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")
The error is now there again in a different guise when the values_ptypes
argument is used.
library(tidyverse)
small_diamonds <- diamonds %>%
select(cut, color, price) %>%
mutate(row_num = row_number())
small_diamonds %>%
pivot_longer( - row_num,
names_to = "key",
values_to = "val",
values_ptypes = list(val = 'character'))
#> Error: Can't convert <integer> to <character>.
Therefore I need to use the values_transform
argument to get the desired result.
library(tidyverse)
small_diamonds <- diamonds %>%
select(cut, color, price) %>%
mutate(row_num = row_number())
small_diamonds %>%
pivot_longer( - row_num,
names_to = "key",
values_to = "val",
values_transform = list(val = as.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
Created on 2020-08-25 by the reprex package (v0.3.0)
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
Using your example, you can see with str() that you have two vectors encoded as factors, and two as integers. pivot_longer demands that all vectors are of the same type, and throws the error you have reported.
library(tidyverse)
small_diamonds <- diamonds %>%
select(cut, color, price) %>%
mutate(row_num = row_number())
str(small_diamonds)
One solution is to convert all vector to characters with mutate.if, and then pass the pivot_longer command.
small_diamonds %>%
mutate_if(is.numeric,as.character, is.factor, as.character) %>%
pivot_longer( - row_num,
names_to = "key",
values_to = "val")
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With