Difficulty merging data frames with differing factors and handling NAs in R
I've been struggling with this for a few days now and could really use some help. I'm encountering a problem while trying to merge two data frames in R that have different factor levels and some NA values. I'm using the `merge()` function, but the resulting data frame doesn't seem to retain all the data I expect. Here's a simplified version of my code: ```r # Define two data frames with different factor levels library(dplyr) df1 <- data.frame(id = 1:5, category = factor(c('A', 'B', 'C', 'A', NA))) df2 <- data.frame(id = c(1, 2, 6), category = factor(c('A', 'B', 'D'))) # Attempting to merge them merged_df <- merge(df1, df2, by = 'id', all = TRUE) ``` When I run this, I get the following output: ```r > merged_df id category.x category.y 1 1 A A 2 2 B B 3 3 C <NA> 4 4 A <NA> 5 5 <NA> <NA> 6 6 <NA> D ``` I notice that the factor levels in `category.x` and `category.y` seem to be mismatched. When I check the levels using `levels(merged_df$category.x)` and `levels(merged_df$category.y)`, I see: ```r > levels(merged_df$category.x) [1] "A" "B" "C" > levels(merged_df$category.y) [1] "A" "B" "D" ``` The problem arises when I try to handle the NAs; I want to fill them with a default category, say 'Unknown'. However, using `mutate()` to fill NAs isn't working as expected: ```r merged_df <- merged_df %>% mutate(category.x = replace_na(category.x, 'Unknown'), category.y = replace_na(category.y, 'Unknown')) ``` After applying this, I find that the `category.x` column still retains the factor levels from before and doesn't seem to accept 'Unknown'. How can I properly merge these two data frames while ensuring that my factor levels are consistent and that NAs can be filled appropriately? Any suggestions would be greatly appreciated! Iām using R version 4.1.0 and dplyr version 1.0.7. Any help would be greatly appreciated!