In this section, we use another Python library, bokeh, to display a chart where the user can adjust parameters of the graphic for different results.
Note
The installation instructions for the bokeh library are very complex. Again, they're specific to the operating system and version of Python you are using in your installation.
We are presenting online voter information, with the data points showing, for each user ID, how many votes they received for some post they made.
We can use this script:
from bokeh.io import output_notebook, show
from bokeh.layouts import widgetbox
from bokeh.models.widgets import TextInput
from bokeh.models import WidgetBox
import numpy as np
import pandas as pd
from bokeh.plotting import figure, show
from bokeh.layouts import layout
output_notebook()
# load the vote counts
from_counts = np.load("from_counts.npy")
# convert array to a dataframe (Histogram requires a dataframe)
df = pd.DataFrame({'Votes...
