The use of computer programs to create visual representations helps viewers and users to comprehend data. This is a useful technique for data scientists who want to present the results of their research in a way that is more digestible.
Choosing the appropriate programming language
The best programming language to create visualizations depends on several aspects such as your experience level with programming and the type of visualization you’d like to create and the amount of customization that you require. There are many languages that are renowned for their ability to create high-quality visualizations, but the choice should be made according to your needs.
R, Python and JavaScript are popular languages that are commonly used in data visualization. Each of these languages has pros and cons.
Python is a versatile and widely used programming language. It is a great choice for any project that requires data visualisation. It is a breeze to learn and has a large developer community. It is fast and can handle huge amounts of data. Its ability to do manipulation of data makes it a great option to create complex graphs and charts as well as interactive apps.
There are a variety of Python libraries that enable users to create a range of different types of visualizations such as bar charts, pie charts scatterplots, histograms contour plots and sparklines. Some of these libraries provide the ability to visualize data using SVG.
If you’re company website interested in using SVG to visualize your data, Polymaps is an excellent choice. It offers a wide selection of styles for maps and is simple to use. It makes use of SVG for the maps. This allows you to modify colors and the appearance.
Polymaps is also available as an iOS app that can help you with your visualization of data. Its ability to import or export data from any source is a further advantage.
ChartBlocks allows you to create responsive charts using any data source, including real-time feeds. It permits for extensive customization of the final visualisation and comes with a built-in chart building wizard to help you select the most appropriate data for your project.
In addition to being a robust charting tool, ChartBlocks also has an intuitive interface that makes it simple for novices to start. The app includes extensive support for ReactJS, React Native and other cross-platform technologies.
VictoryJS is a different popular visualization library that uses ReactJS to create an efficient and scalable solution for data visualizations. It also offers special support for modular charts.
It is a completely free, open-source framework for creating interactive web-based visualizations. It can also be integrated into your website or mobile app to allow users to include interactive elements without having to install a separate application.
Matlab is a programming language targeted towards physics and engineering. It is especially well-suited for numerical computations including visualization of data. It is taught in undergraduate classes that cover a wide variety of subjects, including electrical engineering and biology.