How to create a new row using aggregation of two or more rows?

I'm running on RStudio. So, I run a pretty big database, and run a code to get a new dataframe (Results_Final_Status) based on the columns that I want.

Results_Final_Status = Results_Final %>% 
  group_by(status) %>%
  dplyr::summarise(total=n()) %>%
  arrange(-total)`

status	total
Finished	7083
+1 Lap	3850
Engine	2011
+2 Laps	1593
Accident	1044

So my objective is to create a new dataframe, and aggregate "+1 Lap" and "+2 Lap" creating a new value "OTHER" and the total SUM of this two values is added in the total column.

I've tried the mutate function and the case_when function, but something is missing and I keep having errors on RStudio. I'm expecting a new dataframe, with this values somewhat aggregated in order to create a new table, so my visualization is easier to observe (otherwise I would have like 100 rows with different values and a lot of "total" values).

Solution

Perhaps a brute force method but you can append rows to your current dataframe:

library(tidyverse)

Results_final <- tibble(status=c('Finished','+1 Lap','Engine', '+2 Laps','Accident'),
                        total=c(7083,3850,2011,1593,1044)
                        )

Results_final_status <- Results_final %>% 
  add_row(.data = data.frame(status='Other',
                             total=sum(Results_final$total[Results_final$status=='+1 Lap'|
                                                             Results_final$status=='+2 Laps'])))

Results_final_status