I’m having trouble grasping the purpose of .group = "drop" in dplyr’s summarise function. I’m attempting to execute the following code to display the top 20 stations along with their respective latitude and longitude:

summary <- trips_2023 %>% 
    filter(member_casual == "member") %>%
    group_by(start_station_name, start_lat, start_lng) %>%
    summarise(count = n()) %>%
    arrange(desc(count)) %>%
    mutate(type = "start",
           member = "member") %>% 
    slice(1:20) 

However, the code returns a table with many more rows than the requested 20.
If I add .groups = "drop" after summarise, then the code works, but honestly, I haven’t understood why.

summary <- trips_2023 %>% 
    filter(member_casual == "member") %>%
    group_by(start_station_name, start_lat, start_lng) %>%
    summarise(count = n(), .groups = "drop") %>%
    arrange(desc(count)) %>%
    mutate(type = "start",
           member = "member") %>% 
    slice(1:20) 

‘.groups = “drop”‘ supposedly instructs dplyr to remove group information after performing grouping and summarising operations.
However, the definition is not clear to me. I have also read the official documentation, but it’s not very understandable.
Can someone help me understand better with a practical example?