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我有一个包含多个字符串（文本）变量的文件，其中每个受访者为每个变量写了一两句话。我希望能够找到每个单词组合的频率（即“能力”与“性能”一起出现的频率）。到目前为止，我的代码是：

#Setting up the data file 
data.text <- scan("C:/temp/tester.csv", what="char", sep="\n")

#Change everything to lower text
data.text <- tolower(data.text)

#Split the strings into separate words
data.words.list <- strsplit(data.text, "\\W+", perl=TRUE)
data.words.vector <- unlist(data.words.list)

#List each word and frequency
data.freq.list <- table(data.words.vector)

这给了我每个单词的列表以及它在字符串变量中出现的频率。现在我想查看每 2 个单词组合的频率。这可能吗？

谢谢！

字符串数据示例：

ID   Reason_for_Dissatisfaction    Reason_for_Likelihood_to_Switch
1    "not happy with the service"  "better value at other place"
2    "poor customer service"       "tired of same old thing"
3    "they are overchanging me"    "bad service"
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1 回答 1

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我不确定这是否是你的意思，但不是在每两个单词边界上拆分（我发现尝试使用正则表达式很痛苦）你可以使用 trusty headand tailsslip 技巧将每两个单词粘贴在一起......

#  How I read your data
df <- read.table( text = 'ID   Reason_for_Dissatisfaction    Reason_for_Likelihood_to_Switch
1    "not happy with the service"  "better value at other place"
2    "poor customer service"       "tired of same old thing"
3    "they are overchanging me"    "bad service"
' , h = TRUE , stringsAsFactors = FALSE )


#  Split to words
wlist <- sapply( df[,-1] , strsplit , split = "\\W+", perl=TRUE)

#  Paste word pairs together
outl <- sapply( wlist , function(x) paste( head(x,-1) , tail(x,-1) , sep = " ") )

#  Table as per usual
table(unlist( outl ) )
are overchanging         at other      bad service     better value customer service 
               1                1                1                1                1 
      happy with        not happy          of same        old thing      other place 
               1                1                1                1                1 
 overchanging me    poor customer         same old      the service         they are 
               1                1                1                1                1 
        tired of         value at         with the 
               1                1                1
于 2013-09-18T07:39:25.583 回答