按“rleid”组折叠行,存在重复值时除外

按“rleid”组折叠行,存在重复值时除外,r,dplyr,R,Dplyr,我在话语中有语音数据,在A_aoi、B_aoi和C_aoi列中有凝视数据。一些语句行是重复的: df <- data.frame( line = c(1,2,3,4,4,4,5,6,6,7,8), speaker = c("b", "a", NA, "c", "c", "c", NA, "c", "c", "a", &quo

我在
话语
中有语音数据,在
A_aoi
B_aoi
C_aoi
列中有凝视数据。一些
语句
行是重复的

df <- data.frame(
  line = c(1,2,3,4,4,4,5,6,6,7,8),
  speaker = c("b", "a", NA, "c", "c", "c", NA, "c", "c", "a", "a"),
  utterance = c("Hey sweetheart!", "Louise!", "(0.234)", "What?", "What?", "What?", "(0.778)", "um::", "um::", "Wake up,", "breakfast's ready"),
  A_aoi = c("B", "B", "C", "B", NA, "C", "C", NA, "C", "C", "C"),
  B_aoi = c("C", "C", "C", "C", "A", "C", NA, NA, "C", "C", NA),
  C_aoi = c("A", NA, NA, "B", NA, "C", "C", "A", "A", "A", "A")
)
但是,这也会折叠重复的
话语
值。预期结果是:

# A tibble: 7 x 6
   line speaker utterance                  A_aoi B_aoi C_aoi
  <dbl> <chr>   <chr>                      <chr> <chr> <chr>
1     1 b       Hey sweetheart!            B     C     A    
2     2 a       Louise!                    B     C     *    
3     3 NA      (0.234)                    C     C     *    
4     4 c       What?                      B*C   CAC   B*C  
5     5 NA      (0.778)                    C     *     C    
6     6 c       um::                       *C    *C    AA   
7     7 a       Wake up, breakfast's ready CC    C*    AA 
#一个tible:7 x 6
线路扬声器发声A_aoi B_aoi C_aoi
嘿,亲爱的!B、C、A
路易丝!B C*
3钠(0.234)碳*
什么?B*C CAC B*C
5Na(0.778)C*C
6 c um::*c*c AA
7 a起床,早餐准备好了CC C*AA
感谢您的帮助

编辑

我有一个逐步解决方案,但如果有人有一个更好、更简单的解决方案,我将非常感激:

# step 1 -- collapse only `aoi` columns:
df_a <- df %>%
  group_by(grp = rleid(speaker)) %>% 
  summarise(across(c(line, speaker), first),  
            A_aoi = str_c(if_else(!is.na(A_aoi), A_aoi, "*" ), collapse = ""), 
            B_aoi = str_c(if_else(!is.na(B_aoi), B_aoi, "*" ), collapse = ""),
            C_aoi = str_c(if_else(!is.na(C_aoi), C_aoi, "*" ), collapse = ""), .groups = 'drop') %>%
  select(- c(grp, line, speaker))

# step 2 -- remove duplicates:
df_b <- df[-which(duplicated(df$line)),]

# step 3 -- collapse `utterance`:
df_c <- df_b %>%
  group_by(grp = rleid(speaker)) %>% 
  summarise(across(c(line, speaker), first), 
            utterance = str_c(utterance, collapse = ' '), .groups = 'drop') %>%
  select(- grp)

# step 4 -- bind:
bind_cols(df_c, df_a)
#步骤1--仅折叠'aoi'列:
df_a%
分组人(grp=rleid(扬声器))%>%
总结(跨越(c(行,发言人),第一个),
A_aoi=str_c(if_else(!is.na(A_aoi),A_aoi,“*”),collapse=“”),
B_aoi=str_c(如果其他(!is.na(B_aoi),B_aoi,“*”),collapse=“”),
C_aoi=str_C(如果_else(!is.na(C_aoi),C_aoi,“*”,collapse=“”),.groups='drop')%>%
选择(-c(玻璃钢、线路、扬声器))
#步骤2--删除重复项:
df_b%
总结(跨越(c(行,发言人),第一个),
话语=str_c(话语,折叠=“”),.groups='drop')%>%
选择(-grp)
#步骤4——绑定:
绑定cols(df_c,df_a)

如何使用
独特(话语)
?这会帮助你实现你想要的吗

df %>%
  group_by(grp = rleid(speaker)) %>% 
  summarise(across(c(line, speaker), first), 
    utterance = str_c(unique(utterance), collapse = ' '), 
    A_aoi = str_c(if_else(!is.na(A_aoi), A_aoi, "*" ), collapse = ""), 
    B_aoi = str_c(if_else(!is.na(B_aoi), B_aoi, "*" ), collapse = ""),
    C_aoi = str_c(if_else(!is.na(C_aoi), C_aoi, "*" ), collapse = ""), .groups = 'drop') %>%
  select(- grp)
输出

# A tibble: 7 x 6
   line speaker utterance                  A_aoi B_aoi C_aoi
  <dbl> <chr>   <chr>                      <chr> <chr> <chr>
1     1 b       Hey sweetheart!            B     C     A    
2     2 a       Louise!                    B     C     *    
3     3 NA      (0.234)                    C     C     *    
4     4 c       What?                      B*C   CAC   B*C  
5     5 NA      (0.778)                    C     *     C    
6     6 c       um::                       *C    *C    AA   
7     7 a       Wake up, breakfast's ready CC    C*    AA
#一个tible:7 x 6
线路扬声器发声A_aoi B_aoi C_aoi
嘿,亲爱的!B、C、A
路易丝!B C*
3钠(0.234)碳*
什么?B*C CAC B*C
5Na(0.778)C*C
6 c um::*c*c AA
7 a起床,早餐准备好了CC C*AA

太棒了,真的!这么简单,但绝对切中要害。也适用于更大、更复杂的数据集!那么thxs!
# A tibble: 7 x 6
   line speaker utterance                  A_aoi B_aoi C_aoi
  <dbl> <chr>   <chr>                      <chr> <chr> <chr>
1     1 b       Hey sweetheart!            B     C     A    
2     2 a       Louise!                    B     C     *    
3     3 NA      (0.234)                    C     C     *    
4     4 c       What?                      B*C   CAC   B*C  
5     5 NA      (0.778)                    C     *     C    
6     6 c       um::                       *C    *C    AA   
7     7 a       Wake up, breakfast's ready CC    C*    AA