Mutate_all except some columns

I have a dataframe containing a set of variables that I want to lag at different lenghts so that I can use them in regressions later on (instead of lagging one variable at a time manually).

I found this code on Stackoverflow that seems to do the trick:

df = data.frame(a = 1:10, b = 21:30) dplyr::mutate_all(df, lag) a b 1 NA NA 2 1 21 3 2 22 4 3 23 5 4 24 6 5 25 7 6 26 8 7 27 9 8 28 10 9 29 

The problem is that this lags every column and I have some columns that I don't want to be lagged. How do I adapt the above code so that the columns I don't want to be lagged are excluded? And also how do i lag a different lenghts, now it only lags by 1 as the default setting

2 Answers

I keep googling up this same Q&A and then noting that mutate_at() and mutate_if() are now superceded by across(), which provides a slightly easier-to-remember approach for the "mutate all except these columns" pattern

df = data.frame(a = 1:10, b = 21:30, c=31:40, d=41:50) > df a b c d 1 1 21 31 41 2 2 22 32 42 3 3 23 33 43 4 4 24 34 44 5 5 25 35 45 6 6 26 36 46 7 7 27 37 47 8 8 28 38 48 9 9 29 39 49 10 10 30 40 50 > # everythng but columns b and c > df %>% mutate(across(!b & !c, lag)) a b c d 1 NA 21 31 NA 2 1 22 32 41 3 2 23 33 42 4 3 24 34 43 5 4 25 35 44 6 5 26 36 45 7 6 27 37 46 8 7 28 38 47 9 8 29 39 48 10 9 30 40 49 

Have a look at mutate_at or mutate_if

library(dplyr) df = tibble(a = LETTERS[1:10], b = 21:30,c=31:40) #exclude column a df %>% mutate_at(vars(-("a")),lag) #> # A tibble: 10 x 3 #> a b c #> <chr> <int> <int> #> 1 A NA NA #> 2 B 21 31 #> 3 C 22 32 #> 4 D 23 33 #> 5 E 24 34 #> 6 F 25 35 #> 7 G 26 36 #> 8 H 27 37 #> 9 I 28 38 #> 10 J 29 39 #only column b df %>% mutate_at(c("b"),lag,4) #> # A tibble: 10 x 3 #> a b c #> <chr> <int> <int> #> 1 A NA 31 #> 2 B NA 32 #> 3 C NA 33 #> 4 D NA 34 #> 5 E 21 35 #> 6 F 22 36 #> 7 G 23 37 #> 8 H 24 38 #> 9 I 25 39 #> 10 J 26 40 #only character column df %>% mutate_if(is.character,lag,3) #> # A tibble: 10 x 3 #> a b c #> <chr> <int> <int> #> 1 <NA> 21 31 #> 2 <NA> 22 32 #> 3 <NA> 23 33 #> 4 A 24 34 #> 5 B 25 35 #> 6 C 26 36 #> 7 D 27 37 #> 8 E 28 38 #> 9 F 29 39 #> 10 G 30 40 

^{Created on 2020-04-20 by the reprex package (v0.3.0)}