orange Alternatives - Python Science and Data Analysis

Popularity

7.4

Growing

Activity

9.7

Stable

Stars 1,874

Watchers 155

Forks 542

Last Commit about 2 months ago

Description

This is a development version of Orange 3. The stable version 2.7 is still available (binaries and sources).

Code Quality Rank: L2

Programming language: Python

License:

Tags: Science And Data Analysis Scientific Engineering Visualization Artificial Intelligence

orange alternatives and similar packages

Based on the "Science and Data Analysis" category

Pandas

9.8 9.9 L2 orange VS Pandas

A library providing high-performance, easy-to-use data structures and data analysis tools.
NumPy

9.6 9.8 L1 orange VS NumPy

A fundamental package for scientific computing with Python.
SciPy

9.4 9.8 L2 orange VS SciPy

A Python-based ecosystem of open-source software for mathematics, science, and engineering.
SymPy

9.3 10.0 L2 orange VS SymPy

A Python library for symbolic mathematics.
NetworkX

9.2 8.6 L3 orange VS NetworkX

A high-productivity software for complex networks.
statsmodels

8.9 9.7 L3 orange VS statsmodels

Statistical modeling and econometrics in Python.
PyMC

8.7 9.2 L4 orange VS PyMC

Markov Chain Monte Carlo sampling toolkit.
Dask

8.5 9.5 L2 orange VS Dask

Versatile parallel programming with task scheduling
Numba

8.5 9.8 L3 orange VS Numba

Python JIT (just in time) compiler to LLVM aimed at scientific Python by the developers of Cython and NumPy.
astropy

8.0 9.8 L2 orange VS astropy

A community Python library for Astronomy.
Biopython

7.8 9.6 L2 orange VS Biopython

Biopython is a set of freely available tools for biological computation.
blaze

7.8 2.5 L4 orange VS blaze

NumPy and Pandas interface to Big Data.
Interactive Parallel Computing with IPython

7.0 5.4 L3 orange VS Interactive Parallel Computing with IPython

Interactive Parallel Computing in Python
Cubes

6.1 3.4 L3 orange VS Cubes

Light-weight Python OLAP framework for multi-dimensional data analysis
Open Mining

5.8 0.0 L3 orange VS Open Mining

Business Intelligence (BI) in Python (Pandas web interface)
RDKit

5.4 9.0 L1 orange VS RDKit

Cheminformatics and Machine Learning Software.
bcbio-nextgen

5.4 9.3 L3 orange VS bcbio-nextgen

A toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis.
NIPY

5.1 9.2 L3 orange VS NIPY

A collection of neuroimaging toolkits.
bcolz

4.7 4.0 orange VS bcolz

A columnar data container that can be compressed.
bccb

4.5 5.1 L4 orange VS bccb

Collection of useful code related to biological analysis.
Neupy

4.3 8.6 L5 orange VS Neupy

Running and testing different Artificial Neural Networks algorithms.
Bubbles

3.6 0.0 L5 orange VS Bubbles

A Python ETL framework
PyDy

2.9 6.0 L3 orange VS PyDy

Short for Python Dynamics, used to assist with workflow in the modeling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.
harold

1.7 7.8 L2 orange VS harold

An MIT licensed systems and controls toolbox for Python.
signac

1.0 8.5 orange VS signac

Manage large and heterogeneous data spaces on the file system.
cclib

0.9 2.1 orange VS cclib

A library for parsing and interpreting the results of computational chemistry packages.
dask-memusage

0.5 3.2 orange VS dask-memusage

A low-impact profiler to figure out how much memory each task in Dask is using
Open Babel

- - orange VS Open Babel

A chemical toolbox designed to speak the many languages of chemical data.

* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest. Visit our partner's website for more details.

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README

Orange

Orange is a component-based data mining software. It includes a range of data visualization, exploration, preprocessing and modeling techniques. It can be used through a nice and intuitive user interface or, for more advanced users, as a module for the Python programming language.

This is the latest version of Orange (for Python 3). The deprecated version of Orange 2.7 (for Python 2.7) is still available (binaries and sources).

Installing with Miniconda / Anaconda

Orange requires Python 3.6 or newer.

First, install Miniconda for your OS. Create virtual environment for Orange:

conda create python=3 --name orange3

In your Anaconda Prompt add conda-forge to your channels:

conda config --add channels conda-forge

This will enable access to the latest Orange release. Then install Orange3:

conda install orange3

To install the add-ons, follow a similar recipe:

conda install orange3-<addon name>

See specific add-on repositories for details.

Installing with pip

To install Orange with pip, run the following.

# Install some build requirements via your system's package manager
sudo apt install virtualenv build-essential python3-dev

# Create a separate Python environment for Orange and its dependencies ...
virtualenv --python=python3 --system-site-packages orange3venv
# ... and make it the active one
source orange3venv/bin/activate

# Install Qt dependencies for the GUI
pip install PyQt5 PyQtWebEngine

# Install Orange
pip install orange3

Starting Orange GUI

To start Orange GUI from the command line, run:

orange-canvas
# or
python3 -m Orange.canvas

Append --help for a list of program options.

orange

Data mining, data visualization, analysis and machine learning through visual programming or Python scripting.