我有一个类似的数据帧，只是更长：
# A tibble: 6 x 9
`First name` `Last name` Username TwitterID Party Chamber Country `Legislative per… Notes
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 Raynell Andreychuk SenAndrey… 902575098 "Conservative Party of Canada (2… Senate Canada 1993/03/11 - 201… NA
2 Salma Ataullahjan SenatorSa… 498059173 "Conservative Party of Canada (2… Senate Canada 2010/07/09 - NA
3 Michèle Audette michele_a… 948136886 "Independent Senators Group (202… Senate Canada 2021/07/29 - NA
4 Denise Batters denisebat… 2422634642 "Conservative Party of Canada (2… Senate Canada 2013/01/25 - NA
5 Diane Bellemare sendbelle… 1426402920 ""Canadian Senators Group (2019… Senate Canada 2012/09/06 - NA
6 Wanda Thomas Bernard SenatorWa… 83161013426… "Progressive Senate Group (2020/… Senate Canada 2016/11/10 - NA
我的目标是，每当政治家活跃在一个新的政党中时，就把每一排划分成一排。我试过用ifelse()碰碰运气，但没有成功。我非常感谢能得到的任何帮助！
再现性：
structure(list(`First name` = c("Raynell", "Salma", "Michèle",
"Denise", "Diane", "Wanda Thomas"), `Last name` = c("Andreychuk",
"Ataullahjan", "Audette", "Batters", "Bellemare", "Bernard"),
Username = c("SenAndreychuk", "SenatorSalma", "michele_audette",
"denisebatters", "sendbellemare", "SenatorWanda"), TwitterID = c("902575098",
"498059173", "948136886", "2422634642", "1426402920", "831610134262665216"
), Party = c("Conservative Party of Canada (2004/02/02 - 2019/08/13)rrnProgressive Conservative Party (1993/03/11 - 2004/02/01)",
"Conservative Party of Canada (2010/07/09 - )", "Independent Senators Group (2021/09/27 - )rrnNon-affiliated (2021/07/29 - 2021/09/26)",
"Conservative Party of Canada (2013/01/25 - )", ""Canadian Senators Group (2019/11/04 - )rnIndependent Senators Group (2018/02/28 - 2019/11/03)rnNon-affiliated (2018/02/15 - 2018/02/27)"",
"Progressive Senate Group (2020/07/08 - )rrnIndependent Senators Group (2017/06/01 - 2020/07/07)rrnNon-affiliated (Independent Senators Group) (2017/03/30 - 2017/05/31)rrnNon-affiliated (2016/11/10 - 2017/03/29)"
), Chamber = c("Senate", "Senate", "Senate", "Senate", "Senate",
"Senate"), Country = c("Canada", "Canada", "Canada", "Canada",
"Canada", "Canada"), `Legislative period` = c("1993/03/11 - 2019/08/13",
"2010/07/09 -", "2021/07/29 -", "2013/01/25 -", "2012/09/06 -",
"2016/11/10 -"), Notes = c("NA", "NA", "NA", "NA", "NA",
"NA")), row.names = c(NA, -6L), class = c("tbl_df", "tbl",
"data.frame"))
您应该尝试tidyr::separate_rows(Party, sep = "[rn]"):
library(tidyverse)
data <-
structure(list(
`First name` = c(
"Raynell", "Salma", "Michèle",
"Denise", "Diane", "Wanda Thomas"
), `Last name` = c(
"Andreychuk",
"Ataullahjan", "Audette", "Batters", "Bellemare", "Bernard"
),
Username = c(
"SenAndreychuk", "SenatorSalma", "michele_audette",
"denisebatters", "sendbellemare", "SenatorWanda"
), TwitterID = c(
"902575098",
"498059173", "948136886", "2422634642", "1426402920", "831610134262665216"
), Party = c(
"Conservative Party of Canada (2004/02/02 - 2019/08/13)rrnProgressive Conservative Party (1993/03/11 - 2004/02/01)",
"Conservative Party of Canada (2010/07/09 - )", "Independent Senators Group (2021/09/27 - )rrnNon-affiliated (2021/07/29 - 2021/09/26)",
"Conservative Party of Canada (2013/01/25 - )", ""Canadian Senators Group (2019/11/04 - )rnIndependent Senators Group (2018/02/28 - 2019/11/03)rnNon-affiliated (2018/02/15 - 2018/02/27)"",
"Progressive Senate Group (2020/07/08 - )rrnIndependent Senators Group (2017/06/01 - 2020/07/07)rrnNon-affiliated (Independent Senators Group) (2017/03/30 - 2017/05/31)rrnNon-affiliated (2016/11/10 - 2017/03/29)"
), Chamber = c(
"Senate", "Senate", "Senate", "Senate", "Senate",
"Senate"
), Country = c(
"Canada", "Canada", "Canada", "Canada",
"Canada", "Canada"
), `Legislative period` = c(
"1993/03/11 - 2019/08/13",
"2010/07/09 -", "2021/07/29 -", "2013/01/25 -", "2012/09/06 -",
"2016/11/10 -"
), Notes = c(
"NA", "NA", "NA", "NA", "NA",
"NA"
)
), row.names = c(NA, -6L), class = c(
"tbl_df", "tbl",
"data.frame"
))
data
#> # A tibble: 6 x 9
#> `First name` `Last name` Username TwitterID Party Chamber Country
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Raynell Andreychuk SenAndrey… 902575098 "Conservative … Senate Canada
#> 2 Salma Ataullahjan SenatorSa… 498059173 "Conservative … Senate Canada
#> 3 Michèle Audette michele_a… 948136886 "Independent S… Senate Canada
#> 4 Denise Batters denisebat… 2422634642 "Conservative … Senate Canada
#> 5 Diane Bellemare sendbelle… 1426402920 ""Canadian Se… Senate Canada
#> 6 Wanda Thomas Bernard SenatorWa… 831610134… "Progressive S… Senate Canada
#> # … with 2 more variables: Legislative period <chr>, Notes <chr>
data %>%
separate_rows(Party, sep = "[rn]") %>%
filter(Party != "")
#> # A tibble: 13 x 9
#> `First name` `Last name` Username TwitterID Party Chamber Country
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Raynell Andreychuk SenAndrey… 902575098 "Conservative… Senate Canada
#> 2 Raynell Andreychuk SenAndrey… 902575098 "Progressive … Senate Canada
#> 3 Salma Ataullahjan SenatorSa… 498059173 "Conservative… Senate Canada
#> 4 Michèle Audette michele_a… 948136886 "Independent … Senate Canada
#> 5 Michèle Audette michele_a… 948136886 "Non-affiliat… Senate Canada
#> 6 Denise Batters denisebat… 2422634642 "Conservative… Senate Canada
#> 7 Diane Bellemare sendbelle… 1426402920 ""Canadian S… Senate Canada
#> 8 Diane Bellemare sendbelle… 1426402920 "Independent … Senate Canada
#> 9 Diane Bellemare sendbelle… 1426402920 "Non-affiliat… Senate Canada
#> 10 Wanda Thomas Bernard SenatorWa… 831610134… "Progressive … Senate Canada
#> 11 Wanda Thomas Bernard SenatorWa… 831610134… "Independent … Senate Canada
#> 12 Wanda Thomas Bernard SenatorWa… 831610134… "Non-affiliat… Senate Canada
#> 13 Wanda Thomas Bernard SenatorWa… 831610134… "Non-affiliat… Senate Canada
#> # … with 2 more variables: Legislative period <chr>, Notes <chr>
创建于2021-11-11由reprex包(v2.0.1(