A C D E F H I K L M N P Q R S T U W misc
quanteda-package | An R package for the quantitative analysis of textual data |
applyDictionary | apply a dictionary or thesarus to an object |
applyDictionary.dfm | apply a dictionary or thesarus to an object |
as.data.frame-method | coerce a dfm to a data.frame |
as.data.frame.dfm | coerce a dfm to a data.frame |
as.dfm | create a document-feature matrix |
as.DocumentTermMatrix | convert a dfm to a non-quanteda format |
as.DocumentTermMatrix.dfm | convert a dfm to a non-quanteda format |
as.matrix-method | Virtual class "dfm" for a document-feature matrix |
as.matrix.similMatrix | compute similarities between documents and/or features |
as.tokenizedTexts | tokenize a set of texts |
as.wfm | convert a dfm to a non-quanteda format |
as.wfm.dfm | convert a dfm to a non-quanteda format |
c.corpus | constructor for corpus objects |
cbind.dfm | Combine dfm objects by Rows or Columns |
changeunits | change the document units of a corpus |
changeunits.corpus | change the document units of a corpus |
clean | tokenize a set of texts |
collocations | Detect collocations from text |
collocations.character | Detect collocations from text |
collocations.corpus | Detect collocations from text |
collocations.tokenizedTexts | Detect collocations from text |
colMeans-method | Virtual class "dfm" for a document-feature matrix |
colSums-method | Virtual class "dfm" for a document-feature matrix |
compress | compress a dfm by combining similarly named dimensions |
compress.dfm | compress a dfm by combining similarly named dimensions |
convert | convert a dfm to a non-quanteda format |
convert.dfm | convert a dfm to a non-quanteda format |
corpus | constructor for corpus objects |
corpus.character | constructor for corpus objects |
corpus.corpusSource | constructor for corpus objects |
corpus.data.frame | constructor for corpus objects |
corpus.VCorpus | constructor for corpus objects |
corpusSource-class | corpus source classes |
describeTexts | summarize a corpus or a vector of texts |
dfm | create a document-feature matrix |
dfm-class | Virtual class "dfm" for a document-feature matrix |
dfm.character | create a document-feature matrix |
dfm.corpus | create a document-feature matrix |
dfm.tokenizedTexts | create a document-feature matrix |
dfm2ldaformat | convert a dfm to a non-quanteda format |
dfm2ldaformat.dfm | convert a dfm to a non-quanteda format |
dfmDense-class | Virtual class "dfm" for a document-feature matrix |
dfmSparse-class | Virtual class "dfm" for a document-feature matrix |
dictionary | create a dictionary |
docfreq | #' @rdname weight #' @return 'weight, x' with no 'type' argument queries the weighting applied to the dfm, returning setMethod("weight", signature(c("dfm", "MISSING")), function(x) if (isS4(x)) x@weighting else attr(x, "weighting") ) |
docfreq-method | #' @rdname weight #' @return 'weight, x' with no 'type' argument queries the weighting applied to the dfm, returning setMethod("weight", signature(c("dfm", "MISSING")), function(x) if (isS4(x)) x@weighting else attr(x, "weighting") ) |
docnames | get or set document names |
docnames.corpus | get or set document names |
docnames.dfm | get or set document names |
docnames<- | get or set document names |
docvars | get or set for document-level variables |
docvars.corpus | get or set for document-level variables |
docvars.corpusSource | get or set for document-level variables |
docvars<- | get or set for document-level variables |
docvars<-.corpus | get or set for document-level variables |
encodedTextFiles | a .zip file of texts containing a variety of differently encoded texts |
encodedTexts | encoded texts for testing |
encoding | detect the encoding of texts |
encoding.character | detect the encoding of texts |
encoding.corpus | detect the encoding of texts |
encoding.corpusSource | detect the encoding of texts |
englishSyllables | count syllables in a text |
exampleString | A paragraph of text for testing various text-based functions |
features | extract the feature labels from a dfm |
features.dfm | extract the feature labels from a dfm |
head-method | Return the first or last part of a dfm |
head.dfm | Return the first or last part of a dfm |
ie2010Corpus | Irish budget speeches from 2010 |
