Unexpected NA values when using `dplyr::summarize` with grouped data frames in R 4.3
I'm sure I'm missing something obvious here, but I'm trying to compute the mean of a numeric column grouped by a categorical variable using `dplyr::summarize()`, but I'm getting unexpected NA values in the output. I have a data frame `df` with a column `group` and a column `value`. Here’s a snippet of my code: ```r library(dplyr) df <- data.frame( group = c('A', 'A', 'B', 'B', 'C', 'C'), value = c(10, NA, 20, NA, 30, 40) ) result <- df %>% group_by(group) %>% summarize(mean_value = mean(value, na.rm = TRUE)) ``` I expect the result to give me the mean of `value` for each group, ignoring the NA values. However, the output is: ``` # A tibble: 3 × 2 group mean_value <chr> <dbl> 1 A 10 2 B 20 3 C 35 ``` While the mean for group 'A' and 'B' seems correct, I was surprised to see the mean for group 'C' being `35` instead of `30`. I thought that the mean should be calculated as `(30 + 40) / 2`. I’ve verified that there are no additional NA values in the `value` column for group 'C'. Additionally, I also tried using `summarize(mean_value = mean(value))` without `na.rm = TRUE`, and it still resulted in the same output. I’m confused about how `dplyr` is handling the NA values during the calculation. Is there a specific configuration or setting in `dplyr` that might affect this behavior? Any help would be appreciated! My team is using R for this mobile app. Any ideas how to fix this? The project is a mobile app built with R. Cheers for any assistance!