重命名列中的向量

Question

我有一个数据框，总结如下：

                            CEMETERY    SEX CONTEXT RaHD.L RaHD.R
1           Medieval-St. Mary Graces FEMALE    7172   21.2   21.6
2           Medieval-St. Mary Graces   MALE    6225   23.9   25.2
3           Medieval-St. Mary Graces   MALE    9987   23.9   23.5
4           Medieval-St. Mary Graces   MALE   11475   22.4   22.3
5           Medieval-St. Mary Graces   MALE   12356   25.8   25.4
6           Medieval-St. Mary Graces   MALE   12525   22.4   22.3
7           Medieval-St. Mary Graces   MALE   12785   22.9   22.6
8           Medieval-St. Mary Graces   MALE   13840   22.5   22.9
9             Medieval-Spital Square FEMALE     383   21.5   22.0
10            Medieval-Spital Square   MALE      31   23.3   22.0
17  Post-Medieval-Chelsea Old Church FEMALE      19   20.0   20.6
18  Post-Medieval-Chelsea Old Church FEMALE      31   19.5   20.0
19  Post-Medieval-Chelsea Old Church FEMALE      39   19.6   19.2
41 Post-Medieval-St. Thomas Hospital FEMALE      60   21.8   22.6
43 Post-Medieval-St. Thomas Hospital   MALE      83   22.4   23.0

我想将CEMETERY列中的向量更改为“中世纪”和“后中世纪”，而不是拥有整个墓地名称，或者创建一个新列，标明“中世纪”或“后中世纪”。

Answer 1

我们可以使用sub捕获子串到“Medieval”，然后在替换中使用反向引用（\\1）来捕获子串

df1$CEMETERY <- sub("(.*(M|m)edieval).*", "\\1", df1$CEMETERY)
df1$CEMETERY
#[1] "Medieval"      "Medieval"      "Medieval"      "Medieval"     
#[5] "Medieval"      "Medieval"      "Medieval"      "Medieval"     
#[9] "Medieval"      "Medieval"      "Post-Medieval" "Post-Medieval"
#[13] "Post-Medieval" "Post-Medieval" "Post-Medieval"

Answer 2

如果应该保留关于位置的信息，有一种替代方法将CEMETERY列拆分为“中世纪”之后的第一个连字符（包括在“后中世纪”之后拆分）并将这两个部分分配给两列PERIOD和CEMETERY：

library(data.table)
setDT(DF)[, c("PERIOD", "CEMETERY") := tstrsplit(CEMETERY, "(?<=Medieval)-", perl = TRUE)][]

               CEMETERY    SEX CONTEXT RaHD.L RaHD.R        PERIOD
 1:     St. Mary Graces FEMALE    7172   21.2   21.6      Medieval
 2:     St. Mary Graces   MALE    6225   23.9   25.2      Medieval
 3:     St. Mary Graces   MALE    9987   23.9   23.5      Medieval
 4:     St. Mary Graces   MALE   11475   22.4   22.3      Medieval
 5:     St. Mary Graces   MALE   12356   25.8   25.4      Medieval
 6:     St. Mary Graces   MALE   12525   22.4   22.3      Medieval
 7:     St. Mary Graces   MALE   12785   22.9   22.6      Medieval
 8:     St. Mary Graces   MALE   13840   22.5   22.9      Medieval
 9:       Spital Square FEMALE     383   21.5   22.0      Medieval
10:       Spital Square   MALE      31   23.3   22.0      Medieval
11:  Chelsea Old Church FEMALE      19   20.0   20.6 Post-Medieval
12:  Chelsea Old Church FEMALE      31   19.5   20.0 Post-Medieval
13:  Chelsea Old Church FEMALE      39   19.6   19.2 Post-Medieval
14: St. Thomas Hospital FEMALE      60   21.8   22.6 Post-Medieval
15: St. Thomas Hospital   MALE      83   22.4   23.0 Post-Medieval

正则表达式中用于标识要拆分的正确连字符的功能称为正向后视。

Data

DF <- readr::read_table(
  "                            CEMETERY    SEX CONTEXT RaHD.L RaHD.R
1           Medieval-St. Mary Graces FEMALE    7172   21.2   21.6
2           Medieval-St. Mary Graces   MALE    6225   23.9   25.2
3           Medieval-St. Mary Graces   MALE    9987   23.9   23.5
4           Medieval-St. Mary Graces   MALE   11475   22.4   22.3
5           Medieval-St. Mary Graces   MALE   12356   25.8   25.4
6           Medieval-St. Mary Graces   MALE   12525   22.4   22.3
7           Medieval-St. Mary Graces   MALE   12785   22.9   22.6
8           Medieval-St. Mary Graces   MALE   13840   22.5   22.9
9             Medieval-Spital Square FEMALE     383   21.5   22.0
10            Medieval-Spital Square   MALE      31   23.3   22.0
17  Post-Medieval-Chelsea Old Church FEMALE      19   20.0   20.6
18  Post-Medieval-Chelsea Old Church FEMALE      31   19.5   20.0
19  Post-Medieval-Chelsea Old Church FEMALE      39   19.6   19.2
41 Post-Medieval-St. Thomas Hospital FEMALE      60   21.8   22.6
43 Post-Medieval-St. Thomas Hospital   MALE      83   22.4   23.0"
)[, -1]