iebudgets | Irish budget speeches from 2010 |
inaugCorpus | A corpus of US presidential inaugural addresses from 1789-2013 |
inaugTexts | A corpus of US presidential inaugural addresses from 1789-2013 |
is.corpus | constructor for corpus objects |
is.dfm | create a document-feature matrix |
is.tokenizedTexts | tokenize a set of texts |
kwic | List key words in context from a text or a corpus of texts. |
kwic.character | List key words in context from a text or a corpus of texts. |
kwic.corpus | List key words in context from a text or a corpus of texts. |
kwic.tokenizedTexts | List key words in context from a text or a corpus of texts. |
LBGexample | dfm with example data from Table 1 of Laver Benoit and Garry (2003) |
lexdiv | calculate lexical diversity |
lexdiv.dfm | calculate lexical diversity |
metacorpus | get or set corpus metadata |
metacorpus.corpus | get or set corpus metadata |
metacorpus<- | get or set corpus metadata |
metadoc | get or set document-level meta-data |
metadoc.corpus | get or set document-level meta-data |
metadoc<- | get or set document-level meta-data |
mobydickText | Project Gutenberg text of Herman Melville's _Moby Dick_ |
ndoc | get the number of documents or features |
ndoc.corpus | get the number of documents or features |
ndoc.dfm | get the number of documents or features |
nfeature | get the number of documents or features |
nfeature.corpus | get the number of documents or features |
nfeature.dfm | get the number of documents or features |
ngrams | Create ngrams and skipgrams |
ngrams.character | Create ngrams and skipgrams |
ngrams.tokenizedTexts | Create ngrams and skipgrams |
nsentence | count the number of sentences |
nsentence.character | count the number of sentences |
nsentence.corpus | count the number of sentences |
ntoken | count the number of tokens or types |
ntoken.character | count the number of tokens or types |
ntoken.corpus | count the number of tokens or types |
ntoken.dfm | count the number of tokens or types |
ntoken.tokenizedTexts | count the number of tokens or types |
ntype | count the number of tokens or types |
ntype.character | count the number of tokens or types |
ntype.corpus | count the number of tokens or types |
ntype.dfm | count the number of tokens or types |
ntype.tokenizedTexts | count the number of tokens or types |
phrasetotoken | convert phrases into single tokens |
phrasetotoken-method | convert phrases into single tokens |
plot.dfm | plot features as a wordcloud |
plot.kwic | plot a dispersion plot of key word(s) |
predict.textmodel_NB_fitted | prediction method for Naive Bayes classifier objects |
predict.textmodel_wordscores_fitted | Wordscores text model |
print-method | print a dfm object |
print.dfm | print a dfm object |
print.kwic | List key words in context from a text or a corpus of texts. |
print.settings | Get or set the corpus settings |
print.similMatrix | compute similarities between documents and/or features |
print.textmodel_wordfish_fitted | wordfish text model |
print.textmodel_wordscores_fitted | Wordscores text model |
print.textmodel_wordscores_predicted | Wordscores text model |
print.tokenizedTexts | print a tokenizedTexts objects |
quanteda | An R package for the quantitative analysis of textual data |
quantedaformat2dtm | convert a dfm to a non-quanteda format |
quantedaformat2dtm.dfm | convert a dfm to a non-quanteda format |
rbind.dfm | Combine dfm objects by Rows or Columns |
readability | calculate readability |
readability.character | calculate readability |
readability.corpus | calculate readability |
removeFeatures | remove features from an object |
rowMeans-method | Virtual class "dfm" for a document-feature matrix |
rowSums-method | Virtual class "dfm" for a document-feature matrix |
sample | Randomly sample documents or features |
sample.corpus | Randomly sample documents or features |
sample.default | Randomly sample documents or features |
sample.dfm | Randomly sample documents or features |
scrabble | compute the Scrabble letter values of text |
scrabble.character | compute the Scrabble letter values of text |
segment | segment texts into component elements |
segment.character | segment texts into component elements |
segment.corpus | segment texts into component elements |
