SLIDcES is in a prototype phase. What is it? There’s a reason for a lowercase ‘c’ in there; this is a ‘slide’- like presentation package that uses DC.js internally. Thus, DC within SLIDES, or SLIDcES.
Here is an example created to visualize some auto leases offered in the Summer of 2014. Compare this to reading through paragraphs or even tables of data. Click on the image to see the sample and see how visualization can help with leasing comparisons.
So what is DC.js? Dimensional Charting roughly speaking is D3 + Crossfilter. Follow the links for more information about each library.
1. D3 is a js library that provides capability to manipulate documents based on data, allowing visualizations that can come alive through the use of basic web technology (HTML, SVG and CSS) supported by modern browsers. The full name is Document Driven Data, or D3 for short.
+ 1. Crossfilter, also a js library, enables exploring large multivariate datasets in the browser.
There are many public examples of the DC technology, one such is at Dancing Data* using coffee shop data. The D3 Gallery is full of charts that demonstrate a wide range of visualizations that could be created. Although DC.js presently has a limited subset implemented, it does meet basic charting requirements, and more.
Click on over to SLIDcES and start by trying out the Auto Leases sample, using real** data from July 2014. Check the Show Table checkbox in the upper left corner of the page in order to view the table of all or filtered data. Isn’t this a better way to compare lease offers, than reading through a table, many paragraphs, or multiple articles/websites of offers?
SLIDcES has a small footprint, a few hundred Kbytes. The files can be loaded from a CDN, or hosted locally, even within an Android App. The Google Play store has a sample app that loads the files from www.the12Lab.com – https://play.google.com/store/apps/details?id=com.the12Lab.wvd.SLIDcES
Note* The Dancing Data example does take quite some time to load, YMMV.
Note** ‘real’ here includes any errors in the original data, and any that may have been introduced creating this sample.