blocks|key|768185|text|我建议编写一个小脚本，并使用Grep执行多次搜索。我从来没有找到搜索多个模式的方法，相信我，我已经找过了！|type|unstyled|depth|inlineStyleRanges|entityRanges|data|768186|就像这样，您的shell文件中嵌入了一个字符串：|768187|+#!/bin/bash+
+grep+*A6*+"Alex+A1+Alex+A6+Alex+A7+Bob+A1+Chris+A9+Chris+A6";
+grep+*A7*+"Alex+A1+Alex+A6+Alex+A7+Bob+A1+Chris+A9+Chris+A6";
+grep+*A8*+"Alex+A1+Alex+A6+Alex+A7+Bob+A1+Chris+A9+Chris+A6";|code-block|syntax|javascript|768188|然后输入myshell.sh运行。|768189|如果您希望能够在命令行上传递字符串，可以这样做，并带有一个shell参数--这是bash符号btw：|768190|+#!/bin/bash+
+$stingtomatch+=+"${1}";
+grep+*A6*+"${stingtomatch}";
+grep+*A7*+"${stingtomatch}";
+grep+*A8*+"${stingtomatch}";|768191|以此类推。|768192|如果有很多模式需要匹配，你可以把它放在for循环中。|768193|entityMap^0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|V|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|W|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|X|8|@]|9|@]|A|$]]|$1|K|3|L|5|6|7|Y|8|@]|9|@]|A|$]]|$1|M|3|N|5|F|7|Z|8|@]|9|@]|A|$G|H]]|$1|O|3|P|5|6|7|10|8|@]|9|@]|A|$]]|$1|Q|3|R|5|6|7|11|8|@]|9|@]|A|$]]|$1|S|3|-4|5|6|7|12|8|@]|9|@]|A|$]]]|T|$]]

I suggest writing a little script and doing multiple searches with Grep. I've never found a way to search for multiple patterns, and believe me, I've looked!

Like so, your shell file, with an embedded string:

<pre><code> #!/bin/bash 
 grep *A6* "Alex A1 Alex A6 Alex A7 Bob A1 Chris A9 Chris A6";
 grep *A7* "Alex A1 Alex A6 Alex A7 Bob A1 Chris A9 Chris A6";
 grep *A8* "Alex A1 Alex A6 Alex A7 Bob A1 Chris A9 Chris A6";
</code></pre>

Then run by typing myshell.sh.

If you want to be able to pass in the string on the command line, do it like this, with a shell argument--this is bash notation btw:

<pre><code> #!/bin/bash 
 $stingtomatch = "${1}";
 grep *A6* "${stingtomatch}";
 grep *A7* "${stingtomatch}";
 grep *A8* "${stingtomatch}";
</code></pre>

And so forth. 

If there are a lot of patterns to match, you can put it in a for loop.

blocks|key|768248|text|除了@Marek关于不包含fixed==TRUE的评论之外，您还需要在正则表达式中不包含空格。应该是"A1%7CA9%7CA6"。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|768249|您还提到有很多模式。假设它们在一个向量中|768250|toMatch+<-+c("A1",+"A9",+"A6")|code-block|syntax|javascript|768251|然后，您可以使用paste和collapse+=+"%7C"直接创建正则表达式。|768252|matches+<-+unique+(grep(paste(toMatch,collapse="%7C"),+
++++++++++++++++++++++++myfile$Letter,+value=TRUE))|768253|entityMap^0|D|B|1E|A|0|0|0|8|5|E|E|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@$9|T|A|U|B|C]|$9|V|A|W|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|X|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|Y|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|Z|8|@$9|10|A|11|B|C]|$9|12|A|13|B|C]]|D|@]|E|$]]|$1|O|3|P|5|J|7|14|8|@]|D|@]|E|$K|L]]|$1|Q|3|-4|5|6|7|15|8|@]|D|@]|E|$]]]|R|$]]

In addition to @Marek's comment about not including <code>fixed==TRUE</code>, you also need to not have the spaces in your regular expression. It should be <code>"A1|A9|A6"</code>. 

You also mention that there are lots of patterns. Assuming that they are in a vector

<pre><code>toMatch &lt;- c("A1", "A9", "A6")
</code></pre>

Then you can create your regular expression directly using <code>paste</code> and <code>collapse = "|"</code>.

