regex - How to extract only person A's statements in a conversation between two persons A and B -

i have record of conversations between 2 arbitrary persons , b.

c1 <- "person a: blabla...something person b: blabla else person a: ok blabla" c2 <- "person a: again blabla person b: blabla else person a: blabla" 

the data frame looks this:

df <- data.frame(id = rbind(123, 345), conversation = rbind(c1, c2))  df      id                                                                     conversation c1 123 person a: blabla...something person b: blabla else person a: ok blabla c2 345   person a: again blabla person b: blabla else person a: blabla 

now extract part of person , put in data frame. result should be:

   id                     person_a 1 123 blabla...something ok blabla 2 345   again blabla blabla 

i'm big fan of solving sort of problem in way gives access data (that includes person b's discourse well). love tidyr's extract sort of column splitting. used use do.call(rbind, strsplit())) approach love how clean extract approach is.

c1 <- "person a: blabla...something person b: blabla else person a: ok blabla" c2 <- "person a: again blabla person b: blabla else person a: blabla" c3 <- "person a: again blabla person b: blabla else" df <- data.frame(id = rbind(123, 345, 567), conversation = rbind(c1, 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    blabla...something ## 2 123 person b blabla else ## 3 123 person             ok blabla ## 4 345 person          again blabla ## 5 345 person b blabla else ## 6 345 person         blabla ## 7 567 person          again blabla ## 8 567 person b blabla else   df2 %>%     extract(conversation, c("person", "conversation"), "([^:]+):\\s+(.+)") %>%     filter(person == "person a")      ##    id   person       conversation ## 1 123 person blabla...something ## 2 123 person          ok blabla ## 3 345 person       again blabla ## 4 345 person      blabla ## 5 567 person       again blabla 

or collapse them show in desired output:

df2 %>%     extract(conversation, c("person", "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 blabla ## 3 567                 again blabla 

edit: in reality suspect data has real names "john smith" vs. "person a". if case initial regex split capture first , last name uses caps followed colon:

c1 <- "greg smith: blabla...something sue williams: blabla else greg smith: ok blabla" c2 <- "greg smith: again blabla sue williams: blabla else greg smith: blabla" c3 <- "greg smith: again blabla sue williams: blabla else" df <- data.frame(id = rbind(123, 345, 567), conversation = rbind(c1, c2, c3))r   conv <- strsplit(as.character(df[["conversation"]]), "\\s+(?=([a-z][a-z]+\\s+[a-z][a-z]+:))", 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   greg smith    blabla...something ## 2 123 sue williams blabla else ## 3 123   greg smith             ok blabla ## 4 345   greg smith          again blabla ## 5 345 sue williams blabla else ## 6 345   greg smith         blabla ## 7 567   greg smith          again blabla ## 8 567 sue williams blabla else