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
1 maintainer
Release files for Orange3-Textable 3.2.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| orange3_textable-3.2.7.tar.gz | 7.0 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| orange3_textable-3.2.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:7.2 MB
Release files / orange3_textable-3.2.7.tar.gz
| Download URL | orange3_textable-3.2.7.tar.gz |
|---|---|
| Size | 7.0 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.11
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Release files / orange3_textable-3.2.7-py3-none-any.whl
| Download URL | orange3_textable-3.2.7-py3-none-any.whl |
|---|---|
| Size | 205.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.11
|
