r - pivot_longer with multiple classes causes error ("No common type")

Question

I am running pivot_longer on multiple columns (i.e. two character columns and one numeric). I am encountering an error related to the class mismatch.

I have investigated the documentation for any "force" options and did not see any arguments within pivot_longer to specify the class to use -- or to allow the function auto-detect the most general class.

Are there any parameters within pivot_longer to avoid this error? Or do you need to convert the columns to a single class before running pivot_longer?

library(dplyr)
library(tidyr)
library(ggplot2) # Just for `diamonds` dataset

small_diamonds <- diamonds %>% 
  # Select a few columns (two character, one numeric, specifically integers)
  select(cut, color, price) %>% 
  # Create a row_id
  mutate(row_num = row_number()) 

# This works with `gather`
small_diamonds %>% 
  gather(key, val, - row_num)

# This fails due to class error:
small_diamonds %>% 
  # Pivot data
  pivot_longer( - row_num, 
                names_to = "key",
                values_to = "val")

# Output
# Error: No common type for `cut` <ordered<4bd7e>> and `price` <integer>.
# Call `rlang::last_error()` to see a backtrace

# Convert columns to a single class (character) and then use `pivot_longer`. 
# Runs successfully
small_diamonds %>% 
  mutate_all(as.character) %>% 
  # Pivot data
  pivot_longer( - row_num, 
                names_to = "key",
                values_to = "val")

Answer 1

We can specify the values_ptype in this case (as the value columns differ in types)

library(ggplot2)
library(tidyr)
library(dplyr)
small_diamonds %>%  
   pivot_longer( - row_num, 
             names_to = "key",
             values_to = "val", values_ptypes = list(val = 'character'))
# A tibble: 161,820 x 3
#   row_num key   val    
#     <int> <chr> <chr>  
# 1       1 cut   Ideal  
# 2       1 color E      
# 3       1 price 326    
# 4       2 cut   Premium
# 5       2 color E      
# 6       2 price 326    
# 7       3 cut   Good   
# 8       3 color E      
# 9       3 price 327    
#10       4 cut   Premium
# … with 161,810 more rows