There is a Python package, Bokeh, that can be used to generate a figure in your notebook where the user can interact and change the figure.

In this example, I am using the same data from the histogram example later in this chapter (also included in the file set for this chapter) to display an interactive Bokeh histogram.

The coding is as follows:

from bokeh.io import show, output_notebook
from bokeh.charts import Histogram
import numpy as np
import pandas as pd
# this step is necessary to have display inline in a notebook
output_notebook()
# load the counts from other histogram example
from_counts = np.load("from_counts.npy")
# convert array to a dataframe for Histogram
df = pd.DataFrame({'Votes':from_counts})
# make sure dataframe is working correctly
print(df.head())
   Votes
0     23
1     29
2     23
3    302
4     24
# display the Bokeh histogram
hist = Histogram(from_counts, 
title="How Many Votes Made By Users", 
bins=12)
show(hist) 

We can see the histogram displayed as follows. There is little being done automatically to clean up the graph, such as move counters around or the uninteresting axes labels. I assume there are options with the Histogram function that would allow further changes:

Notice the widgets across the top of the image:

• On the left side is a Bokeh icon
• On the right side are icons for:
  • Moving the image to another portion of the screen
  • Magnifying
  • Resizing
  • Wheel zoom-slide wheel to zoom in/out
  • Save the image to disk
  • Refresh the image
  • Interactive help on Bokeh functions