selectFeatures | select features from an object |
selectFeatures.collocations | select features from an object |
selectFeatures.dfm | select features from an object |
selectFeatures.tokenizedTexts | select features from an object |
settings | Get or set the corpus settings |
settings.corpus | Get or set the corpus settings |
settings.default | Get or set the corpus settings |
settings.dfm | Get or set the corpus settings |
settings<- | Get or set the corpus settings |
show-method | corpus source classes |
show-method | print a dfm object |
show-method | print a dictionary object |
show-method | wordfish text model |
show-method | Wordscores text model |
similarity | compute similarities between documents and/or features |
similarity-method | compute similarities between documents and/or features |
skipgrams | Create ngrams and skipgrams |
skipgrams.character | Create ngrams and skipgrams |
skipgrams.tokenizedTexts | Create ngrams and skipgrams |
smoother | weight the feature frequencies in a dfm |
sort.dfm | sort a dfm by one or more margins |
stopwords | access built-in stopwords |
subset.corpus | extract a subset of a corpus |
summary.character | summarize a corpus or a vector of texts |
summary.corpus | summarize a corpus or a vector of texts |
syllables | count syllables in a text |
syllables.character | count syllables in a text |
syllables.tokenizedTexts | count syllables in a text |
t-method | Virtual class "dfm" for a document-feature matrix |
tail-method | Return the first or last part of a dfm |
tail.dfm | Return the first or last part of a dfm |
textfile | read a text corpus source from a file |
textfile-method | read a text corpus source from a file |
textmodel | fit a text model |
textmodel-method | fit a text model |
textmodel_ca | correspondence analysis of a document-feature matrix |
textmodel_fitted-class | the fitted textmodel classes |
textmodel_NB | Naive Bayes classifier for texts |
textmodel_wordfish | wordfish text model |
textmodel_wordfish_fitted-class | the fitted textmodel classes |
textmodel_wordfish_predicted-class | the fitted textmodel classes |
textmodel_wordscores | Wordscores text model |
textmodel_wordscores_fitted-class | the fitted textmodel classes |
textmodel_wordscores_predicted-class | the fitted textmodel classes |
texts | get corpus texts |
texts.character | get corpus texts |
texts.corpus | get corpus texts |
texts.corpusSource | get corpus texts |
texts<- | get corpus texts |
texts<-.corpus | get corpus texts |
tf | compute (weighted) term frequency from a dfm |
tf-method | compute (weighted) term frequency from a dfm |
tfidf | compute tf-idf weights from a dfm |
tfidf.dfm | compute tf-idf weights from a dfm |
tokenise | tokenize a set of texts |
tokenize | tokenize a set of texts |
tokenize.character | tokenize a set of texts |
tokenize.corpus | tokenize a set of texts |
toLower | Convert texts to lower case |
toLower.character | Convert texts to lower case |
toLower.corpus | Convert texts to lower case |
toLower.NULL | Convert texts to lower case |
toLower.tokenizedTexts | Convert texts to lower case |
topFeatures | list the most frequent features |
topfeatures | list the most frequent features |
topfeatures.dfm | list the most frequent features |
topfeatures.dgCMatrix | list the most frequent features |
trim | Trim a dfm using threshold-based or random feature selection |
trim-method | Trim a dfm using threshold-based or random feature selection |
trimdfm | Trim a dfm using threshold-based or random feature selection |
ukimmigTexts | Immigration-related sections of 2010 UK party manifestos |
weight | weight the feature frequencies in a dfm |
weight-method | weight the feature frequencies in a dfm |
wordlists | word lists used in some readability indexes |
wordstem | stem words |
wordstem.character | stem words |
wordstem.dfm | stem words |
wordstem.tokenizedTexts | stem words |
+-method | Virtual class "dfm" for a document-feature matrix |
+.corpus | constructor for corpus objects |
.stopwords | access built-in stopwords |
[-method | Virtual class "dfm" for a document-feature matrix |
[.corpus | constructor for corpus objects |
[[.corpus | constructor for corpus objects |
[[<-.corpus | constructor for corpus objects |