如何只删除连续的重复行？

Question

我只需要删除我的数据框中的所有重复项，当它们连续出现时。我尝试过distinct()函数，但它会删除所有重复项-因此我需要一个不同的代码，以便仅当重复项连续且仅针对特定列时才有机会进行自定义和删除。

以下是我的数据示例：

 Subject  Trial Event_type  Code   Time 
    
23  VP02_RP 15  Picture face01_n    887969

24  VP02_RP 15  Sound   mpossound_test5 888260

25  VP02_RP 15  Picture pospic_test5    906623

26  VP02_RP 15  Nothing ev_mnegpos_adj_onset    928623

27  VP02_RP 15  Response    15  958962

28  VP02_RP 18  Picture face01_p    987666

29  VP02_RP 18  Sound   mpossound_test6 987668

30  VP02_RP 18  Picture negpic_test6    1006031

31  VP02_RP 18  Nothing ev_mposnegpos_adj_onset 1028031

32  VP02_RP 18  Response    15  1076642

33  VP02_RP 19  Response    13  1680887

正如您在第32和33行中看到的，我有两个连续的响应，我只想保留第一个。所以我想删除Event_type列上所有重复的连续行。

我该怎么做呢？

Answer 1

您可以使用data.table中的rleid函数，它将为每个连续的事件值提供一个唯一的数字，然后使用duplicated只保留第一个值。

res <- df[!duplicated(data.table::rleid(df$Event_type)), ]
res

#   Subject Trial Event_type                    Code    Time
#23 VP02_RP    15    Picture                face01_n  887969
#24 VP02_RP    15      Sound         mpossound_test5  888260
#25 VP02_RP    15    Picture            pospic_test5  906623
#26 VP02_RP    15    Nothing    ev_mnegpos_adj_onset  928623
#27 VP02_RP    15   Response                      15  958962
#28 VP02_RP    18    Picture                face01_p  987666
#29 VP02_RP    18      Sound         mpossound_test6  987668
#30 VP02_RP    18    Picture            negpic_test6 1006031
#31 VP02_RP    18    Nothing ev_mposnegpos_adj_onset 1028031
#32 VP02_RP    18   Response                      15 1076642

base R中的rleid函数可以用rle -

res <- df[!duplicated(with(rle(df$Event_type),rep(seq_along(values), lengths))),]
res

Answer 2

一个潜在的tidyverse解决方案：

library(tidyverse)

df1 <- data.frame(
  stringsAsFactors = FALSE,
         row.names = c("23","24","25","26","27",
                       "28","29","30","31","32","33"),
           Subject = c("VP02_RP","VP02_RP","VP02_RP",
                       "VP02_RP","VP02_RP","VP02_RP","VP02_RP","VP02_RP",
                       "VP02_RP","VP02_RP","VP02_RP"),
             Trial = c(15L, 15L, 15L, 15L, 15L, 18L, 18L, 18L, 18L, 18L, 19L),
        Event_type = c("Picture","Sound","Picture",
                       "Nothing","Response","Picture","Sound","Picture",
                       "Nothing","Response","Response"),
              Code = c("face01_n","mpossound_test5",
                       "pospic_test5","ev_mnegpos_adj_onset","15","face01_p",
                       "mpossound_test6","negpic_test6",
                       "ev_mposnegpos_adj_onset","15","13"),
              Time = c(887969L,888260L,906623L,
                       928623L,958962L,987666L,987668L,1006031L,1028031L,
                       1076642L,1680887L)
)

df1 %>%
  filter(Event_type != lag(Event_type, 1))
#>    Subject Trial Event_type                    Code    Time
#> 24 VP02_RP    15      Sound         mpossound_test5  888260
#> 25 VP02_RP    15    Picture            pospic_test5  906623
#> 26 VP02_RP    15    Nothing    ev_mnegpos_adj_onset  928623
#> 27 VP02_RP    15   Response                      15  958962
#> 28 VP02_RP    18    Picture                face01_p  987666
#> 29 VP02_RP    18      Sound         mpossound_test6  987668
#> 30 VP02_RP    18    Picture            negpic_test6 1006031
#> 31 VP02_RP    18    Nothing ev_mposnegpos_adj_onset 1028031
#> 32 VP02_RP    18   Response                      15 1076642

Answer 3

data.table的一个选项

library(data.table)
setDT(df1)[Event_type != shift(Event_type)]