<pre><code>matches &lt;- unique (grep(paste(toMatch,collapse="|"), 
 myfile$Letter, value=TRUE))
</code></pre>

blocks|key|551549|text|您尝试过match()或charmatch()函数吗？|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|551550|示例用法：|551551|match(c("A1",+"A9",+"A6"),+myfile$Letter)|code-block|syntax|javascript|551552|entityMap^0|4|7|C|B|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]|$9|R|A|S|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|T|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|U|8|@]|D|@]|E|$K|L]]|$1|M|3|-4|5|6|7|V|8|@]|D|@]|E|$]]]|N|$]]

Have you tried the <code>match()</code> or <code>charmatch()</code> functions?

Example use:

<pre><code>match(c("A1", "A9", "A6"), myfile$Letter)
</code></pre>

blocks|key|768335|text|根据Brian+Digg的帖子，这里有两个用于过滤列表的有用函数：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|768336|#Returns+all+items+in+a+list+that+are+not+contained+in+toMatch
#toMatch+can+be+a+single+item+or+a+list+of+items
exclude+<-+function+(theList,+toMatch){
++return(setdiff(theList,include(theList,toMatch)))
}

#Returns+all+items+in+a+list+that+ARE+contained+in+toMatch
#toMatch+can+be+a+single+item+or+a+list+of+items
include+<-+function+(theList,+toMatch){
++matches+<-+unique+(grep(paste(toMatch,collapse="%7C"),+
++++++++++++++++++++++++++theList,+value=TRUE))
++return(matches)
}|code-block|syntax|javascript|768337|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Based on Brian Digg's post, here are two helpful functions for filtering lists:

<pre><code>#Returns all items in a list that are not contained in toMatch
#toMatch can be a single item or a list of items
exclude &lt;- function (theList, toMatch){
 return(setdiff(theList,include(theList,toMatch)))
}

#Returns all items in a list that ARE contained in toMatch
#toMatch can be a single item or a list of items
include &lt;- function (theList, toMatch){
 matches &lt;- unique (grep(paste(toMatch,collapse="|"), 
 theList, value=TRUE))
 return(matches)
}
</code></pre>

blocks|key|551698|text|添加到Brian+Diggs的答案中。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|551699|使用grepl的另一种方法将返回一个包含所有值的数据框。|551700|toMatch+<-+myfile$Letter

matches+<-+myfile[grepl(paste(toMatch,+collapse="%7C"),+myfile$Letter),+]

matches

Letter+Firstname
1+++++A1++++++Alex+
2+++++A6++++++Alex+
4+++++A1+++++++Bob+
5+++++A9+++++Chris+
6+++++A6+++++Chris|code-block|syntax|javascript|551701|也许会更干净一点。也许吧?|551702|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|N|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|O|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|P|8|@]|9|@]|A|$]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

To add to Brian Diggs answer.

another way using grepl will return a data frame containing all your values.

<pre><code>toMatch &lt;- myfile$Letter

matches &lt;- myfile[grepl(paste(toMatch, collapse="|"), myfile$Letter), ]

matches

Letter Firstname
1 A1 Alex 
2 A6 Alex 
4 A1 Bob 
5 A9 Chris 
6 A6 Chris
</code></pre>

Maybe a bit cleaner... maybe?

blocks|key|551741|text|不确定这个答案是否已经出现...|type|unstyled|depth|inlineStyleRanges|entityRanges|data|551742|对于问题中的特定模式，您只需使用一个grep()调用即可完成。|offset|length|style|CODE|551743|grep("A[169]",+myfile$Letter)|code-block|syntax|javascript|551744|entityMap^0|0|I|6|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|P|8|@$D|Q|E|R|F|G]]|9|@]|A|$]]|$1|H|3|I|5|J|7|S|8|@]|9|@]|A|$K|L]]|$1|M|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|N|$]]

Not sure whether this answer has already appeared...

