Visual Representation of cloud data


A javascript library that parses raw data (from a database or api) and generates meaningful visualizations.

In essence, the scope of Cloudvisio is to allow for the easy generation of "axis" based on the raw data.

For the technical person Cloudvisio may resemble a javascript template engine for graphs.

For the artistic mind Cloudvisio may open up the possibility to play with the data in creative ways.

Powered by D3.

  • D3 integration
  • Structure agnostic approach
  • Live filtering of data

This is the kind of charts you can create right now:

As the library is enhanced with more methods, we expect "smarter" use cases to emerge.

For client-side processing you can install with bower:

bower install cloudvisio

For server-side processing you can use npm (still work in progress):

npm install cloudvisio

For either client-side or server-side processing the API is the same. For instance:

var chart = new Cloudvisio({ layout: "stack" });
chart.parse( data );

In the above example, where 'data' is a known javascript object with pre-caclulated axis. If the data is a raw collection we can filter it first by creating the axis out of conditions we create:

var chart = new Cloudvisio({ layout: "stack" }); data );
chart.axis("name");["USA"], "address");

After the data is processed we compile the new chart with the method render() which will output the required markup.

var html = chart.render();

Look into the examples folder for more specific implementations of the (server-side) logic.

  • layout: "string", the type of chart we want to render. Review the layout section for the available options
  • chart: { object }, options related with the rendering of the chart - which differ for every layout. ...

The api is trying to use the most obvious conventions every experienced web developer is already familiar with, and thus it is greatly inspired by vanilla js, jquery, backbone and of course the d3 library itself.

Pass a raw object to the library that will be used for further analysis.

Add a normalized dataset ( with pre-calculated axis ) to the models.

Update the visualization's options dynamically. Accepts an object of updated values.

Apply a query on the data with either filter, exclude or group sorting.

Use an axis as a basis to group the parsed models into groups, with their labels specified in the array.

Cloudvisio supports some of D3 layouts out of the box.

  • Stack
  • Pie
  • Force ...

In addition, Cloudvisio can accept custom layouts using the chart() method.

Created by Makis Tracend

Distributed through

Released under the Apache License v2.0