The libraries and toolkits discussed in this article can be used for rendering dynamic plot on desktop, mobile and web-based platforms so that a quick summary of results can be presented. These tools can be used by data scientists and researchers for an effective analysis of dynamic data.
But, before moving on to these tools/libraries, let's look at some obvious points!
The key features and characteristics that are directly related to effective visualisation and plotting cab be as follows:
- Free and Open Source without any licensing issues.
- Support for assorted web standards.
- Animated charts and plots for better analysis of data.
- Integrated wizards and template.
- Data imports from multiple sources.
- Integration of APIs to 3rd party channels.
- Responsive outputs.
- Multi-color plots with multiple dimensional views.
The real-world scenarios of desktop and web-based applications need different types of visual components so that the application can be built with a user-friendly interface.
A few scenarios where the need comes up for plotting, visualisation and dynamic graphs in software applications can be as follows:
- Real-time maps and street views for mobile app-based delivery systems.
- Dynamic graphs and plots for predictions (for stock-market, e-governance and weather forecasting).
- Knowledge discovery and predictive mining (for learning time series).
The hunt for data visualisation tools that can present huge data sets on web-based platforms can be tedious since a number of software frameworks and tools are available for plotting data and for the dynamic graph generation.
In this article, we will cover the free and open-source resources that can be used for the visualisation of big data sets.
Candela supports assorted plots and graphical segments, including
ScatterPlotMatrix and many more, using which easily understandable plots can be generated.
The key goal of this platform is to provide the maximum capability of the current browser, including strong viewing components and an approach focused on the DOM without a proprietary system.
Datawrapper is an open-source data visualisation tool for anyone to create easy, realistic and embeddable charts quickly. This platform is available in both free and premium segments. The free version of Datawrapper is very powerful and has a huge number of features.
The leaflet library is built to be quick, powerful and user-friendly for data scientists and researchers. It runs easily across all major desktop and mobile platforms and can be expanded with several plugins. It has an easy-to-use and well-documented API and easy-to-read source code so that advanced data science applications can be worked out.
A number of dynamic graphs and maps can be generated by the leaflet with the OpenStreetMap so that real-time locations and positions can be plotted on different types of display devices.
Sigma works as a rendering engine in which the data sets can be linked and real-time graphs and networks can be plotted for multiple applications, including social network analysis, wireless networks, street maps and many others.
Well, that's it from me.
Let me know in the comments, what are all the libraries you have used and which is your favourite.
Just starting your Open Source Journey? Don't forget to check Hello Open Source
Need inspiration or a different perspective on the Python projects or just out there to explore? Check Awesome Python Repos
Want to make a simple and awesome game from scratch? Check out PongPong
++your GitHub Profile README? Check out Quote - README
Till next time!
Interested in reading more such articles from Siddharth Chandra?
Support the author by donating an amount of your choice.
Awesome article, there are so many libraries out there, one just does not know which to use. Better to stick to 2-3 or just use depending on the use case.