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biolab/orange3

Orange is an open-source visual programming tool for data mining, analysis and visualization, built around drag-and-drop workflows.

Open-source alternative to:TableauKNIME

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What is it?

Orange is a data mining and visualization toolbox aimed at both novices and experts. Users build analysis pipelines by connecting interactive widgets on a canvas, so exploring data does not require writing code or deep mathematical background.

The core package covers common data science tasks such as loading and preprocessing tables, classification, regression, clustering, and interactive plotting. It is written in Python and built on libraries like NumPy, pandas and scikit-learn. Installers are provided for Windows and macOS, while Linux users can install through conda, pip or uv.

Functionality can be extended with add-ons. The project lists first-party add-ons for text mining, bioinformatics, time series, single-cell analysis, image analytics, geographic data, association rules, networks and model explanation.

Key features

  • 01Drag-and-drop visual workflows built from interactive widgets.
  • 02Built-in tools for classification, regression and clustering.
  • 03Interactive data visualization and exploration.
  • 04Installers for Windows and macOS, and installation via conda, pip or uv on Linux.
  • 05Extensible through a add-on system with domain-specific widgets.

Use cases

  • Exploring a new tabular dataset without writing code.
  • Teaching data mining and machine learning concepts visually.
  • Prototyping a classification or regression pipeline before scripting it.
  • Analyzing domain data such as text, bioinformatics or time series with dedicated add-ons.

Quick start

  1. 1

    Create and activate a virtual environment

  2. 2

    Install Orange with pip

    pip install PyQt6 PyQt6-WebEngine orange3
  3. 3

    Run Orange (the first launch may be slow)

    python -m Orange.canvas

Things to know

  • The license is not clearly identified in the project metadata.
  • Installing with pip may require a C/C++ compiler, and Windows users are advised to use the standalone installer or conda instead.
  • The first launch can take a long time.

In collections

Data science courses & tools

Topics

#data-mining#visual-programming#machine-learning#data-visualization#python#scikit-learn#no-code#classification#clustering#data-science

FAQ

What is orange3?
Orange is an open-source visual programming tool for data mining, analysis and visualization, built around drag-and-drop workflows. Orange is a data mining and visualization toolbox aimed at both novices and experts. Users build analysis pipelines by connecting interactive widgets on a canvas, so exploring data does not require writing code or deep mathematical background.
Is orange3 free to use? What license does it have?
orange3 is open source under the Other license. Check the license terms before using it in commercial products.
Is orange3 still maintained?
Actively maintained. The last commit to orange3 was on Nov 6, 2026.
What can I use orange3 for?
Exploring a new tabular dataset without writing code. Teaching data mining and machine learning concepts visually. Prototyping a classification or regression pipeline before scripting it. Analyzing domain data such as text, bioinformatics or time series with dedicated add-ons.
How do I install orange3?
Create and activate a virtual environment Install Orange with pip: pip install PyQt6 PyQt6-WebEngine orange3 Run Orange (the first launch may be slow): python -m Orange.canvas
Where can I get orange3?
The source code and installation instructions are on GitHub: https://github.com/biolab/orange3

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