Programming for visualization involves the use of computer programs to create visual representations that aid users to comprehend the meaning of data. This is an excellent technique for data scientists that are looking to make their research findings easier to digest.
The best programming language for visualization depends on various factors, including the level of programming experience you have as well as the type and quantity of customization you require, and your desired visualization. There are a variety of languages that are renowned for their ability to produce high-quality visualizations, but the choice should be made according to your requirements.
Python is a widely used and versatile programming language that is suitable for any project involving data visualization. It is easy to learn and has an extensive developer community. It is fast and can handle huge amounts of data. Its ability to manipulate data makes it an excellent option for creating complex graphs, charts and interactive applications.
There are many Python libraries that enable users to create a range of different types of visualizations such as pie charts, bar charts scatterplots, histograms sparklines and contour plots. Some of these libraries even offer support for data visualization with SVG.
Polymaps provides a variety of styles for maps and is user-friendly. It is simple to use and comes with various styles for maps. It uses SVG for the maps. This lets you customize colors and appearance.
Polymaps also comes as an iOS app that can help you with your project of data visualization. Its ability to import and export data from any source is a further benefit.
ChartBlocks is a great tool for creating responsive charts from any source, including live feeds. It lets you make extensive adjustments of the final visualization and comes with a built-in chart building wizard to help you select the most appropriate data for your project.
ChartBlocks is a powerful charting tool but it also has an easy user interface for beginners. The app includes extensive support for ReactJS, React Native and other cross-platform technologies.
VictoryJS is a well-known visualization library which uses ReactJS to create an efficient, scalable solution for visualizing data. It also provides special support for modular charts.
It is a free open-source framework that allows you to create interactive web-based visualizations. It also supports React Native and can be integrated into your website or mobile application to give you the ability to add interactive elements to your pages without having to install a separate app.
Matlab is a physics and engineering-focused programming language that is well suited for numerical computations, which includes data visualization. It is taught in undergraduate courses that cover a wide variety of subjects, including electrical engineering and biology.