Question

我有一个表（数据框）myTable，其中包含一个列，如下所示：

         sentence
1      it is a window
2      My name is john doe
3      Thank you
4      Good luck
.
.
.

我想将其转换为R中的Term Document Matrix。我这样做了：

tdm_s <- TermDocumentMatrix(Corpus(DataframeSource(myTable)))

但是我收到了这个错误：

Error: all(!is.na(match(c("doc_id", "text"), names(x)))) is not TRUE

我用谷歌搜索，无法找到任何东西。我该如何进行转换？

Answer 1

您需要执行以下操作才能转换为术语文档矩阵：

## Your sample data
myTable <- data.frame(sentence = c("it is a window", "My name is john doe", "Thank you", "Good luck"))

## You need to use VectorSource before using Corpus
library(tm)
myCorpus <- Corpus(VectorSource(myTable$sentence))
tdm <- TermDocumentMatrix(myCorpus)

inspect(tdm)
#<<TermDocumentMatrix (terms: 8, documents: 4)>>
#Non-/sparse entries: 8/24
#Sparsity           : 75%
#Maximal term length: 6
#Weighting          : term frequency (tf)
#Sample             :
#         Docs
#Terms   1 2 3 4
#doe     0 1 0 0
#good    0 0 0 1
#john    0 1 0 0
#luck    0 0 0 1
#name    0 1 0 0
#thank   0 0 1 0
#window  1 0 0 0
#you     0 0 1 0

Answer 2

如果您不介意使用Quanteda包（非常好）......

require(quanteda)
# Your sample data 
# Important to make sure the sentence variable is not converted to type factor
myTable <- data.frame(sentence = c("it is a window", "My name is john doe", "Thank you", "Good luck"),
                  stringsAsFactors = FALSE)
newcorpus <- corpus(myTable, text_field = "sentence") # you have to tell it the name of the text field
# lots of options to dfm read the help pages
newdfm <- dfm(newcorpus, remove_punct = TRUE, remove = stopwords("english"), stem = TRUE)
newdfm

如何将数据框转换为R中的术语文档矩阵？

2 个答案: