as.data.frame.default(dtm) 中的错误：无法将类 "c("DocumentTermMatrix", "simple_triplet_matrix")" 强制转换为 data.frame

Question

我有类似的问题，我从网上下载了一个大的推文文件 将其保存为 data.txt 并使用 rstudio（导入数据集）加载到 R 中。 但有错误，无法继续。

  This is step by step on what i did and the errors i had.

# required packages
library(twitteR)
library(plyr)
library(ggplot2)
library(wordcloud)
library(RColorBrewer)
library(tm)
library(XML)
library(SnowballC) 


 data<- read.csv("~/data/datasStream.txt", header=FALSE , sep = "," )

我有 3425 个观察值和 97 个变量

## i load it to corpus

corpus = Corpus(VectorSource(data)) ## 97 elements 17.4 MB

## i cleaned the data using 

corpus = tm_map (corpus, tolower)

corpus = tm_map (corpus, stripWhitespace)

corpus = tm_map (corpus, stemDocument)

corpus = tm_map (corpus, PlainTextDocument)

# remove unnecessary spaces
corpus = gsub("[ \t]{2,}", "", corpus)
corpus = gsub("^\\s+|\\s+$", "", corpus)


# remove NAs in corpus
corpus = corpus[!is.na(corpus)]

dtm = DocumentTermMatrix(corpus)

dtm

<<DocumentTermMatrix (documents: 97, terms: 151132)>>
Non-/sparse entries: 201231/14458573
Sparsity           : 99%
Maximal term length: 1775
Weighting          : term frequency (tf)


adtm <- removeSparseTerms(dtm, 0.75)

adtm
<<DocumentTermMatrix (documents: 97, terms: 270)>>
Non-/sparse entries: 11962/14228
Sparsity           : 54%
Maximal term length: 33
Weighting          : term frequency (tf)


df1 =  as.data.frame (m=as.matrix (adtm)) 

Error in as.data.frame.default(dtm) : cannot coerce class "c("DocumentTermMatrix", "simple_triplet_matrix")" to a data.frame

我该如何解决这个问题？我想对数据执行 k-means 聚类和词云。

这是一个示例数据：

{"created_at":"2013 年 2 月 27 日星期三 14:24:12 +0000","id":306771719996186625,"id_str":"306771719996186625","text":"@Joeypearce 我们又来了一个铃铛看看我要帮我打扫的车 :-/ 下班后再见！X","source":"\u003ca href=\"http://twitter.com/download/iphone\" rel = \“nofollow \ \ \ u003e”，“截断”：false，“in_reply_to_status_id”：“in_reply_to_status_id_str”，“in_reply_to_user_id”：127665137，“in_reply_to_user_id_str”：“ 127665137","in_reply_to_screen_name":"Joeypearce","user":{"id":274997668,"id_str":"274997668","name":"Ell Beaton \u00a9","screen_name":"Ell_Beaton"," location":"","url":null,"description":"去格伦，或者回家。","protected":false,"followers_count":147,"friends_count":85,"listed_count":0, "created_at":"Thu Mar 31 12:44:39 +0000 2011","favourites_count":132,"utc_offset":0,"time_zone":"London","geo_enabled":true,"verified":false, "statuses_count":1087,"lang":"en","contributors_ena流血":false,"is_translator":false,"profile_background_color":"1A1B1F","profile_background_image_url":"http://a0.twimg.com/profile_background_images/768018009/7a0b3fe303f234e8d6a5429bb9ede9a9.jpeg","profile_background_image_url_https":"https: //si0.twimg.com/profile_background_images/768018009/7a0b3fe303f234e8d6a5429bb9ede9a9.jpeg","profile_background_tile":true,"profile_image_url":"http://a0.twimg.com/profile_images/3304123896/606a7413bce208a1a38b1eb41fd017c9_normal.jpeg","profile_image_url_https” :"https://si0.twimg.com/profile_images/3304123896/606a7413bc​​e208a1a38b1eb41fd017c9_normal.jpeg","profile_banner_url":"https://si0.twimg.com/profile_banners/274997668/1361751912","0"profile_link_color":"E5 ,"profile_sidebar_border_color":"000000","profile_sidebar_fill_color":"252429","profile_text_color":"666666","profile_use_background_image":true,"default_profile":false,"default_profile_image":false,"following":null," follow_request_sent":null,"notifications":null},"geo":{"type":"Point","coor dinates":[52.43718380,-2.14324244]},"coordinates":{"type":"Point","coordinates":[-2.14324244,52.43718380]},"place":{"id":"ddeec3dc241e5b6a"," url":"http://api.twitter.com/1/geo/id/ddeec3dc241e5b6a.json","place_type":"city","name":"Dudley","full_name":"Dudley, Dudley" ,"country_code":"GB","country":"United Kingdom","bounding_box":{"type":"Polygon","coordinates":[[[-2.191947,52.426012],[-2.191947,52.558221] ,[-2.011849,52.558221],[-2.011849,52.426012]]]},"attributes":{}},"contributors":null,"retweet_count":0,"entities":{"hashtags":[], "urls":[],"user_mentions":[{"screen_name":"Joeypearce","name":"Joey Pearce","id":127665137,"id_str":"127665137","indices":[0 ,11]}]},"favorited":false,"retweeted":false,"filter_level":"medium"}

Answer 1

这是 R 文本挖掘的痛点之一。 dtm 和后续的 adtm 都有两种类类型。

class(dtm)
[1] "DocumentTermMatrix"    "simple_triplet_matrix"

对于转置，术语文档矩阵也是如此。您可以通过首先将 dtm,adtm（或者如果您制作了 tdm）转换为矩阵来解决此问题。我在 1000 条推文上对此进行了测试，并且能够进行强制转换。

adtm.m<-as.matrix(adtm)
adtm.df<-as.data.frame(adtm.m)

或者你可以嵌套函数：

adtm.df<-as.data.frame(as.matrix(adtm))

这有点笨拙，但要完成工作，您可以在此处查看新课程。

class(adtm.df)
[1] "data.frame"

Answer 2

这是因为R 的强制代码，恕我直言，拒绝尝试将任意类转换为数据帧。有两个原因。通常的一个是有问题的类可能是“衣衫褴褛的”，即任何试图变成data.frame的尝试都会产生不等长度的行或列。第二个原因是可能根本没有为对象定义强制方法有问题，这将是编写有问题的包的人的错。据我所知，这种情况要少得多。

您可能必须手动（例如通过循环或其他构造）提取对象内的记录并弄清楚如何构建类似矩阵的对象。