Why and when to use D3 for Data Visualization?

This article was originally posted on our company website. TechVariable is a product development company from India.

D3 or Data-Driven Documents is an open-source JavaScript library and is undoubtedly the most influential tool for creating custom interactive data visualizations in the web browser using SVG, HTML and CSS.

With the massive amount of data being generated each day, communication of this information in a lucid yet attractive manner becomes the most challenging task. Visual representations of data have always been the most effective means of conveying meaningful information and D3 is one such dynamic and intuitive means that provides a great deal of ease and flexibility to create personalized data visualizations.

D3 is a purely data-driven and extremely powerful visualization tool that creates interactive data visualizations by exploiting modern web standards. D3 is able to use either static data or fetch it directly from any remote server in different formats like Arrays, Objects, JSON, CSV, XML etc. to name a few and create different types of intuitive and attractive charts.

It is one such tool that allows manipulation of the Document Object Model (DOM) based on the data and empowers the data to dynamically generate elements and apply styles to the elements. D3 is often preferred over other data visualization tools as it is a very flexible tool that can provide dynamic properties to most of its functions. With D3, there are no standard visualization formats. Rather we can create anything from a simple HTML table to a dynamic line or pie chart, from graphs and bar charts to 3-D geospatial maps with geojson and topojson formats.

D3 works with web standards and gives us complete control over our visualization features through the transition() function. Since D3 works out the logic to interpolate between our values to find the intermittent states, this makes it a powerful tool internally. Also, D3 provides great support for faster and responsive animation with functions like duration(), delay() and ease().

“So why use D3 in the first place”?

“D3 is amazingly powerful, it allows endless creativity and customization. It’s no rocket science, but far more learnable and interesting for any avid programmer.”

You can check this case study to delve deeper into Data Visualization.

Key Benefits:

• D3 is data-focused, hence it becomes the apt and specialized tool for data visualizations.
• As D3 is a Javascript library, it can be easily used with any of the JS frameworks, say, Angular.js, React.js and Ember.js, etc.
• D3 is open-source and we can work with the source code and add our own features.
• It works with web standards so you don’t need any other technology or plugin other than a browser to make use of D3.
• There is no need for a new learning or debugging tool required to work on D3 as it works with every web standard like HTML, CSS and SVG.
• Also, D3 does not provide any specific feature, so it gives you complete freedom as well as control over our visualization to customize the way we want. This can be called the USP of D3 as this provides an edge over other popular tools like Chart.JS, Tableau or QlikView.
• D3 is extremely fast and works easily with larger and most complex datasets.

Now, let’s analyze some of the key reasons for learning D3:

1. Lots of D3 examples.

One of the prime fortes of learning D3 would be no barrier to our imagination, we can create all kinds of scatterplot visualizations. We can make use of the dashed strokes or composite filter effects or clipping, seriously there’s just no limit to what sort of mapping charts to be built with D3 be it a Bar or Circle Chart, Pie or Donut Chart, Line or Bubble Chart!

Most of the examples are posted online since the mighty developers want others to re-use their code. Also, you may check the following links to check out these awesome D3 examples:

• Stoppage made by Police in January 2012 in New York
• Visual Introduction to Machine Learning
• More than 600 examples on D3

2. Open and vibrant open-source community

Also, while working with D3 whenever we face any issue, there are extensive and primarily ample free resources available on the internet because of the very large and vibrant open-source community of users and learners of D3.

3. Demanding skill

The rate at which D3 is being so widely used for data visualization, having a grasp over it to master makes us thrice more hirable for the tech jobs. Even if the job does not seek direct D3 skills, the way we would be able to communicate complex data for the potential clients, business partners and investors and benefit the company itself, by all means, leverages our outstanding identity in any interview.

4. Learning web development skills.

While learning D3, we also get an opportunity to learn many other web skills involving JavaScript and HTML. Therefore, knowing these skills make us adapt to work in different kinds of projects involving web development. At the end of the day, we learn a lot about foundational web skills, unlike some other data visualization frameworks such as Tableau, Chartist.js, FusionCharts, Datawrapper, ChartBlocks, etc.

We acquire broader skills because D3 exposes you to the internals of a webpage. In more technical terms, D3 doesn’t use ‘Intermediate’ representations, instead, it directly manipulates elements on the Document Object Model (DOM).

5. Cost Cutting

If we seek customized and dynamic dashboards/data stories delivered at a low cost on the web, then D3 tends to stand out amongst the other options due to the requirement of lesser manpower while working with D3 which ultimately results in lesser friction, and the project gets delivered effectively within the timeline

Meanwhile, D3 in React and Python is gaining extreme popularity these days as React and D3.js is an extremely popular pairing among frontend developers and on the other hand, Python and D3.js are frequently paired to produce reusable and engaging data visualizations with reproducible and editable source code.

The only trouble with learning D3 is that the learning curve depends solely on our background, so a front-end developer would have the easiest time in understanding JavaScript, SVG and the browser Document Object Model (DOM), while the non-technical designers and analysts might take a bit longer to grasp a stronghold of all the concepts of d3.js modules, resources and web browser technologies that it is built upon as a wonderful map for understanding on how the ecosystem and various parts of the library fit together.

You can grab a cup of coffee and binge on another short write-up on ‘Python for backend development’.