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-3.1.0b2.tar.gz (144.8 kB view details)

Uploaded Source

Built Distribution

Orange3_Textable-3.1.0b2-py3-none-any.whl (187.7 kB view details)

Uploaded Python 3

File details

Details for the file Orange3-Textable-3.1.0b2.tar.gz.

File metadata

File hashes

Hashes for Orange3-Textable-3.1.0b2.tar.gz
Algorithm Hash digest
SHA256 cef2d975e8ef6e7149b83caddcc1445871f2aa3c548ac9d1c85ba406dcd8e9c6
MD5 2b65d94ceda7f67362cc9dd4f18b5393
BLAKE2b-256 f7750bbf1efcb050d3aecd6b04648d50e59289032eb201dc3e8729c083b50391

See more details on using hashes here.

File details

Details for the file Orange3_Textable-3.1.0b2-py3-none-any.whl.

File metadata

File hashes

Hashes for Orange3_Textable-3.1.0b2-py3-none-any.whl
Algorithm Hash digest
SHA256 f995fde78b5e0ff1a934768dc5c0853429f049dbef248aa8d48eef90f56f70d5
MD5 e6a175139701116fa76ce6a17bf47f08
BLAKE2b-256 69b5cda8cf4715d7ec144942b7760ef04fdc9d4c48fc2c891ff64312db2d1c9a

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