R: Recoding variables using recode, mutate and case_when

Question

I want to recode the following values < 4 = -1, 4 = 0, > 4 = 1 for the following variables defined by core.vars in the dataset, and still keep the rest of the variables in the data frame.

temp.df <- as.tibble (mtcars)
other.vars <- c('hp', 'drat', 'wt')
core.vars <- c('mpg', 'cyl', 'disp')
temp.df <- rownames_to_column (temp.df, var ="cars_id")
temp.df <- temp.df %>% mutate_if (is.integer, as.numeric)

I have tried a number of ways to implement this. Using case_when, mutate, recode but with no luck. recode requires a vector and so my thought was to create a vector using case_when or mutate for each variable of interest and then recoding the values. But they have failed.

temp.df <- temp.df %>% 
           mutate_at(.vars %in% (core.vars)), '< 4' = "-1", '4' = "0", '> 4' = "1")

Error: unexpected ',' in "temp.df <- temp.df %>% mutate_at(.vars %in% (core.vars)),"

temp.df <- temp.df %>% 
           mutate_at(vars(one_of(core.vars)), '< 4' = "-1", '4' = "0", '> 4' = "1")

Error in inherits(x, "fun_list") : argument ".funs" is missing, with no default

 temp.df <- temp.df %>% 
            mutate (temp.df, case_when (vars(one_of(core.vars)), recode ('< 4' = "-1", '4' = "0", '> 4' = "1")))

Error in mutate_impl(.data, dots) : Column temp.df is of unsupported class data.frame

 temp.df <- temp.df %>% 
            case_when (vars(one_of(core.vars)), recode ('< 4' = "-1", '4' = "0", '> 4' = "1"))

Error in recode.character(< 4 = "-1", 4 = "0", > 4 = "1") : argument ".x" is missing, with no default

temp.df <- temp.df %>% rowwise() %>% mutate_at(vars (core.vars),
                                            funs (case_when (
                                                recode(., '< 4' = -1, '0' = 0, '>4' = 1)
                                            ))) %>%
 ungroup()`

Error in mutate_impl(.data, dots) : Evaluation error: Case 1 (recode(mpg,< 4= -1,0= 0,>4= 1)) must be a two-sided formula, not a double. In addition: Warning message: In recode.numeric(mpg, < 4 = -1, 0 = 0, >4 = 1) : NAs introduced by coercion

Previous questions on the forum include how to do this for individual variables, however as mentioned I have 100 variables and 300 samples so inputting them individually line by line is not an option.

Ideally, it would be nice to not create a separate data frame and then do join, or to create multiple separate variables as mutate would do.

I am sure there is a a for loop and/or ifelse method for this, but was trying to use tidyverse to achieve the goals. Any suggestions would be helpful.

Answer 1

temp.df %>%
  mutate_at(vars(one_of(core.vars)), 
            function(x) case_when(
              x < 4 ~ -1,
              x == 4 ~ 0,
              x > 4 ~ 1
            ))

Output

# A tibble: 32 x 12
   cars_id             mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
   <chr>             <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
 1 Mazda RX4             1     1     1   110  3.9   2.62  16.5     0     1     4     4
 2 Mazda RX4 Wag         1     1     1   110  3.9   2.88  17.0     0     1     4     4
 3 Datsun 710            1     0     1    93  3.85  2.32  18.6     1     1     4     1
 4 Hornet 4 Drive        1     1     1   110  3.08  3.22  19.4     1     0     3     1
 5 Hornet Sportabout     1     1     1   175  3.15  3.44  17.0     0     0     3     2
 6 Valiant               1     1     1   105  2.76  3.46  20.2     1     0     3     1
 7 Duster 360            1     1     1   245  3.21  3.57  15.8     0     0     3     4
 8 Merc 240D             1     0     1    62  3.69  3.19  20       1     0     4     2
 9 Merc 230              1     0     1    95  3.92  3.15  22.9     1     0     4     2
10 Merc 280              1     1     1   123  3.92  3.44  18.3     1     0     4     4