For the particular pattern in the question, you can just do it with a single <code>grep()</code> call,

<pre><code>grep("A[169]", myfile$Letter)
</code></pre>

blocks|key|551807|text|很好的答案，但是不要忘记来自dplyr的filter()：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|551808|patterns+<-+c("A1",+"A9",+"A6")
>your_df
++FirstName+Letter
1++++++Alex+++++A1
2++++++Alex+++++A6
3++++++Alex+++++A7
4+++++++Bob+++++A1
5+++++Chris+++++A9
6+++++Chris+++++A6

result+<-+filter(your_df,+grepl(paste(patterns,+collapse="%7C"),+Letter))

>result
++FirstName+Letter
1++++++Alex+++++A1
2++++++Alex+++++A6
3+++++++Bob+++++A1
4+++++Chris+++++A9
5+++++Chris+++++A6|code-block|syntax|javascript|551809|entityMap^0|K|8|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|P|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|Q|8|@]|D|@]|E|$]]]|L|$]]

Good answers, however don't forget about <code>filter()</code> from dplyr:

<pre><code>patterns &lt;- c("A1", "A9", "A6")
&gt;your_df
 FirstName Letter
1 Alex A1
2 Alex A6
3 Alex A7
4 Bob A1
5 Chris A9
6 Chris A6

result &lt;- filter(your_df, grepl(paste(patterns, collapse="|"), Letter))

&gt;result
 FirstName Letter
1 Alex A1
2 Alex A6
3 Bob A1
4 Chris A9
5 Chris A6
</code></pre>

blocks|key|768505|text|使用sapply|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|768506|+patterns+<-+c("A1",+"A9",+"A6")
+++++++++df+<-+data.frame(name=c("A","Ale","Al","lex","x"),Letters=c("A1","A2","A9","A1","A9"))



+++name+Letters
1++++A++++++A1
2++Ale++++++A2
3+++Al++++++A9
4++lex++++++A1
5++++x++++++A9


+df[unlist(sapply(patterns,+grep,+df$Letters,+USE.NAMES+=+F)),+]
++name+Letters
1++++A++++++A1
4++lex++++++A1
3+++Al++++++A9
5++++x++++++A9|code-block|syntax|javascript|768507|entityMap^0|2|6|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|P|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|Q|8|@]|D|@]|E|$]]]|L|$]]

Using the <code>sapply</code> 

<pre><code> patterns &lt;- c("A1", "A9", "A6")
 df &lt;- data.frame(name=c("A","Ale","Al","lex","x"),Letters=c("A1","A2","A9","A1","A9"))



 name Letters
1 A A1
2 Ale A2
3 Al A9
4 lex A1
5 x A9


 df[unlist(sapply(patterns, grep, df$Letters, USE.NAMES = F)), ]
 name Letters
1 A A1
4 lex A1
3 Al A9
5 x A9
</code></pre>

blocks|key|768592|text|去掉空格。也是如此：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|768593|matches+<-+unique(grep("A1%7CA9%7CA6",+myfile$Letter,+value=TRUE,+fixed=TRUE))|code-block|syntax|javascript|768594|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Take away the spaces. So do:

<pre><code>matches &lt;- unique(grep("A1|A9|A6", myfile$Letter, value=TRUE, fixed=TRUE))
</code></pre>

blocks|key|551933|text|这应该是可行的：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|551934|grep(pattern+=+'A1%7CA9%7CA6',+x+=+myfile$Letter)|code-block|syntax|javascript|551935|或者更简单地说：|551936|library(data.table)
myfile$Letter+%25like%25+'A1%7CA9%7CA6'|551937|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

This should work:
<pre><code>grep(pattern = 'A1|A9|A6', x = myfile$Letter)
</code></pre>
Or even more simply:
<pre><code>library(data.table)
myfile$Letter %like% 'A1|A9|A6'
</code></pre>

I am trying to use <code>grep</code> to test whether a vector of strings are present in an another vector or not, and to output the values that are present (the matching patterns). 

I have a data frame like this:

<pre><code>FirstName Letter 
Alex A1
Alex A6
Alex A7
Bob A1
Chris A9
Chris A6
</code></pre>

I have a vector of strings patterns to be found in the "Letter" columns, for example: <code>c("A1", "A9", "A6")</code>.

I would like to check whether the any of the strings in the pattern vector is present in the "Letter" column. If they are, I would like the output of unique values. 

The problem is, I don't know how to use <code>grep</code> with multiple patterns. I tried:

<pre><code>matches &lt;- unique (
 grep("A1| A9 | A6", myfile$Letter, value=TRUE, fixed=TRUE)
)
</code></pre>

But it gives me 0 matches which is not true, any suggestions?

grep using a character vector with multiple patterns

我正在尝试使用grep来测试字符串向量是否存在于另一个向量中，并输出存在的值(匹配模式)。我有一个这样的数据框架：FirstName Letter   Alex      A1Alex      A6Alex      A7Bob       A1Chris     A9Chris     A6我在"Letter“列中...

问使用具有多个模式的字符向量的grep
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