# Text Mining using 'dplyr', 'ggplot2', and Other Tidy Tools

## Documentation for package ‘tidytext’ version 0.4.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

augment.CTM | Tidiers for LDA and CTM objects from the topicmodels package
augment.jobjRef | Tidiers for Latent Dirichlet Allocation models from the mallet package
augment.LDA | Tidiers for LDA and CTM objects from the topicmodels package
augment.STM | Tidiers for Structural Topic Models from the stm package
bind_tf_idf | Bind the term frequency and inverse document frequency of a tidy text dataset to the dataset
cast_dfm | Casting a data frame to a DocumentTermMatrix, TermDocumentMatrix, or dfm
cast_dtm | Casting a data frame to a DocumentTermMatrix, TermDocumentMatrix, or dfm
cast_sparse | Create a sparse matrix from row names, column names, and values in a table.
cast_tdm | Casting a data frame to a DocumentTermMatrix, TermDocumentMatrix, or dfm
corpus_tidiers | Tidiers for a corpus object from the quanteda package
dictionary_tidiers | Tidy dictionary objects from the quanteda package
get_sentiments | Get a tidy data frame of a single sentiment lexicon
get_stopwords | Get a tidy data frame of a single stopword lexicon
glance.corpus | Tidiers for a corpus object from the quanteda package
glance.CTM | Tidiers for LDA and CTM objects from the topicmodels package
glance.estimateEffect | Tidiers for Structural Topic Models from the stm package
glance.LDA | Tidiers for LDA and CTM objects from the topicmodels package
glance.STM | Tidiers for Structural Topic Models from the stm package
lda_tidiers | Tidiers for LDA and CTM objects from the topicmodels package
mallet_tidiers | Tidiers for Latent Dirichlet Allocation models from the mallet package
nma_words | English negators, modals, and adverbs
parts_of_speech | Parts of speech for English words from the Moby Project
reorder_func | Reorder an x or y axis within facets
reorder_within | Reorder an x or y axis within facets
scale_x_reordered | Reorder an x or y axis within facets
scale_y_reordered | Reorder an x or y axis within facets
sentiments | Sentiment lexicon from Bing Liu and collaborators
stm_tidiers | Tidiers for Structural Topic Models from the stm package
stop_words | Various lexicons for English stop words
tdm_tidiers | Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package
tidy.Corpus | Tidy a Corpus object from the tm package
tidy.corpus | Tidiers for a corpus object from the quanteda package
tidy.CTM | Tidiers for LDA and CTM objects from the topicmodels package
tidy.dfm | Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package
tidy.dfmSparse | Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package
tidy.dictionary2 | Tidy dictionary objects from the quanteda package
tidy.DocumentTermMatrix | Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package
tidy.estimateEffect | Tidiers for Structural Topic Models from the stm package
tidy.jobjRef | Tidiers for Latent Dirichlet Allocation models from the mallet package
tidy.LDA | Tidiers for LDA and CTM objects from the topicmodels package
tidy.simple_triplet_matrix | Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package
tidy.STM | Tidiers for Structural Topic Models from the stm package
tidy.TermDocumentMatrix | Tidy DocumentTermMatrix, TermDocumentMatrix, and related objects from the tm package
tidy_triplet | Utility function to tidy a simple triplet matrix
unnest_characters | Wrapper around unnest_tokens for characters and character shingles
unnest_character_shingles | Wrapper around unnest_tokens for characters and character shingles
unnest_lines | Wrapper around unnest_tokens for sentences, lines, and paragraphs
unnest_ngrams | Wrapper around unnest_tokens for n-grams
unnest_paragraphs | Wrapper around unnest_tokens for sentences, lines, and paragraphs
unnest_ptb | Wrapper around unnest_tokens for Penn Treebank Tokenizer
unnest_regex | Wrapper around unnest_tokens for regular expressions
unnest_sentences | Wrapper around unnest_tokens for sentences, lines, and paragraphs
unnest_skip_ngrams | Wrapper around unnest_tokens for n-grams
unnest_tokens | Split a column into tokens