r - 您如何根据某些搜索字符串创建正则表达式以对数据框进行子集化？

Question

我正在尝试搜索字符串来对数据框进行子集化。我的 df 看起来像这样:

dput(df)
structure(list(Cause = structure(c(2L, 1L), .Label = c("jasper not able to read the property table after the release", 
"More than 7000  messages loaded which stuck up"), class = "factor"), 
    Resolution = structure(1:2, .Label = c("jobs and reports are processed", 
    "Updated the property table which resolved the issue."), class = "factor")), .Names = c("Cause", 
"Resolution"), class = "data.frame", row.names = c(NA, -2L))

我正在尝试这样做:

df1<-subset(df, grepl("*MQ*|*queue*|*Queue*", df$Cause))

在 Cause 列中搜索 MQ 或队列或队列，使用匹配的记录对数据框 df 进行子集化。它似乎不起作用，它正在捕获不存在 MQ、队列或队列字符串的其他记录。

这就是你这样做的方式，我可以遵循任何其他想法吗？

Answer 1

下面的正则表达式似乎有效。我在您的 data.frame 中添加了一行所以这是一个更有趣的例子。

我认为问题来自 * s 在您的正则表达式中，还添加了大括号来定义 | 的组但不要认为这是强制性的。

df <- data.frame(Cause=c("jasper not able to read the property table after the release", 
                         "More than 7000  messages loaded which stuck up",
                         "blabla Queue blabla"),
                 Resolution = c("jobs and reports are processed", 
                                "Updated the property table which resolved the issue.",
                                "hop"))

> head(df)
Cause                                           Resolution
1 jasper not able to read the property table after the release                       jobs and reports are processed
2               More than 7000  messages loaded which stuck up Updated the property table which resolved the issue.
3                                          blabla Queue blabla                                                  hop

> subset(df, grepl("(MQ)|(queue)|(Queue)", df$Cause))
Cause Resolution
3 blabla Queue blabla        hop

这是你想要的吗？