_pkgdown.yml

url: https://quanteda.io
template:
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    bootswatch: readable
    ganalytics: UA-144616-24
    docsearch:
      api_key: 9b4ef7fd791dc6075154d3ebd7b12acf
      index_name: quanteda
news:
- one_page: false
navbar:
  title: "Quanteda"
  type: inverse
  left:
    - text: "Quick Start"
      menu:
        - text: "Quick Start Guide"
          href: articles/quickstart.html
        - text: "Guía de Inicio Rápido"
          href: articles/pkgdown/quickstart_es.html
        - text: "快速入门指南"
          href: articles/pkgdown/quickstart_cn.html
        - text: "クイック・スタートガイド"
          href: articles/pkgdown/quickstart_ja.html
        - text: "त्वरित आरंभ "
          href: articles/pkgdown/quickstart_hi.html
    - text: "Reference"
      href: reference/index.html
    - text: "Features"
      menu:
        - text: "Feature comparison"
          href: articles/pkgdown/comparison.html
        - text: "Package design"
          href: articles/pkgdown/design.html
        - text: "Changelog"
          href: news/index.html
    - text: "Examples"
      menu:
        - text: "Multi-word expressions"
          href: articles/pkgdown/examples/phrase.html
        - text: "Textual data visualization"
          href: articles/pkgdown/examples/plotting.html
        - text: "Latent Semantic Analysis (LSA)"
          href: articles/pkgdown/examples/lsa.html
        - text: "Chinese text analysis"
          href: articles/pkgdown/examples/chinese.html
        - text: "Social media analysis"
          href: articles/pkgdown/examples/twitter.html
    - text: "Replications"
      menu:
        - text: "Text Analysis with R for Students of Literature"
          href: articles/pkgdown/replication/digital-humanities.html
        - text: "Word embedding (word2vec)"
          href: articles/pkgdown/replication/text2vec.html
        - text: "Quantitative Social Science Ch. 5.1"
          href: articles/pkgdown/replication/qss.html
  right:
    - icon: fa-github fa-lg
      href: https://github.com/quanteda/quanteda
reference:
- title: Package-level
  contents:
    - quanteda
    - quanteda_options
- title: Data
  desc: Built-in data objects.
  contents:
    - data_char_sampletext
    - data_char_ukimmig2010
    - data_corpus_inaugural
    - data_dfm_lbgexample
    - data_dictionary_LSD2015
    - data-relocated
- title: Corpus functions
  desc: Functions for constructing and manipulating corpus class objects.
  contents:
    - starts_with("corpus")
    - docvars
    - as.character.corpus
- title: Tokens functions
  desc: Functions for constructing and manipulating tokens class objects.
  contents:
    - starts_with("tokens")
    - types
    - as.character.tokens
    - as.list.tokens
    - as.tokens
    - is.tokens
- title: Character functions
  desc: Functions for constructing and manipulating character objects.
  contents:
    - char_tolower
    - char_toupper
    - char_segment
    - char_ngrams
    - char_select
    - char_trim
    - char_wordstem
- title: Text matrix functions
  desc: Functions for constructing and manipulating a document-feature matrix (dfm) or feature co-occurrence matrix object.
  contents:
    - starts_with("dfm")
    - docfreq
    - featfreq
    - head.dfm
    - tail.dfm
    - as.dfm
    - is.dfm
    - as.data.frame.dfm
    - as.matrix.dfm
    - starts_with("fcm")
    - as.fcm
    - is.fcm
- title: Dictionary functions
  desc: Constructor and utility functions for working with dictionaries.
  contents:
    - dictionary
    - is.dictionary
    - as.yaml
- title: Phrase discovery functions
  desc: Functions for exploring and detecting keywords and phrases.
  contents:
    - is.collocations
    - is.kwic
    - kwic
- title: Utility functions
  desc: R-like functions to return counts and object information.
  contents:
    - index
    - ndoc
    - nfeat
    - nsentence
    - ntoken
    - ntype
    - print-methods
    - starts_with("docnames")
    - featnames
- title: Miscellaneous functions
  contents:
    - phrase
    - convert
    - bootstrap_dfm
    - meta
    - readtext-methods
    - spacyr-methods
- title: Statistics, models, and plots
  desc: Functions for computing statistics, fitting models, and producing visualisations models from text.
  contents:
    - sparsity
    - topfeatures
    - textmodels
    - textplots
    - textstats