正则表达式 – 如何在两个人A和B之间的对话中仅提取人A的陈述

我有两个任意人A和B之间的对话记录.

c1 <- "Person A: blabla...something Person B: blabla something else Person A: OK blabla"
c2 <- "Person A: again blabla Person B: blabla something else Person A: thanks blabla"

数据框如下所示：

df <- data.frame(id = rbind(123,345),conversation = rbind(c1,c2))

df

    id                                                                     conversation
c1 123 Person A: blabla...something Person B: blabla something else Person A: OK blabla
c2 345   Person A: again blabla Person B: blabla something else Person A: thanks blabla

现在我想只提取人A的一部分并将其放在数据框中.结果应该是：

id                     person_A
1 123 blabla...something OK blabla
2 345   again blabla thanks blabla

我非常喜欢以一种方式解决这类问题,让您可以访问所有数据(包括Person B的话语).我喜欢tidyr的萃取物用于这种柱分裂.我曾经使用过do.call(rbind,strsplit()))方法但是喜欢提取方法的清洁程度.

c1 <- "Person A: blabla...something Person B: blabla something else Person A: OK blabla"
c2 <- "Person A: again blabla Person B: blabla something else Person A: thanks blabla"
c3 <- "Person A: again blabla Person B: blabla something else"
df <- data.frame(id = rbind(123,345,567),c2,c3))


if (!require("pacman")) install.packages("pacman")
pacman::p_load(dplyr,tidyr)

conv <- strsplit(as.character(df[["conversation"]]),"\\s+(?=Person\\s)",perl=TRUE)

df2 <- df[rep(1:nrow(df),sapply(conv,length)),drop=FALSE]
rownames(df2) <- NULL
df2[["conversation"]] <- unlist(conv)

df2 %>%
    extract(conversation,c("Person","Conversation"),"([^:]+):\\s+(.+)")

##    id   Person          Conversation
## 1 123 Person A    blabla...something
## 2 123 Person B blabla something else
## 3 123 Person A             OK blabla
## 4 345 Person A          again blabla
## 5 345 Person B blabla something else
## 6 345 Person A         thanks blabla
## 7 567 Person A          again blabla
## 8 567 Person B blabla something else


df2 %>%
    extract(conversation,"([^:]+):\\s+(.+)") %>%
    filter(Person == "Person A")    

##    id   Person       Conversation
## 1 123 Person A blabla...something
## 2 123 Person A          OK blabla
## 3 345 Person A       again blabla
## 4 345 Person A      thanks blabla
## 5 567 Person A       again blabla

或者在显示所需的输出时折叠它们：

df2 %>%
    extract(conversation,"([^:]+):\\s+(.+)") %>%
    filter(Person == "Person A") %>%
    group_by(id) %>%
    select(-Person) %>%
    summarise(Person_A =paste(Conversation,collapse=" "))

##    id                     Person_A
## 1 123 blabla...something OK blabla
## 2 345   again blabla thanks blabla
## 3 567                 again blabla

编辑：实际上我怀疑你的数据有真实的名字,如“约翰史密斯”与“人物A”.如果是这种情况,这个初始正则表达式拆分将捕获使用大写后跟冒号的名字和姓氏：

c1 <- "Greg Smith: blabla...something Sue Williams: blabla something else Greg Smith: OK blabla"
c2 <- "Greg Smith: again blabla Sue Williams: blabla something else Greg Smith: thanks blabla"
c3 <- "Greg Smith: again blabla Sue Williams: blabla something else"
df <- data.frame(id = rbind(123,c3))r


conv <- strsplit(as.character(df[["conversation"]]),"\\s+(?=([A-Z][a-z]+\\s+[A-Z][a-z]+:))","([^:]+):\\s+(.+)")

##    id       Person          Conversation
## 1 123   Greg Smith    blabla...something
## 2 123 Sue Williams blabla something else
## 3 123   Greg Smith             OK blabla
## 4 345   Greg Smith          again blabla
## 5 345 Sue Williams blabla something else
## 6 345   Greg Smith         thanks blabla
## 7 567   Greg Smith          again blabla
## 8 567 Sue Williams blabla something else