How to Visualise Your Data: 7 Top Libraries


When working with data science and choosing a charting tool for analytics, you should take into account few important factors. In this article, we will go through seven popular charting tools for web developers to let you quit fighting with large amounts of data and begin to chart.

It’s extremely difficult to manually reach the necessary quality of data visualization, especially if it means staring at columns of numerous figures in spreadsheets which might be the most unattractive way of work ever.

Web programmers usually avoid using spreadsheets in their practice. But they no longer need to since there are many more efficient solutions for this purpose and the static Excel graph stopped being the only alternative. A boom in the number of accessible information sources and data processing instruments results in growing number of IT specialists who work with data visualization tasks. However, with such a long way to go, it can be hard to learn exactly where to begin. Let’s consider the pros and cons of each library.


D3 is obviously the most widespread and popular data visualization library. D3 stands for Data Driven Documents. It’s an open source JavaScript library normally used to create SVG images. SVG is a well-known and rarely used vector picture format. The popularity of this image format continuously grows since vector graphics can be zoomed in without any damage to the image quality. That’s why it looks perfect even on large high-resolution displays, such as Apple Retina.

It’s hard to find that kind of programming library which would be able to compete with D3 in terms of data visualization in SVG format.

Many web developers also use other libraries based on D3, such as NVD3. This solution offers instant and adaptable standard diagram components. Another example of D3-based projects is Crossfilter which is a great data filtering engine. D3 is a great tool, and its advantage is that it supports all capabilities of new web browsers.

If, however, web client doesn’t leverage some feature, e.g. 3D rendering with WebGL, this library will not be able to leverage it either.

Since D3 is a multipurpose programming library, it’s not that good for everything as it could be. The main con of this library is that it doesn’t set or even advise any visual representation. It’s mostly an instrument for transmitting data to the web browser and creating DOM elements.


While D3 is an intense instrument for custom visuals, Vega is a programming library that can come in handy when you need to make a standard graph without paying much attention to how it should look. Being based on D3, Vega offers a syntax for characterizing diagram components.

When using Vega, you can create JSON-based data visualization descriptions instead of generating JavaScript code as in the case with D3. After that, you can create interactive views with SVG or HTML5 Canvas. This will help you significantly facilitate the task by allowing you to write a simpler code. Therefore, you will spend much less time on visualizing your data. This greatly improves the platform flexibility and let you reuse and share your visualizations.

The main drawback of Vega, however, is that it’s hard to create customizable visualization when using this library. It would be better to use D3 for that purpose.


Processing is a tool for visualization of data that has been already in existence for a couple of years. One of the main benefits of Processing is that it can be easily deployed on any platform. It provides a simple syntax which allows creating nice charts with a single line of code. In fact, it’s a simple programming environment that allows web developers quickly generate well-designed and interactive graphs.

Processing.js is a Processing-based solution that lets web developers generate charts utilizing web standards without any additional modules. This library doesn’t use JS – it uses its own syntax instead. To visualize data with Processing.js, you should create a corresponding command and then paste it to a necessary web page.

The main drawback of Processing is that it’s not gonna work when working on complex tasks since its integrated development environment has not that wide functionality compared to D3.

With many community members and ease of use, Processing seems to be an effective tool for non-complex projects especially when time really matters.


While both Processing and D3 are multipurpose instruments that can be used for different data virtualization tasks, Gephi is aimed at specific tasks. It’s a free open source programming library for network visualization. If you need to demonstrate complex connections between various points, Gephi is a good fit.

Gephi is extremely easy to deploy. To visualize your data, you should first upload it, then optimize it, and then visualize. This library also lets web developers export visualized data to web documents and share it with their colleagues.


Dygraphs is a powerful and customizable programming library based on JavaScript. It allows web developers to visualize large amounts of data. It supports all modern web browsers. The main benefit of Dygraphs is that it provides a wide range of additional visualization features, such as pan, mouseover, zoom, etc. In fact, Dygraphs is a product developed by Google and it’s currently used by this company in some projects.

This charting tool is ideal when working with complex projects since it can process large amounts of data without any damage to the performance. Dygraphs has surrounded itself with a large community that is always ready to help you when you face any problem with this charting tool. Its source is available on GitHub.

Google Charts

Google Charts is a tremendous programming library for creating charts from large amounts of data. For those who have a good knowledge of JavaScript, this charting tool can become a real project saver. One of the main advantages of Google Charts is that it has an extremely detailed documentation which can greatly simplify tasks for those who just started working with this library. It supports both SVG- and HTML5-based graphs.

This library is the best choice for senior web developers who need an efficient tool accompanied with detailed instructions.


MetricsGraphics is among programming libraries based on D3.js. It’s aimed at visualizing time-series data and allows generating line graphs, scatterplots, bar diagrams, etc.

Being developed by Mozilla item, this charting tool has huge amounts of valuable documentation and code samples, making it easy to use for inexperienced web developers. The main benefit of MetricsGraphics is its simplicity, lightness, and easiness to install. This charting library is a good fit for those who need a fast and easy-to-learn solution.

As long as data remains true, comprehensive, and well represented, any of the above-mentioned charting libraries is a convenient solution. However, by comparing capabilities and focus of each, you will be able to choose the library that better correlates with your needs. At Unicsoft we have a deep expertise in working with big data and creating data analysis solutions for various industries.

Contact us at if you wondering how data science solutions can boost your business today.

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