Working in the Notebook

Inline Plots

To display Bokeh plots inline in an Jupyter notebook, use the output_notebook() function from instead of (or in addition to) the output_file() function we have seen previously. No other modifications are required. When show() is called, the plot will be displayed inline in the next notebook output cell. You can see a screenshot below:



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

Notebook Handles

It is possible to update a previously shown plot in-place. When the argument notebook_handle=True is passed to show() then a handle object is returned. This handle object can be used with the push_notebook() function to update the plot with any recent changes to plots properties, data source values, etc.

The following screenshots walk through the basic usage of notebook handles.

  • Next, create some plots, and make sure to pass notebook_handle=True to show():
  • Looking at the handle, see that it is associated with the output cell for In[2] that was just displayed:
  • Now, update any properties of the plot, then call push_notebook() with the handle:
  • After doing so, note that the earlier output cell for In[2] has changed (without being re-executed)

More detailed demonstrations of using notebook handles can be found in the following example notebooks:

Jupyter Interactors

It is possible to drive updates to Bokeh plots using Jupyter notebook widgets, known as interactors. The key doing this is the push_notebook() function described above. Typically it is called in the update callback for the interactors, to update the plot from widget values. A screenshot of the examples/howto/notebook_comms/Jupyter Interactors.ipynb example notebook is shown below: