我正在分析一所学校的学生成绩单数据库。我的数据集由大约3000条记录组成，结构与下面的示例类似。每次观察都是一位老师对一位学生的评价。每个观察都包含一个三句话的叙述性评论。
为了分享我的分析结果，我想从评论中删除提到的学生名字，并用其他名字代替。在一个理想的世界里，我也想分享一个匿名版本的数据库，为了再现性。
学生名字的不一致使用(名字、昵称和全名)和学生名字的非结构化使用使得这对于像我这样的业余爱好者来说相当棘手。我试图解决这个问题的方法是将注释作为语料库中的文档，并使用编写一个使用tm::removeWords的函数，但它对我不起作用。提前感谢!
示例数据(此处为表的dput)
Teacher Subject Student.Name Comment
1 Black Math Richard (Dick) Dick is a terrible student-- why hasn't he been kicked out yet?
2 Black Math Elizabeth (Betty) Betty procrastinates, but does good work.
3 Black Math Mary Grace (MG) As her teacher, I think MG is my favorite.
4 Brown English Richard (Dick) Richard is terrible at turning in homework.
5 Brown English Elizabeth (Betty) Elizabeth's work is interfering with her studies.
6 Brown English Mary Grace (MG) Mary Grace should be a teacher someday.
7 Blue P.E. Richard (Dick) Richard (Dick) kicked more field goals than any other student.
8 Blue P.E. Elizabeth (Betty) Elizabeth (Betty) needs to work to communicate on the field.
9 Blue P.E. Mary Grace (MG) Mary Grace (MG) needs to stop insulting the teacher
Teacher Subject Student Name Comment
Black Math A A is a terrible student-- why hasn't he been kicked out yet?
Black Math B B procrastinates, but does good work.
Black Math C As her teacher, I think C is my favorite.
Brown English A A is terrible at turning in homework
Brown English B B's work is interfering with her studies.
Brown English C C should be a teacher someday.
Blue P.E. A A kicked more field goals than any other student.
Blue P.E. B B needs to work to communicate on the field.
Blue P.E. C C needs to stop insulting the teacher
注意:
四个月前，我问了这个问题的一个版本，没有得到答复。我认为这将有助于展示我的解决方案，但也许tm包没有被广泛使用。这是另一个镜头
我将在这里使用qdap包中的mgsub。您可以这样做(不过要注意确保学生的id是相同的，这里可能过于特定于您的示例，其中包含每个学生的昵称):
names <- unique(as.character(reports$Student.Name))
ids <- sample(100000, length(names))
tocheck <- c(
names,
unlist(regmatches(names, gregexpr("(?<=\().*?(?=\))", names, perl = T))),
gsub("\s*\([^\)]+\)","",as.character(names))
)
reports$Student.Name <- rep(ids, 3)
reports$Comment <- qdap::mgsub(tocheck, rep(ids, 3), reports$Comment)
Student.Name Comment
1 61034 61034 is a terrible student-- why hasn't he been kicked out yet?
2 45005 45005 procrastinates, but does good work.
3 13699 As her teacher, I think 13699 is my favorite.
4 61034 61034 is terrible at turning in homework
5 45005 45005's work is interfering with her studies.
6 13699 13699 should be a teacher someday.
7 61034 61034 kicked more field goals than any other student.
8 45005 45005 needs to work to communicate on the field.
9 13699 13699 needs to stop insulting the teacher
我不认为有一个简单的一刀切的解决方案。我可能会尝试一下正则表达式。
## load dput data
#eval(parse(text=paste0(readLines("http://pastebin.com/raw/MbghGybd", warn = F), collapse="n")))
# anonymize:
r <- regexec("(\w+)\s(?:(\w+)\s)?\((\w+)\)", levels(reports$Student.Name))
m <- regmatches(levels(reports$Student.Name), r)
names(m) <- levels(reports$Student.Name)
m <- lapply(m, function(x) {
paste(sprintf("%s\s*\(%s\)", x[2], x[4]), sprintf("%s %s \(%s\)", x[2], x[3], x[4]), x[2], x[4], paste(x[2], x[3], sep=" "), sep="|")
})
rep <- split(reports, reports$Student.Name)
for (x in seq_along(names(rep))) {
rep[[x]]$Comment <- gsub(m[[names(rep)[x]]], x, rep[[x]]$Comment, perl=TRUE)
}
transform(do.call(rbind, rep), Student.Name=as.integer(Student.Name))
# Teacher Subject Student.Name Comment
# Elizabeth (Betty).2 Black Math 1 1 procrastinates, but does good work.
# Elizabeth (Betty).5 Brown English 1 1's work is interfering with her studies.
# Elizabeth (Betty).8 Blue P.E. 1 1 needs to work to communicate on the field.
# Mary Grace (MG).3 Black Math 2 As her teacher, I think 2 is my favorite.
# Mary Grace (MG).6 Brown English 2 2 Grace should be a teacher someday.
# Mary Grace (MG).9 Blue P.E. 2 2 needs to stop insulting the teacher
# Richard (Dick).1 Black Math 3 3 is a terrible student-- why hasn't he been kicked out yet?
# Richard (Dick).4 Brown English 3 3 is terrible at turning in homework
# Richard (Dick).7 Blue P.E. 3 3 kicked more field goals than any other student.
但是这肯定需要大量的调整才能得到真实的数据集。