JavaScript for Line of Business Applications

The following should be an introduction to combining D3 with React to create reusable chart components. This is not intended to be an introduction into D3 nor React.

D3s approach to data visualization fits well with the React way of building UI components and App structuring. React encourages to figure out how to structure a number of components to enforce a data flow that moves from top down, meaning that lower level components receive data and render it at best and only keep state if needed, but never manipulating any data that might affect the higher up components.

Another strong correlation between the libraries is their respective component lifecycle. D3 has enter, update and exit.

At the time of this post, working with SVG in Ember can be a PITA to say the least.

The issues faced in Ember with SVG are the same issues faced by most frameworks. In fact, as of right now (now meaning while I'm typing this), there are no stable versions of JavaScript "frameworks" that fully support SVG properly. Angular, Ember, React and Polymer all have some pain around handling SVG. Some of them attempt to handle it, React for example, but there are certain cases where it will still break.

A small example exploring how to integrate D3.js data visualizations into a React app.

I think that using React and D3.js together makes sense because they share a common philosophy of "give me a set of data, tell me how it should be rendered, and I'll figure out which parts of the DOM to update for you". Indeed, React has its virtual DOM diffs, and D3.js has its update selections, making both quite efficient in the business of keeping the UI in sync with data changes.

I find that making D3 components play nice inside a React app becomes easier when you follow these simple guidelines: ...

Vis.js is a dynamic, browser based visualization library. The library is designed to be easy to use, to handle large amounts of dynamic data, and to enable manipulation of and interaction with the data. The library consists of the components DataSet, Timeline, and Graph.

Sigma is a JavaScript library dedicated to graph drawing. It makes easy to publish networks on Web pages, and allows developers to integrate network exploration in rich Web applications.

Sigma provides a lot of built-in features, such as Canvas and WebGL renderers or mouse and touch support, to make networks manipulation on Web pages smooth and fast for the user.

Sigma provides a lot of different settings to make it easy to customize how to draw and interact with networks. And you can also directly add your own functions to your scripts to render nodes and edges the exact way you want.

D3 a very powerful tool and at times can be a bit overwhelming. Today I would like to simplify things by walking you through building a bar chart using D3.

First step is to create a barChart directive.

It will will take an data array and add a svg tag to our element. We will using this svg to build our chart.

D3 allow us to resize our data to the portions of the SVG using d3.scale. We tell the scale the upper and lower bounds of the dataset using domain and the upper and lower bounds of the chart using range. Using x and y functions generated from d3.scale.linear(), we can then place bars in the right spot on the SVG.

C3 makes it easy to generate D3-based charts by wrapping the code required to construct the entire chart. We don't need to write D3 code any more.

Forio Contour provides a core set of common visualizations that you can see in the gallery, and it's easy to extend if you want to add your own customizations. Plus, it's free and open source.

Forio Contour uses the popular D3 engine and adds a set of intuitive abstractions so you can easily create graphs and charts.

Welcome to DashingD3js.com - a website full of D3 Tutorials, D3 Screencasts and a D3 Newsletter.

* Why Data Visualizations
* Why build Data Visualizations with D3.js
* The Data Visualization Process
* Basic Building Blocks
* D3.js First Steps
* Adding a DOM element
* Adding an SVG element
* Binding Data to DOM Elements
* Using Data Bound to DOM Elements
* Creating SVG Elements Based on Data
* Using the SVG Coordinate Space
* Data Structures D3.js Accepts
* Using JSON to Simplify Code
* SVG Basic Shapes and D3.js
* SVG Paths and D3.js
* Dynamic SVG Coordinate Space
* D3.js Scales
* SVG Group Element and D3.js
* SVG Text Element
* D3.js Axes

These tutorials evolved out of my own process of learning how to use D3. You already know that D3 is an extraordinary tool for mapping data within web pages, written by Mike Bostock. Many people, including myself, come to D3 with backgrounds in design, mapping, and data visualization, but not programming and computer science.

Yet D3 employs advanced JavaScript techniques, so learning to use D3 often means learning a lot about JavaScript. For many datavis folks, D3 is their introduction to JavaScript. It’s hard enough to learn a new programming language, let alone a new tool built on that language. D3 is amazing and will enable you to do great things with JavaScript that you never would have even attempted. The time you spend learning both the language and the tool will provide an incredible payoff.

My goal is to reduce that learning time, so you can start creating awesome stuff sooner.

* Fundamentals
* Setup
* Adding elements
* Chaining methods
* Binding data
* Using your data
* Drawing divs
* The power of data()
* An SVG primer
* Drawing SVGs
* Types of data
* Making a bar chart
* Making a scatterplot
* Scales
* Axes

Cytoscape.js is an open-source graph library written in JavaScript. You can use Cytoscape.js for graph analysis and visualisation.

Cytoscape.js allows you to easily display graphs in your websites. Because Cytoscape.js allows the user to interact with the graph and the library allows the client to hook into user events, Cytoscape.js is easily integrated into your webapp, especially since Cytoscape.js supports both desktop browsers, like Chrome, and mobile browsers, like on the iPad.

Cytoscape.js also has graph analysis in mind: The library contains a slew of useful functions in graph theory. You can use Cytoscape.js headlessly on Node.js to do graph analysis in the terminal or on a web server.

Dc.js is a JavaScript library used to make interactive dashboards in JavaScript. By clicking and selecting different events in graphs, you can filter the entire dashboard to drill into a particular event.

In order to do this, DC.js relies on two other JavaScript plugins/libraries: D3.js and Crossfilter js.

With this first art we're going to start off with how Crossfilter works because most of the actual dashboard code is manipulating the data for the charts. Once you have a good understanding of how that works, the actual graphing is pretty simple. I'm going to try to cover several different scenarios, so you can hopefully avoid some of the pitfalls as you start to use it.