advanced patterns with `rbind()` when combining data frames with differing column types in R
I've encountered a strange issue with I'm a bit lost with I'm sure I'm missing something obvious here, but I am trying to combine two data frames using `rbind()`, but I'm running into a question due to the column types being different..... For example, I have two data frames: `df1` has a character column for `id`, while `df2` has that same column as an integer. Here are the snippets: ```r # First data frame id <- c("1", "2", "3") value <- c(10, 20, 30) df1 <- data.frame(id, value) # Second data frame id <- c(1, 2, 3) value <- c(40, 50, 60) df2 <- data.frame(id, value) ``` When I run the following code to combine them: ```r combined_df <- rbind(df1, df2) ``` I receive the warning: ``` Warning message: In rbind(deparse(substitute(x)), deparse(substitute(y)), ...) : number of columns of matrices must match (see arg 2) ``` I've tried converting the `id` column in `df2` to character before performing `rbind()`, but it still doesn’t work as expected: ```r df2$id <- as.character(df2$id) combined_df <- rbind(df1, df2) ``` After running this, I still get a different structure than I anticipated, and the values in the `value` column seem to get coerced into factors instead of staying as numeric. How can I properly combine these two data frames while preserving the data types? Is there a best practice or a function in the `dplyr` package that could guide to avoid these issues? I'm using R version 4.1.1 and the `dplyr` version is 1.0.7. Thanks for any help you can provide! I'm working with R in a Docker container on Windows 10. How would you solve this? I recently upgraded to R latest. Any advice would be much appreciated. Any ideas how to fix this?