Handling row-wise operations with `dplyr::rowwise` and unexpected type changes in R 4.3.1
I'm integrating two systems and I've looked through the documentation and I'm still confused about I'm migrating some code and I need some guidance on Hey everyone, I'm running into an issue that's driving me crazy... I've been banging my head against this for hours... I'm trying to perform row-wise operations on a data frame using `dplyr::rowwise()`, but I'm working with unexpected type changes in the output. Specifically, I'm calculating the mean of several columns and I want to retain the original data types of these columns. Here's the code I'm using: ```r library(dplyr) # Sample data frame my_data <- data.frame( id = 1:5, score1 = c(10, 20, NA, 40, 50), score2 = c(5, NA, 15, 20, 25), stringsAsFactors = FALSE ) # Using rowwise to calculate mean result <- my_data %>% rowwise() %>% mutate(mean_score = mean(c(score1, score2), na.rm = TRUE)) print(result) ``` In the output, I noticed that the `mean_score` column is of type numeric, which is expected. However, when I check the types of the original columns and the new column after the operation, I find that `score1` and `score2` have been converted to numeric types instead of remaining character vectors as they were initially. Additionally, when I try to run further operations that depend on these columns being characters, I get the behavior: ``` behavior in some_function(): argument is not of length 1 ``` I've also tried using `mutate(across(...))` instead of `rowwise`, but it doesn't seem to solve the scenario. How can I ensure that the original column types remain unchanged while still performing row-wise calculations? I'm using R version 4.3.1 and `dplyr` version 1.1.0. Any insights would be greatly appreciated! For context: I'm using R on macOS. For context: I'm using R on macOS. Am I missing something obvious? This is part of a larger web app I'm building. How would you solve this? I appreciate any insights! Any ideas what could be causing this? I'm coming from a different tech stack and learning R. My team is using R for this desktop app. Is there a simpler solution I'm overlooking?