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Plotly is a technical computing company headquartered in Montreal, Quebec, that develops online data analytics and visualization tools. Plotly provides online graphing, analytics, and statistics tools for individuals and collaboration, as well as scientific graphing libraries for Python, R, MATLAB, Perl, Julia, Arduino, JavaScript [1] and REST.
MayaVi is a scientific data visualizer written in Python, which uses VTK and provides a GUI via Tkinter. MayaVi was developed by Prabhu Ramachandran, is free and distributed under the BSD License. It is cross-platform and runs on any platform where both Python and VTK are available (almost any Unix, Mac OS X, or Windows).
Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.
Visualization is an essential element of any Big Data and analytics strategy. The most up-to-date, real time information and advanced analytics soluti The 7 Best Data Visualization Tools For 2018
Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
VisTrails is a scientific workflow management system developed at the Scientific Computing and Imaging Institute at the University of Utah that provides support for data exploration and visualization. It is written in Python and employs Qt via PyQt bindings. The system is open source, released under the GPL v2 license.
Waikato Environment for Knowledge Analysis (Weka) is a collection of machine learning and data analysis free software licensed under the GNU General Public License.It was developed at the University of Waikato, New Zealand and is the companion software to the book "Data Mining: Practical Machine Learning Tools and Techniques".
It has a binding for Python. [1] Tulip is easy to use and offers very appealing visualization. [2] Initially, Tulip targeted only graph visualization. Since then, it has evolved to be a more general-purpose data visualization software. Tulip can work with very huge data sets, e.g. 1,000,000 nodes and 5,000,000 edges. [3]