%
  group_by(cyl) %>%
  mutate(across(disp:carb, .fns = function(x) x - mean(x)))
mtcars2
# # A tibble: 32 x 11
# # Groups:   cyl [3]
#     mpg   cyl   disp      hp    drat      wt   qsec      vs     am    gear   carb
#     <dbl> <dbl>  <dbl>   <dbl>   <dbl>   <dbl>  <dbl>   <dbl>  <dbl>   <dbl>  <dbl>
#  1  21       6 -23.3  -12.3    0.314  -0.497  -1.52  -0.571   0.571  0.143   0.571
#  2  21       6 -23.3  -12.3    0.314  -0.242  -0.957 -0.571   0.571  0.143   0.571
#  3  22.8     4   2.86  10.4   -0.221   0.0343 -0.527  0.0909  0.273 -0.0909 -0.545
#  4  21.4     6  74.7  -12.3   -0.506   0.0979  1.46   0.429  -0.429 -0.857  -2.43 
#  5  18.7     8   6.90 -34.2   -0.0793 -0.559   0.248  0      -0.143 -0.286  -1.5  
#  6  18.1     6  41.7  -17.3   -0.826   0.343   2.24   0.429  -0.429 -0.857  -2.43 
#  7  14.3     8   6.90  35.8   -0.0193 -0.429  -0.932  0      -0.143 -0.286   0.5  
#  8  24.4     4  41.6  -20.6   -0.381   0.904   0.863  0.0909 -0.727 -0.0909  0.455
#  9  22.8     4  35.7   12.4   -0.151   0.864   3.76   0.0909 -0.727 -0.0909  0.455
# 10  19.2     6 -15.7    0.714  0.334   0.323   0.323  0.429  -0.429  0.143   0.571
# # ... with 22 more rows
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