bqplot

bqplot is a Grammar of Graphics based interactive plotting framework for the Jupyter notebook. The library offers a simple bridge between Python and d3.js allowing users to quickly and easily build complex GUI's with layered interactions.

Basic Plotting

To begin start by investigating the introductory notebooks:

1. Introduction - If you're new to bqplot, get started with our Introduction notebook
2. Basic Plotting - which demonstrates some basic bqplot plotting commands and how to use them
3. Pyplot - which introduces the simpler pyplot API

Marks

Move to exploring the different Marks that you can use to represent your data. You have two options for rendering marks:

• Object Model, which is a verbose API but gives you full flexibility and customizability
• Pyplot, which is a simpler API (similar to matplotlib's pyplot) and sets meaningul defaults for the user

1. Bars: Bar mark (Object Model, Pyplot)

• Bins: Backend histogram mark (Object Model, Pyplot)
• Boxplot: Boxplot mark (Object Model, Pyplot)
• Candles: OHLC mark (Object Model, Pyplot)
• FlexLine: Flexible lines mark (Object Model, Pyplot)
• Graph: Network mark (Object Model, Pyplot)
• GridHeatMap: Grid heatmap mark (Object Model, Pyplot)
• HeatMap: Heatmap mark (Object Model, Pyplot)
• Hist: Histogram mark (Object Model, Pyplot)
• Image: Image mark (Object Model, Pyplot)
• Label: Label mark (Object Model, Pyplot)
• Lines: Lines mark (Object Model, Pyplot)
• Map: Geographical map mark (Object Model, Pyplot)
• Market Map: Tile map mark (Object Model, Pyplot)
• Pie: Pie mark (Object Model, Pyplot)
• Scatter: Scatter mark (Object Model, Pyplot)

Interactions

Learn how to use bqplot interactions to convert your plots into interactive applications:

1. Mark Interactions - which describes the mark specific interactions and how to use them
2. Interaction Layer - which describes the use of the interaction layers, including selectors and how they can be used for facilitating better interaction

Advanced Plotting

Once you've mastered the basics of bqplot, you can use these notebooks to learn about some of it's more advanced features.

1. Plotting Dates
2. Advanced Plotting
3. Animations
4. Axis Properties

Applications

Finally, we have a collection of notebooks that demonstrate how to use bqplot and ipywidgets to create advanced interactive applications.

1. Wealth of Nations - a recreation of Hans Rosling's famous TED Talk

Help

For more help,

• Reach out to us via the ipywidgets gitter chat

• Or take a look at a talk given on Interactive visualizations in Jupyter at PyData