Skip to main content

Textable add-on for Orange 3 data mining software package.

Project description

Textable is an open source add-on bringing advanced text-analytical functionalities to the Orange Canvas data mining software package (itself open source). Look at the following example to see it in typical action.

The project’s website is http://textable.io. It hosts a repository of recipes to help you get started with Textable.

Documentation is hosted at http://orange3-textable.readthedocs.io/ and you can get further support at https://textable.freshdesk.com/ or by e-mail to support@textable.io

Orange Textable was designed and implemented by LangTech Sarl on behalf of the department of language and information sciences (SLI) at the University of Lausanne (see Credits and How to cite Orange Textable).

Features

Basic text analysis

  • use regular expressions to segment letters, words, sentences, etc. or full-text query

  • use regexes to extract annotations from many input formats

  • import in-line XML markup (e.g. TEI)

  • include/exclude segments based on user-defined lists (stoplists)

  • filter segments based on frequency

  • easily generate random text samples

Advanced text analysis

  • concordances and collocations, also based on annotations

  • segment distribution, document-term matrix, transition matrix, etc.

  • co-occurrence tables, also between different types of segments

  • lemmatization and POS-tagging via Treetagger

  • robust linguistic complexity measures, incl. mean length of word, lexical diversity, etc.

  • many advanced data mining algorithms: clustering, classification, factor analyses, etc.

Text recoding

  • Unicode-aware preprocessing functions, e.g. remove accents from Ancient Greek text

  • recode and restructure texts using regexes, e.g. rewrite CSV as XML

Extensibility

  • handles hundreds of text files

  • use Python script for custom text processing or to access external tools: NLTK, Pattern, GenSim, etc.

Interoperability

  • import text from keyboard, files, or URLs

  • process any kind of raw text format: TXT, HTML, XML, CSV, etc.

  • supports many text encodings, incl. Unicode

  • export results in text files or copy-paste

  • easy interfacing with Orange’s Text Mining add-on

Ease of access

  • user-friendly visual interface

  • ready-made recipes for a range of frequent use cases

  • extensive documentation

  • support and community forums

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Orange3-Textable-3.1.0a0.tar.gz (144.0 kB view details)

Uploaded Source

Built Distribution

Orange3_Textable-3.1.0a0-py3-none-any.whl (186.5 kB view details)

Uploaded Python 3

File details

Details for the file Orange3-Textable-3.1.0a0.tar.gz.

File metadata

File hashes

Hashes for Orange3-Textable-3.1.0a0.tar.gz
Algorithm Hash digest
SHA256 aa7492e2c06fcb5c35370067f533c8195539f78013384c81f45fda6abfe5e0d5
MD5 c4ef4aed9d97a4dec16de9242f2edb6a
BLAKE2b-256 dc0fefbe3af29a0b2ffc24dbfe1dc93580f1758e479a7a0e66400dfb33bd088c

See more details on using hashes here.

File details

Details for the file Orange3_Textable-3.1.0a0-py3-none-any.whl.

File metadata

File hashes

Hashes for Orange3_Textable-3.1.0a0-py3-none-any.whl
Algorithm Hash digest
SHA256 0f2e12f42fae884a1107b4520fa2e5c378c308852af46482fe11ff8430ca02a5
MD5 be19f6135baa5efda8ed5e04922562c4
BLAKE2b-256 ca932b0d37b3e3c87f96f8543451b5362a287c5cdae523b81459e1e9248ed46c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page