R data.table 在组之间有条件地删除行

Question

I have this example dataset and the actual has millions of rows, so I'd appreciate a data.table solution but also a tidyverse solution would be fine:

dat1 = data.frame(name = c("X1", "X1", "X1", "X2", "X2", "X2", "X2", "X2", "X2"), 
              year = c(2015,2016,2017,2015,2016,2016,2017,2017, 2018),
              choice = c("o","o","o","o","o","r","r","o","o")
)
dat1

The logic I need to apply is:

If for any name and year combination only choice "o" exists, retain the row with "o" .

If for any name and year combination choices "o" and "r" exist, retain row with "r" and drop row with "o" . I don't want to name name and year combinations.

Answer 1

Does this work:

library(dplyr)
dat1 %>% group_by(name ,year) %>% filter(all(choice == 'o' )|choice == 'r')
# A tibble: 7 x 3
# Groups:   name, year [7]
  name   year choice
  <chr> <dbl> <chr> 
1 X1     2015 o     
2 X1     2016 o     
3 X1     2017 o     
4 X2     2015 o     
5 X2     2016 r     
6 X2     2017 r     
7 X2     2018 o     

Answer 2

library(data.table)
setDT(dat1)
dat1[, .SD[all(choice == "o") | choice == "r",], by = .(name, year)]
#    name year choice
# 1:   X1 2015      o
# 2:   X1 2016      o
# 3:   X1 2017      o
# 4:   X2 2015      o
# 5:   X2 2016      r
# 6:   X2 2017      r
# 7:   X2 2018      o

(I generated this before looking at KarthikS's answer, but the logic and the results are identical.)

Answer 3

An option is also to convert the column to factor with levels specified in the custom order and then select the first levels after dropping the levels with droplevels

library(dplyr)
dat1 %>%
     group_by(name, year) %>%
     filter(choice %in% levels(droplevels(factor(choice, 
           levels = c('r', 'o'))))[1])
# A tibble: 7 x 3
# Groups:   name, year [7]
#  name   year choice
#  <chr> <dbl> <chr> 
#1 X1     2015 o     
#2 X1     2016 o     
#3 X1     2017 o     
#4 X2     2015 o     
#5 X2     2016 r     
#6 X2     2017 r     
#7 X2     2018 o     

---

An equivalent option with data.table is

library(data.table)
setDT(dat1)[dat1[, .I[choice %in% 
       levels(droplevels(factor(choice, 
           levels = c('r', 'o'))))[1]], .(name, year)]$V1]