Bokeh is a new plotting framework for Python that natively understands the relationships in multidimensional datasets, uses a Protovis-like expression syntax scheme for creating novel visualizations, and is designed from the ground up to be used on the web.
Although it can be thought of as "ggplot for Python", the goals of Bokeh are much more ambitious. The Grammar of Graphics primarily addresses the mapping of pre-built aeshetics and layouts to a particular data schema and tuples of measure variables. It has limited facility for expressing data interactivity, and its small set of graph types (aka "geoms" or glyphs) are somewhat limited in both their number and in the number of ways they can be combined with one another.
On the flip side, most existing Python plotting frameworks adopt a "tell me how" instead of a "tell me what" approach. Thus, user plotting code canfrequently become mired down in what amounts to details of the rendering system.
In our talk, we will show various features of Bokeh, and talk about future development. We will also go into some detail about how Bokeh unifies the tasks of describing data mapping, building data-driven layout, and composing novel visualizations using a single, multi-purpose scene and data graph.