scenarios when trying to use dplyr with grouped data in R - advanced patterns
I'm working with an scenario while using the `dplyr` package to manipulate grouped data in R. I'm trying to calculate the mean of a variable within each group, but I keep getting an behavior that says `behavior in summarise(): ! question with summarise() input ..1. x must be a vector, not a data frame.` Here's a minimal reproducible example of my code: ```R library(dplyr) # Sample data frame df <- data.frame( group = c('A', 'A', 'B', 'B'), value = c(10, 20, 30, 40) ) # Attempting to group by 'group' and summarize result <- df %>% group_by(group) %>% summarise(mean_value = mean(value)) ``` Despite this code seeming correct, I'm receiving the aforementioned behavior message. I have checked that `dplyr` is properly installed and that I'm using version 1.0.7. I have also verified that there are no missing values in the 'value' column. I've tried using `ungroup()` before `summarise()`, but that doesn't resolve the scenario. Moreover, I've attempted casting `value` to a vector explicitly using `as.vector(value)` before calling `mean()`, which did not work either. What could be causing this behavior? Is there something I might be overlooking regarding how `dplyr` handles grouped data? Any insights would be greatly appreciated.