data_visualization_bokeh.py

from bokeh.io import output_file, show
from bokeh.plotting import figure

plot = figure(plot_width=400, tools='pan,box_zoom')

# import the HoverTool
from bokeh.models import HoverTool
# Add circle glyphs to figure p
p.circle(x, y, size=10,
         fill_color='grey', alpha=0.1, line_color=None,
         hover_fill_color='firebrick', hover_alpha=0.5,
         hover_line_color='white')

# Create a HoverTool: hove
hover = HoverTool(tooltips=None, mode= 'vline')

# Add the hover tool to the figure p
p.add_tools(hover)

# Specify the name of the output file and show the result
output_file('hover_glyph.html')
show(p)

#Import CategoricalColorMapper from bokeh.models
from bokeh.models import CategoricalColorMapper
# Convert df to a ColumnDataSource: source
source = ColumnDataSource(df)

# Make a CategoricalColorMapper object: color_mapper
color_mapper = CategoricalColorMapper(factors=['Europe', 'Asia', 'US'],
                                      palette=['red', 'green', 'blue'])

# Add a circle glyph to the figure p
p.circle('weight', 'mpg', source=source,
            color=dict(field='origin',transform=color_mapper),
            legend='origin')

# Specify the name of the output file and show the result
output_file('colormap.html')
show(p)