Trouble using `dplyr` to join two data frames with different column types in R 4.3.1
I recently switched to I've looked through the documentation and I'm still confused about I'm trying to merge two data frames using `dplyr::left_join`, but I'm running into issues because the key columns have different data types... The first data frame, `df1`, has the key column `id` as a character type, while the second data frame, `df2`, has the same column as numeric. Here are the structures of both data frames: ```r str(df1) # 'data.frame': 5 obs. of 2 variables: # $ id : chr "1" "2" "3" "4" "5" # $ value1: num 10 20 30 40 50 str(df2) # 'data.frame': 3 obs. of 2 variables: # $ id : num 1 2 3 # $ value2: chr "A" "B" "C" ``` When I run the following code: ```r result <- dplyr::left_join(df1, df2, by = "id") ``` I receive this warning: ``` Warning message: In `mutate()`: Ignoring unknown columns: `id` ``` It seems that `dplyr` is unable to find the matching keys due to the type mismatch. I tried converting `df2$id` to character using `as.character()`, but that didn't help because it still produced an empty data frame in the result. Here's what I've tried: ```r df2$id <- as.character(df2$id) result <- dplyr::left_join(df1, df2, by = "id") ``` The resulting data frame is still empty. How can I resolve this type mismatch scenario to perform the join successfully? Are there better practices for handling joins with different data types in R? This is for a application running on Windows 11. Any ideas how to fix this?