(go ahead, you can play with it. Click and drag on any of the charts to perform a live filtering of the dataset)
The process to create these charts is relatively easy:
1. Load the data.
2. Define the dimensions with crossfilter.
3. Create the charts with D3.
4. Write the event code to respond to clicks and filters.
The main challenge of using crossfilter is that you have to spend quite some time
There’s also the question of reusability. How much code would we have to write â€“and maintainâ€“ if we wanted to adapt any of these charts to another visualization?
This is the main problem with using D3.js as a charting library and doing everything by hand. The development and testing of a single non-trivial dashboard could take weeks, if not months.
You know what would be ideal? To have a charting library that allowed us to use large datasets with crossfilter and, at the same time, enabled us to create reusable charts that we could easily plug in wherever we want.
(click and drag on any of the charts to filter the data)
This is the same set of charts, but done in a much simpler, faster and expressive way.
Take a look at the samples they have in their site, like this interactive Twitter dashboard or this stock picker.
dc.js performs the dirty work of linking the charts together, so when we click on a chart, the other charts in the group respond automatically, without writing any additional code. Magic!