Using select_if with variable name and type conditions

user_6822361 0
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There are plenty of posts on using dplyr's select_if for multiple conditions. However, in whatever way, selecting for both is.factor and variable names has not worked for me so far.

Ultimately, I would like to select all factors in a df/tibble and exclude certain variables by name.

Example:

df <- tibble(A = factor(c(0,1,0,1)), 
             B = factor(c("Yes","No","Yes","No")), 
             C = c(1,2,3,4))

Various attempts:

Attempt 1

df %>%
  select_if(function(col) is.factor(col) & !str_detect(names(col), "A"))

Error in selected[[i]] <- .p(.tbl[[tibble_vars[[i]]]], ...) : replacement has length zero

Attempt 2

df %>%
      select_if(function(col) is.factor(col) & negate(str_detect(names(col)), "A"))

Error: Can't convert a logical vector to function Call `rlang::last_error()` to see a backtrace

Attempt 3

df %>%
  select_if(function(col) is.factor(col) && !str_detect(names(col), "A"))

Error: Only strings can be converted to symbols Call `rlang::last_error()` to see a backtrace

Attempt 4

df %>%
  select_if(is.factor(.) && !str_detect(names(.), "A"))

Error in tbl_if_vars(.tbl, .predicate, caller_env(), .include_group_vars = TRUE) : length(.p) == length(tibble_vars) is not TRUE

In the meanwhile, individual conditions have no problem working:

> df %>%
+     select_if(is.factor)
# A tibble: 4 x 2
  A     B    
  <fct> <fct>
1 0     Yes  
2 1     No   
3 0     Yes  
4 1     No   

> df %>%
+     select_if(!str_detect(names(.), "A"))
# A tibble: 4 x 2
  B         c
  <fct> <dbl>
1 Yes       1
2 No        2
3 Yes       3
4 No        4

The problem probably lies here:

df %>%
  select_if(function(col) !str_detect(names(col), "A"))

Error in selected[[i]] <- .p(.tbl[[tibble_vars[[i]]]], ...) : replacement has length zero

However, I have little clue how to fix this.

dplyr r
2 Answers

Perhaps I'm missing something, but is there any reason you couldn't do the following: 

df <- tibble(A = factor(c(0,1,0,1)), 
         B = factor(c("Yes","No","Yes","No")), 
         C = c(1,2,3,4))


df %>% select_if(function(col) is.factor(col)) %>% select_if(!str_detect(names(.), "A"))

# A tibble: 4 x 1
B    
<fct>
1 Yes  
2 No   
3 Yes  
4 No
user_82064340

Just for completeness, not sure if it is acceptable for you, but base R may save you some pain here (a first, very quick shot):

df[, sapply(names(df), 
  function(coln, df) !grepl("A", coln) && is.factor(df[[coln]]), df = df),
  drop = FALSE]
user_88766520
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