Rank_MultipleRows_by_Groups.R

data <- structure(list(CODE = c("AA","AA","AA","AA","AA"),  
                       DATE = c(20181205,20181205,20181205,20181212,20181212), 
                       TIME = c(14.0,14.0,14.2,18.0,18.0), 
                       NO = c("D1","D1","D2","D3","D3"), 
                       ITEM = c("AK011","ZH002","HJ005","AK011","KK021"),
                       RANK = c(1,1,2,3,3)),
                  .Names = c("CODE", "DATE", "TIME", "NO", "ITEM","RANK"), 
                  class = c("tbl_df", "tbl", "data.frame"), 
                  row.names = c(NA, -5L))

library(dplyr)

data_unique = data[!duplicated(data[c("CODE","DATE", "TIME", "NO")]),]
# # A tibble: 3 x 6
# CODE      DATE  TIME NO    ITEM   RANK
# <chr>    <dbl> <dbl> <chr> <chr> <dbl>
#   1 AA    20181205  14   D1    AK011     1
# 2 AA    20181205  14.2 D2    HJ005     2
# 3 AA    20181212  18   D3    AK011     3

data_unique = data_unique %>% mutate(RANK_dplyr = 1:n())
# A tibble: 3 x 7
# CODE      DATE  TIME NO    ITEM   RANK RANK_dplyr
# <chr>    <dbl> <dbl> <chr> <chr> <dbl>      <int>
#   1 AA    20181205  14   D1    AK011     1          1
# 2 AA    20181205  14.2 D2    HJ005     2          2
# 3 AA    20181212  18   D3    AK011     3          3

data %>% 
  inner_join(data_unique, by = c("CODE","DATE", "TIME", "NO"))
# A tibble: 5 x 9
# CODE      DATE  TIME NO    ITEM.x RANK.x ITEM.y RANK.y RANK_dplyr
# <chr>    <dbl> <dbl> <chr> <chr>   <dbl> <chr>   <dbl>      <int>
#   1 AA    20181205  14   D1    AK011       1 AK011       1          1
# 2 AA    20181205  14   D1    ZH002       1 AK011       1          1
# 3 AA    20181205  14.2 D2    HJ005       2 HJ005       2          2
# 4 AA    20181212  18   D3    AK011       3 AK011       3          3
# 5 AA    20181212  18   D3    KK021       3 AK011       3          3

# -----------------------------------
# or even a simpler solution
# one-liner
# -----------------------------------
data %>% group_indices(CODE, DATE, TIME, NO) 
# [1] 1 1 2 3 3