How to choose the most common value in a group related to other group in R?

Question

I have in R the following data frame:

ID = c(rep(1,5),rep(2,3),rep(3,2),rep(4,6));ID
VAR = c("A","A","A","A","B","C","C","D",
             "E","E","F","A","B","F","C","F");VAR
CATEGORY = c("ANE","ANE","ANA","ANB","ANE","BOO","BOA","BOO",
        "CAT","CAT","DOG","ANE","ANE","DOG","FUT","DOG");CATEGORY

DATA = data.frame(ID,VAR,CATEGORY);DATA

That looks like this table below :

ID	VAR	CATEGORY
1	A	ANE
1	A	ANE
1	A	ANA
1	A	ANB
1	B	ANE
2	C	BOO
2	C	BOA
2	D	BOO
3	E	CAT
3	E	CAT
4	F	DOG
4	A	ANE
4	B	ANE
4	F	DOG
4	C	FUT
4	F	DOG

ideal output given the above data frame in R I want to be like that:

ID	TEXTS	category
1	A	ANE
2	C	BOO
3	E	CAT
4	F	DOG

More specifically: I want for ID say 1 to search the most common value in the column VAR which is A and then to search the most common value in the column CATEGORY related to the most common value A which is the ANE and so forth.

How can I do it in R ? Imagine that it is sample example.My real data frame contains 850.000 rows and has 14000 unique ID.

Answer 1

Another dplyr strategy using count and slice:

library(dplyr)
DATA %>% 
    group_by(ID) %>% 
    count(VAR, CATEGORY) %>% 
    slice(which.max(n)) %>% 
    select(-n)

     ID VAR   CATEGORY
  <dbl> <chr> <chr>   
1     1 A     ANE     
2     2 C     BOA     
3     3 E     CAT     
4     4 F     DOG