Beautiful Data(Driven) Visualizations with Javascript

Data visualizations let us turn raw data into relevant information and make it easier to extract meaning from the information and to reason about it. In the talk we'll look at a few examples of powerful javascript libraries that can be used to load, manipulate data in the browser and turn it into beautiful visualizations, easily accessible on the web.

A key method when analyzing huge amounts of data to understand some phenomenon is to create a visual representation of the data we have gathered to grasp a better understanding and try confirm some hypothesis we had. The purpose of data visualization is to turn raw data into meaningful information and the aim of visually representing a data set is that it allows people to extract meaning from the information and to reason about it.

The web browser, given its ubiquitous presence on anyone's computer, is the ideal platform to consume data visualizations shared through the web and javascript has its fair amount of data-viz libraries ( two successful examples are or Processing.js ). One of the most recent and interesting is the subject of this talk: D3 is the successor to a data visualization library called protovis and it brings a novel data centric approach to manipulating data and building graphical representations of it.

Data can be declaratively bound to the elements in the page using a very expressive and powerful function chaining method. It is easy to describe what we want our visualization to look like, and how we want it to change in response to changes in the data or events in the interface.

This is an example of how to represent a force-directed graph to visualize the appearances of the characters in Victor Hugo's Les Miserables:

Another example it Conway's game of life implemented in less than 100 lines of javascript code:

During the talk we'll look at the basics concepts of the D3 library building (interactively, with help from the audience!) a few examples of data visualizations that will help us understand how to:

* load data and connect it with visual elements
* apply transformations to the elements based on data
* operate on new data points added or removed
* use some of the powerful APIs available






60 minutes


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