Hands-On Data Visualization with Bokeh: Interactive web plotting for Python using Bokeh by Kevin Jolly

Author:Kevin Jolly [Jolly, Kevin]
Language: eng
Format: epub
Tags: COM018000 - COMPUTERS / Data Processing, COM089000 - COMPUTERS / Data Visualization, COM051360 - COMPUTERS / Programming Languages / Python
Publisher: Packt Publishing
Published: 2018-06-14T23:00:00+00:00

plot = figure(title = "High Vs. Low Prices (Google & USB)")

plot.title.text_color = "red"

plot.title.text_font = "times"

plot.title.text_font_style = "bold"

plot.circle('high', 'low', size = 8, source = data,

color = {'field': 'Name', 'transform': category_map})

#Output the plot

output_file('title.html')

show(plot)

This results in a plot with a unique title, as illustrated here:

In this plot, the title is red in color, with the Times New Roman font, and is bold. In this code, we used title.text_color to give the title a red color. We then used title.text_font to give the title the Times New Roman font. Finally, we used title.text_font_style to give the plot a bold font.

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