提取出主队和客队，在 R 中按 "at" 分隔

Question

我有一个大学篮球对决的向量：

c("#34 Colorado  at  #36 California", "#31 Utah  at  #87 Stanford", 
"#26 USC  at  #112 Wash State", "#56 UCLA  at  #134 Washington", 
"#187 W Illinois  at  #116 Neb Omaha", "#222 Denver  at  #58 S Dakota St", 
"#245 IUPUI  at  #170 South Dakota", "#268 Rice  at  #208 TX El Paso", 
"#274 North Texas  at  #344 TX-San Ant", "#14 Iowa  at  #3 Purdue"
)

我想要两个单独的向量：一个用于at之前的团队，另一个用于at之后出现的团队。例如)第一个向量有Colorado、Utah、USC等，第二个向量有California、Stanford、Wash State等。

请注意，我不想要#排名。我只想要团队名称。我试过str_split，但效果不太好，因为间距都不一致。

Answer 1

我们可以在"at"上使用strsplit和拆分，这将给我们 2 个字符串部分，从每个部分中删除"#"后跟数字并将其放入数据帧中。

data.frame(t(sapply(strsplit(string, "\bat\b"), 
function(x) trimws(sub("#[0-9]+", "", x)))))

#            X1           X2
#1     Colorado   California
#2         Utah     Stanford
#3          USC   Wash State
#4         UCLA   Washington
#5    W Illinois    Neb Omaha
#6       Denver  S Dakota St
#7        IUPUI South Dakota
#8         Rice   TX El Paso
#9  North Texas   TX-San Ant
#10        Iowa       Purdue

---

或使用tidyr::separate

tidyr::separate(data.frame(col = trimws(gsub("#[0-9]+", "", string))),
col, into = c("T1", "T2"), sep = "\bat\b")

#            T1                T2
#1     Colorado        California
#2         Utah          Stanford
#3          USC        Wash State
#4         UCLA        Washington
#5   W Illinois         Neb Omaha
#6       Denver       S Dakota St
#7        IUPUI      South Dakota
#8         Rice        TX El Paso
#9  North Texas        TX-San Ant
#10        Iowa            Purdue

Answer 2

另一种str_extract_all()解决方案

df <- data.frame(stringsAsFactors = FALSE,
text = c("#34 Colorado  at  #36 California", "#31 Utah  at  #87 Stanford", 
"#26 USC  at  #112 Wash State", "#56 UCLA  at  #134 Washington", 
"#187 W Illinois  at  #116 Neb Omaha", "#222 Denver  at  #58 S Dakota St", 
"#245 IUPUI  at  #170 South Dakota", "#268 Rice  at  #208 TX El Paso", 
"#274 North Texas  at  #344 TX-San Ant", "#14 Iowa  at  #3 Purdue")
)
library(stringr)
library(dplyr)
df %>% 
mutate(team_a = str_extract_all(text, "(?<=\s).+(?=\s+at)"),
team_b = str_extract_all(text, "(?<=\d\s)[^\d]+$"))
#>                                     text       team_a       team_b
#> 1       #34 Colorado  at  #36 California    Colorado    California
#> 2             #31 Utah  at  #87 Stanford        Utah      Stanford
#> 3           #26 USC  at  #112 Wash State         USC    Wash State
#> 4          #56 UCLA  at  #134 Washington        UCLA    Washington
#> 5    #187 W Illinois  at  #116 Neb Omaha  W Illinois     Neb Omaha
#> 6       #222 Denver  at  #58 S Dakota St      Denver   S Dakota St
#> 7      #245 IUPUI  at  #170 South Dakota       IUPUI  South Dakota
#> 8         #268 Rice  at  #208 TX El Paso        Rice    TX El Paso
#> 9  #274 North Texas  at  #344 TX-San Ant North Texas    TX-San Ant
#> 10               #14 Iowa  at  #3 Purdue        Iowa        Purdue

^{创建于 2019-03-29 由 reprex 软件包 (v0.2.1)}

Answer 3

我们可以在base R中通过从"text"列中删除子字符串并使用read.csv来做到这一点

read.csv(text = trimws(gsub("#\d+", "", gsub("\s+at\s+", ",", df$text))),
header = FALSE, col.names = c("T1", "T2"), stringsAsFactors = FALSE)
#            T1            T2
#1     Colorado    California
#2         Utah      Stanford
#3          USC    Wash State
#4         UCLA    Washington
#5   W Illinois     Neb Omaha
#6       Denver   S Dakota St
#7        IUPUI  South Dakota
#8         Rice    TX El Paso
#9  North Texas    TX-San Ant
#10        Iowa        Purdue