如何将具有单列的R数据帧转换为tm的语料库，以使每一行都作为文档？

我建议您tm在继续之前先阅读-vignette。在下面回答您的特定问题。

创建示例数据：

txt <- strsplit("I wanted to use the findAssocs of the tm package. but it works only when there are more than one documents in the corpus. I have a data frame table which has one column and each row has a tweet text. Is it possible to convert the into a corpus which takes each row as a new document?", split=" ")[[1]]
data <- data.frame(text=txt, stringsAsFactors=FALSE)
data[1:5, ]

将数据导入“源”，将“源”导入“ Corpus”，然后从“ Corpus”中制作TDM：

library(tm)
tdm <- TermDocumentMatrix(Corpus(DataframeSource(data)))

show(tdm)
#A term-document matrix (35 terms, 58 documents)
#
#Non-/sparse entries: 43/1987
#Sparsity           : 98%
#Maximal term length: 10 
#Weighting          : term frequency (tf)

str(tdm)
#List of 6
# $ i       : int [1:43] 32 31 28 12 28 21 3 35 20 33 ...
# $ j       : int [1:43] 2 4 5 6 8 10 11 13 14 15 ...
# $ v       : num [1:43] 1 1 1 1 1 1 1 1 1 1 ...
# $ nrow    : int 35
# $ ncol    : int 58
# $ dimnames:List of 2
#  ..$ Terms: chr [1:35] "and" "are" "but" "column" ...
#  ..$ Docs : chr [1:58] "1" "2" "3" "4" ...
# - attr(*, "class")= chr [1:2] "TermDocumentMatrix" "simple_triplet_matrix"
# - attr(*, "Weighting")= chr [1:2] "term frequency" "tf"