Bokeh 0.10.0

Working in the Notebook

Displaying Inline Plots

To display Bokeh plots inline in an IPython/Jupyter notebook, use the output_notebook() function from bokeh.io instead of (or in addition to) the output_file() function we have seen previously. No other modifications are required. You can see an example below:

../../_images/notebook_inline.png

Note

As a convenience, output_notebook() is also importable from the bokeh.charts and bokeh.plotting modules.

Integrating IPython Interactors

It is possible to drive updates to Bokeh plots using IPython/Jupyter notebook widgets, known as interactors. The key doing this is the push_notebook() method on ColumnDataSource. This method allows you to update plot data sources in the notebook, so that the plot is made to update. Typically, push_notebook() is used in the update callback for the interactor. An example is shown below:

../../_images/notebook_interactors.png