Python Based Data Visualisation Tools

6 Best Python Data Visualization Tools

Data visualization is the process of displaying data sets with the help of a graphical representation. Data visualization

Data visualization is the process of displaying data sets with the help of a graphical representation. Data visualization tools map data values and graphics to give its users a clearer idea about the data sets.

Why Python?

Python-based systems offer various graphing libraries that help the data analysts to create live, interactive and highly customized data graphs. It helps them to represent different data sets and their relations visually.

We will be looking at some of the best Python based data visualization tools in this blog.

List of Best Python-based Data Visualization Tools

When it comes to Python-based data visualization tools, we can categorize them on the basis of the systems they use.

Matplotlib

Matplotlib is considered as the pioneer of data visualization tools. John Hunter created it with the help of many other scientists over a period of years. You can represent very complex data relations with ease in Matplotlib. It is an open-source system, which has helped a lot of other data visualization tools.

You can have four graphical user interface tool kits that you can use through web application servers, Jupyter notebook, and Python scripts. You can also create histograms, bar charts, error charts, and power spectra.

It is one of the most powerful data visualization tool, but it has a very complex process to generate these graphs in Matplotlib. It involves a lot of backend coding, which is somewhat time-consuming.

Pandas

Pandas has the same abilities as the Matplotlib tool as it uses Matplotlib’s open-source system. Pandas gives you the flexibility to perform complex programming to generate plots with relative ease.

This data visualization tool gives you a lot of options to show your creativity and represent the data in various forms. You can save a lot of effort and time with Pandas as it involves less coding than that in Matplotlib.

Javascript based python data visualization tools:

Plotly

Plotly is a javascript based data visualization tool. It also offers an online platform for data visualization. Plotly offers one of the most interactive interface to its users. You can also create some unique charts like dendrograms, 3D charts, and contour plots, which you cannot generate through most of the other tools.

OpenGL based Python Data Visualization Tools:

Vispy

Vispy is one of the best OpenGL based tools, and it offers very high speed that helps its users to generate graphs pretty quickly. Its ability to perform cross-platform integration is also commendable.  As it is an open-source tool, you can easily customize it as per your requirements.

d3js based Python Data Visualization Tools:

Altair

Altair offers declarative stats visualization library. It is a d3js based data visualization tool. It has a simple, user-friendly, and easy to customize API.

As it consists of a declarative library, you just need to develop the relationship between the data sets and coding channels once, and the plotting is handled automatically for the rest of the instances. This means you don’t have to perform a lot of hard coding to generate attractive graphs.

Other essential Python Data Visualization Tool:

MayaVi

MayaVi is a 3D visualization tool that has a strong graphical user interface. You can easily customize the graphs with the help of Python importer. Its latest version does not focus on the 3D plotting only, but it also offers interactive programs.

MayaVi also supports PLOT3D data, and you can use multiple datasets simultaneously to generate different data visualization parameters. You can also create custom modules and data filters as per your requirement pretty easily through MayaVi.

MayaVi is a free software license that comes under the BSD license category.

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