如何将数据帧转换为DTM

时间:2017-06-21 15:43:21

标签: r tidy quanteda qdap tidytext

我想把我的表放到DTM中并维护元数据。

Same Data

每行应该是一个文档。但是为了使用cast_dtm(),需要有一个count变量。为了“演员”,它需要采用“文档,术语,计数”格式。

如何将数据转换为“文档,术语,计数”数据框?从那里,很容易被投入DTM,然后做我需要的。

2 个答案:

答案 0 :(得分:2)

您还可以使用 quanteda 包。

要重新创建data.frame:

df <- data.frame(Date = c("2015-01-01", "2015-01-01", "2015-01-03", "2015-01-01"),
                 Group = "Cars",
                 Reporting = c(rep("A", 3), "B"),
                 Comments = c(rep("This car is awesome", 3), "No comments"),
                 stringsAsFactors = FALSE)
df
#         Date Group Reporting            Comments
# 1 2015-01-01  Cars         A This car is awesome
# 2 2015-01-01  Cars         A This car is awesome
# 3 2015-01-03  Cars         A This car is awesome
# 4 2015-01-01  Cars         B         No comments

文档术语矩阵的简短方法:

dfm(df$Comments)
# Document-feature matrix of: 4 documents, 6 features (41.7% sparse).
# 4 x 6 sparse Matrix of class "dfmSparse"
#        features
# docs    this car is awesome no comments
#   text1    1   1  1       1  0        0
#   text2    1   1  1       1  0        0
#   text3    1   1  1       1  0        0
#   text4    0   0  0       0  1        1

dfm很长的路要走:

制作一份语料库,包括文档变量:

require(quanteda)
myCorpus <- corpus(df, text_field = "Comments")
summary(myCorpus)
# Corpus consisting of 4 documents.
# 
#  Text Types Tokens Sentences       Date Group Reporting
# text1     4      4         1 2015-01-01  Cars         A
# text2     4      4         1 2015-01-01  Cars         A
# text3     4      4         1 2015-01-03  Cars         A
# text4     2      2         1 2015-01-01  Cars         B
# 
# Source:  /Users/kbenoit/Dropbox (Personal)/GitHub/quanteda/* on x86_64 by kbenoit
# Created: Wed Jun 21 23:34:35 2017
# Notes:  

然后:

dfm(myCorpus)
# Document-feature matrix of: 4 documents, 6 features (41.7% sparse).
# 4 x 6 sparse Matrix of class "dfmSparse"
#        features
# docs    this car is awesome no comments
#   text1    1   1  1       1  0        0
#   text2    1   1  1       1  0        0
#   text3    1   1  1       1  0        0
#   text4    0   0  0       0  1        1

答案 1 :(得分:1)

试试这个

library(tm)
myCorpus <- Corpus(VectorSource(df))  
dtm <- DocumentTermMatrix(myCorpus)

我已将上述代码用于文本项目,但我已将df替换为df $ column