I am working with tidytext. When I command unnest_tokens. R returns the error
Please supply column name
How can I solve this error?
library(tidytext)
library(tm)
library(dplyr)
library(stats)
library(base)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~#
#Build a corpus: a collection of statements
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~#
f <-Corpus(DirSource("C:/Users/Boon/Desktop/Dissertation/F"))
doc_dir <- "C:/Users/Boon/Desktop/Dis/F/f.csv"
doc <- read.csv(file_loc, header = TRUE)
docs<- Corpus(DataframeSource(doc))
dtm <- DocumentTermMatrix(docs)
text_df<-data_frame(line=1:115,docs=docs)
#This is the output from the code above,which is fine!:
# text_df
# A tibble: 115 x 2
#line docs
#<int> <S3: VCorpus>
# 1 1 <S3: VCorpus>
#2 2 <S3: VCorpus>
#3 3 <S3: VCorpus>
#4 4 <S3: VCorpus>
#5 5 <S3: VCorpus>
#6 6 <S3: VCorpus>
#7 7 <S3: VCorpus>
#8 8 <S3: VCorpus>
#9 9 <S3: VCorpus>
#10 10 <S3: VCorpus>
# ... with 105 more rows
unnest_tokens(word, docs)
# Error: Please supply column name
If you want to convert your text data to a tidy format, you do not need to transform it to a corpus or a document term matrix or anything first. That is one of the main ideas behind using a tidy data format for text; you don't use those other formats, unless you need to for modeling.
You just put the raw text into a data frame, then use unnest_tokens() to tidy it. (I am making some assumptions here about what your CSV looks like; it would be more helpful to post a reproducible example next time.)
library(dplyr)
docs <- data_frame(line = 1:4,
document = c("This is an excellent document.",
"Wow, what a great set of words!",
"Once upon a time...",
"Happy birthday!"))
docs
#> # A tibble: 4 x 2
#> line document
#> <int> <chr>
#> 1 1 This is an excellent document.
#> 2 2 Wow, what a great set of words!
#> 3 3 Once upon a time...
#> 4 4 Happy birthday!
library(tidytext)
docs %>%
unnest_tokens(word, document)
#> # A tibble: 18 x 2
#> line word
#> <int> <chr>
#> 1 1 this
#> 2 1 is
#> 3 1 an
#> 4 1 excellent
#> 5 1 document
#> 6 2 wow
#> 7 2 what
#> 8 2 a
#> 9 2 great
#> 10 2 set
#> 11 2 of
#> 12 2 words
#> 13 3 once
#> 14 3 upon
#> 15 3 a
#> 16 3 time
#> 17 4 happy
#> 18 4 birthday