Tag Archives: D3.js
The NBA Shot Chart has become iconic in many ways. It’s a quality visualization that gives context to the boring summarized score board data we see everyday. This context is valuable to basketball nerds and lay folks alike. In any event this post is not about the intricacies of basketball but about using Node.js/ d3.js to make cool shot carts.
Passing a function as an argument to other functions is a difficult concept to understand for beginners, especially those coming from other languages. D3 further compounds this difficulty by making the functions-as-arguments model integral to the basic pattern, but doesn’t force the designer to understand what the heck is going on when they type function in the middle of their code.
AngularJS is very strong in data binding as well. This feature saves a lot of time and effort required to update the UI according to data in the model. In the modern web world, customers ask developers to build websites that respond in real-time. This means the customers want to always see the latest data on the screen. Data UI has to be updated as soon as someone modifies a piece of data in the back-end. Performing such real-time updates would be very difficult and inefficient if we don’t have support of data binding.
In this article, we will see how to build real-time AngularJS directives that wrap D3 charts.
With the knowledge of jQuery type libraries like Highcharts, I was introduced to D3. At a first glance, I thought that it was just another charting library. That proved to be very wrong.
In this post, I won’t compare D3 to other charting libraries but there might be cases where I talk with reference to popular technologies like jQuery and jQueryUI since it is very easy to understand where you stand compared to what you probably already know.
It has an adaptor for d3.js that allows you to use cola as a drop-in replacement for the D3 force layout. The layout converges to a local optimum unlike the D3 force layout, which forces convergence through a simple annealing strategy. Thus, compared to D3 force layout:
- CoLa achieves higher quality layout;
- is much more stable in interactive applications (no “jitter”);
- it allows user specified constraints such as alignments and grouping;
- it can automatically generate constraints to:
- it may be less scalable to very large graphs.
However, it works well on an average machine on graphs with fewer than 100 nodes.
cola.js can now (optionally) route edges to avoid intersections with node boundaries.
this blog post is to introduce open source business intelligence technologies and explore data using open source technologies like D3.js, DC.js, Nodejs and MongoDB.
Over the span of this post we will see the importance of the various components that we are using and we will do some code based customization as well.