Unexpected NA values when using `datatable` with grouped summary in R
I tried several approaches but none seem to work. I tried several approaches but none seem to work. After trying multiple solutions online, I still can't figure this out. I'm working with the `data.table` package in R (version 1.14.0) to perform a grouped summary on a large dataset, but I'm getting unexpected NA values in my output. I've created a `data.table` from a CSV file and attempted to compute the mean of a numeric column while grouping by a factor column. Here's a snippet of my code: ```r library(data.table) # Load the data my_data <- fread('my_data.csv') # Check the structure of the data to ensure everything is in the right format str(my_data) # Attempt to compute the mean while grouping result <- my_data[, .(mean_value = mean(numeric_column, na.rm = TRUE)), by = group_column] ``` After running this, I noticed that `result` seems to be returning NA for some groups where I expect valid mean values. I checked for NA values in `numeric_column`, and they are indeed present, but I have specified `na.rm = TRUE`. The `group_column` should have no NAs as well, yet I'm still getting NAs in the resulting `data.table`. I also tried using `na.omit()` on the subset before computing the mean, like this: ```r result <- my_data[!is.na(numeric_column), .(mean_value = mean(numeric_column)), by = group_column] ``` This didn't resolve the scenario either. Additionally, I've ensured that `group_column` is a factor and that `numeric_column` is numeric using `setDT(my_data)` to avoid any data frame issues. Can anyone guide to understand why I'm working with these NA values in my grouped summary? Is there a better way to handle this situation with `data.table`? Any insights or best practices would be greatly appreciated! My development environment is Windows. This is part of a larger web app I'm building. Has anyone else encountered this? Thanks for any help you can provide!