How to interpret dplyr message `summarise()` regrouping output by "x" (override with `.groups` argument)?

How to Interpret the summarise() Regrouping Output in dplyr

So, you're running some code in R using the dplyr package, and you encounter a message that says summarise() regrouping output by 'x' (override with .groups argument). What does it mean? Why does it report regrouping only by 'x' when you grouped by other variables as well? And what exactly does it mean to override it? Don't worry, we've got you covered! 🤓

The Context

Let's start by understanding the context around this message. The message appears when using a newer version of dplyr (development version 0.8.99.9003). Here's an example to help recreate the output and give you a clear picture:

library(tidyverse)
library(hablar)

df <- read_csv("year, week, rat_house_females, rat_house_males, mouse_wild_females, mouse_wild_males 
               2018,10,1,1,1,1
               2018,10,1,1,1,1
               2018,11,2,2,2,2
               2018,11,2,2,2,2
               2019,10,3,3,3,3
               2019,10,3,3,3,3
               2019,11,4,4,4,4
               2019,11,4,4,4,4") %>% 
  convert(chr(year,week)) %>% 
  mutate(total_rodents = rowSums(select_if(., is.numeric))) %>% 
  convert(num(year,week)) %>% 
  group_by(year,week) %>% summarise(average = mean(total_rodents))

The resulting tibble is correct, but the message shows up:

summarise() regrouping output by 'year' (override with `.groups` argument)

Interpreting the Message

Let's break down the different parts of this message and understand their meanings.

1. summarise()

This message specifically refers to the summarise() function from dplyr. It tells us that the following information is related to this particular function.

2. regrouping output by 'x'

The message informs us about the variables used for grouping the data, which in this case is 'year'. It tells us that the output has been regrouped based on this variable.

3. (override with .groups argument)

The message suggests that we can override this default behavior using the .groups argument. By default, dplyr groups the output tables, but we have the flexibility to change this behavior if needed. We'll explore this further in the next section.

Overriding the Regrouping

Now that we understand the message, let's talk about overriding the regrouping behavior. The idea behind regrouping is to provide consistent grouping information to downstream operations and avoid ambiguity in the output. However, there might be cases where you want to change this behavior. Here's how you can do it:

df <- df %>% ungroup() %>% summarise(year, week, average, .groups = "drop")

In this code snippet, we use the ungroup() function to remove the default grouping. Then, we explicitly specify the variables we want to keep in the resulting tibble by mentioning them in the summarise() function. Finally, we set .groups = "drop" to drop the information about the overridden grouping.

Conclusion

So there you have it! You can now interpret the summarise() regrouping output in dplyr with confidence. It's important to understand the message and its context, as well as how to override the regrouping if necessary. Remember, the message is there to provide you with useful information and help ensure the integrity of your data analysis.

If you still have any questions or need further assistance, feel free to leave a comment below. Happy coding! 😄