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https://github.com/biolab/orange3

🍊 :bar_chart: :bulb: Orange: Interactive data analysis
https://github.com/biolab/orange3

classification clustering data-mining data-science data-visualization decision-trees machine-learning numpy orange orange3 pandas plotting python random-forest regression scikit-learn scipy visual-programming visualization

Last synced: 4 months ago
JSON representation

🍊 :bar_chart: :bulb: Orange: Interactive data analysis

Host: GitHub
URL: https://github.com/biolab/orange3
Owner: biolab
License: other
Created: 2013-02-22T12:52:56.000Z (over 11 years ago)
Default Branch: master
Last Pushed: 2024-03-11T11:46:59.000Z (4 months ago)
Last Synced: 2024-03-11T12:39:45.799Z (4 months ago)
Topics: classification, clustering, data-mining, data-science, data-visualization, decision-trees, machine-learning, numpy, orange, orange3, pandas, plotting, python, random-forest, regression, scikit-learn, scipy, visual-programming, visualization
Language: Python
Homepage: https://orangedatamining.com
Size: 95.6 MB
Stars: 4,543
Watchers: 181
Forks: 970
Open Issues: 115
Metadata Files:
- Readme: README-dev.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Roadmap: ROADMAP.md

Lists

awesome-python-applications - Repo - based data mining software for graphical interactive data analysis and visualization. `(linux, windows, mac, qt4, qt5)` (<a id="tag-science" href="#tag-science">Science</a>)
awesome-stars - biolab/orange3
awesome-python-application - Repo - based data mining software for graphical interactive data analysis and visualization. `(linux, windows, mac, qt4, qt5)` (<a id="tag-science" href="#tag-science">Science</a>)
awesome-python-applications - Repo - based data mining software for graphical interactive data analysis and visualization. `(linux, windows, mac, qt4, qt5)` (<a id="tag-science" href="#tag-science">Science</a>)
awesome-stars - biolab/orange3 - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis (Python)
awesome-stars - biolab/orange3 - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis (Python)
awesome-python-applications - Repo - based data mining software for graphical interactive data analysis and visualization. `(linux, windows, mac, qt4, qt5)` (<a id="tag-science" href="#tag-science">Science</a>)
awesome-stars - orange3 - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis https://orange.biolab.si (Python)
awesome-python-machine-learning - Orange - Orange is a component-based data mining software. It includes a range of data visualization, exploration, preprocessing and modeling techniques. (Uncategorized / Uncategorized)
awesome-stars - orange3
awesome-python-applications - Repo - based data mining software for graphical interactive data analysis and visualization. (<a id="tag-science" href="#tag-science">Science</a>)
awesome-stars - biolab/orange3 - `★4669` 🍊 :bar_chart: :bulb: Orange: Interactive data analysis (Python)
awesome-starred - biolab/orange3 - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis (scikit-learn)
awesome-stars - biolab/orange3 - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis (Python)
my-awesome-stars - biolab/orange3 - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis (Python)
awesome-stars - biolab/orange3 - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis (Python)

README

        Orange development

==================

The source code of [Orange] is versioned in [Git] and hosted on [GitHub]. 

If you want to contribute to this open-source project you will have to use git. However, for minor experimentation with the source code you can also get by without. 

[Orange]: https://orange.biolab.si/

[Git]: https://git-scm.com/

[GitHub]: https://github.com/biolab/orange

Prerequisites

-------------

[Orange] is written mostly in Python, therefore you'll need [Python 3] version 3.6 or newer.

You will also need a C/C++ compiler. On Windows, you can get one by installing [Visual Studio].

A slightly more "minimalistic" option is to install only its [Build Tools].

[Python 3]: https://www.python.org

[Visual Studio]: https://visualstudio.microsoft.com/vs/

[Build Tools]: https://visualstudio.microsoft.com/visual-cpp-build-tools/

Source code

-----------

Get the source code by cloning the git repository

    git clone https://github.com/biolab/orange3.git

or, alternatively, download and unpack the [ZIP archive] of the source code from [GitHub].

[ZIP archive]: https://github.com/biolab/orange3/archive/master.zip

Building

--------

Consider using virtual environments to avoid package conflicts. 

Install the required Python packages

    pip install -r requirements.txt

    

and run the setup script with a development option, which will link to the source code instead of creating a new package in Python's site-packages.

    python setup.py develop

    

Verify the installation by importing the Orange package from Python and loading an example Iris dataset.

    >>> import Orange

    >>> print(Orange.data.Table("iris")[0])

    [5.1, 3.5, 1.4, 0.2 | Iris-setosa]

Using the graphic user interface requires some additional packages.

    pip install -r requirements-gui.txt

To start Orange GUI from the command line, run:

    python3 -m Orange.canvas

Contributing

------------

If you've made improvements that you want to contribute, you'll need your own fork of the [GitHub] repository. After committing and pushing changes to your fork, you can create a pull request. We will review your contribution and hopefully merge it after any potential corrections. 

You can view the list of open [pull requests] and known [issues] on GitHub.

[pull requests]: https://github.com/biolab/orange3/pulls

[issues]: https://github.com/biolab/orange3/issues