Top 5 of the Best Free Python Dataviz Tools

If you need to make your data meaningful at first glance, and you know a bit of Python language, then you should look for the right Python DataViz tool to use.

Python is a powerful object-oriented programming language. According to wikipython.org, it is easy to learn and easy to use which makes it ideal for prototype development and ad hoc programming tasks.

It is very easy to extend the existing functionalities of Python. How? Thanks to what is called the “libraries” that help the developer work on particular projects. Several libraries can be installed, for example, to develop data visualization tools in Python.

Exhibit your scientific data to the community is elementary. You might want to design a nice infographic easily for your transcriptome or your biomedical data with one of the following Python DataViz tools!

Seaborn

Online tool • For univariate or bivariate distribution visualization • Made in • Free

Source: Scatterplot matrix from Seaborn gallery

Seaborn is a Python visualization library. It enables to visualize the distribution of a data set by plotting univariate or bivariate distributions and also visualizing pairwise relationships in the data set.

It provides functions to draw linear regression models or to fit different kinds of other models. It is also possible to control the size and shape of the plot.

Seaborn allows statistical estimation within categories, plotting “wide-form” data and drawing multi-panel categorical plots.

It enables to plot with categorical data, like categorical scatterplots. There are a lot of different examples in their gallery.

EOMYS engineering

Online tool • For__computing, applied mathematics, and engineering • Made in France

EOMYS is a French company that provides engineering consultancy and research services applied to innovative multiphysics systems or processes.

EOMYS allows implementation of simulation models, with Python among others, based on technical articles. They develop high-performance models and they can optimize system design. They also offer concept development and virtual prototyping.

VisPy

Online tool • For 2D/3D interactive scientific-oriented visualization • Made in USA • Free

VisPy is a Python library for scientific visualization which enables interactive visualization. It is designed to be fast, scalable, and easy to use.

More precisely, it is a high-performance interactive 2D/3D data visualization library. It works through the OpenGL library to display very large data sets.

This tool is for scientists who are seeking a high-level, high-performance plotting toolkit. And also more experimented users knowing OpenGL, or willing to learn OpenGL, and want to create interactive 2D/3D visualizations in Python.

PyQtGraph

Online tool • For mathematics, medical, and engineering applications • Made in the USA • Free

PyQtGraph is a python graphics and GUI library. It is intended for use for mathematics and engineering applications. PyQtGraph is distributed under the MIT open-source license.

Its features include basic 2D plotting in interactive view boxes such as line and scatter plots. It displays images with interactive lookup tables and level control with functions for slicing multidimensional images at arbitrary angles and rapid update for video display or real-time interaction.

It also provides 3D graphics system including interactive viewports rotate and zoom with your mouse and basic 3D scenegraph for easier programming. PyQtGraph allows for creating 2D and 3D graphics.

And there is an accessible library of widgets and modules useful for science/engineering applications. Modules such as a flowchart widget for interactive prototyping and multi-process control allowing remote plotting.

Missingno

Online tool • For datasets with missing values • Made in the UK • Free

If you have messy datasets or missing values, Missingno provides a small toolset of flexible and easy-to-use missing data visualizations. It also allows you to get a quick visual summary of the completeness of your data set, or the lack of it.

There are several visualization possibilities from bar charts to matrix and also dendrograms.

One of them is the heat map that you can see after. It enables you to know how strongly the presence of one variable positively or negatively affects the presence of another.