Python Bokeh title(): Customize Plot Titles Guide

In data visualization, clear and well-formatted titles are essential for conveying information effectively. The Bokeh library's title property allows you to add and customize plot titles with precision.

Basic Title Implementation

Let's start with a simple example of adding a title to a Bokeh plot. The basic syntax is straightforward and allows you to quickly set a plot title.

from bokeh.plotting import figure, show

# Create a basic plot
p = figure(width=600, height=400)
p.line([1, 2, 3, 4], [1, 4, 2, 3])

# Set a basic title
p.title.text = "My First Bokeh Plot"

show(p)

Customizing Title Appearance

Bokeh offers extensive options for customizing your plot titles. You can modify the font, size, color, and alignment to match your visualization needs.

from bokeh.plotting import figure, show

p = figure(width=600, height=400)
p.line([1, 2, 3, 4], [1, 4, 2, 3])

# Customize title appearance
p.title.text = "Customized Plot Title"
p.title.align = 'center'  # Title alignment
p.title.text_color = 'navy'  # Title color
p.title.text_font_size = '24px'  # Title size
p.title.text_font_style = 'bold'  # Title style

show(p)

Title Positioning and Offset

You can adjust the title's position relative to the plot using the offset property. This is particularly useful when working with multiple plots in a grid layout.

# Adjust title position
p.title.offset = 30  # Pixels from the top of the plot
p.title.vertical_align = 'bottom'  # Vertical alignment
p.title.align = 'right'  # Horizontal alignment

Adding Subtitle and Multiple Lines

Sometimes you need to display additional information below the main title. Here's how to create a multi-line title or add a subtitle to your plot.

from bokeh.plotting import figure, show
from bokeh.models import Title

p = figure(width=600, height=400)
p.line([1, 2, 3, 4], [1, 4, 2, 3])

# Add main title
p.title.text = "Main Title"

# Add subtitle
p.add_layout(Title(text="Subtitle Text", text_font_style="italic"), 'above')

show(p)

Dynamic Titles with Interactive Features

When creating interactive visualizations, you might want to combine titles with hover tools or other interactive features to enhance user experience.

from bokeh.plotting import figure, show
from bokeh.models import CustomJS

p = figure(width=600, height=400)
p.line([1, 2, 3, 4], [1, 4, 2, 3])

# Create dynamic title with callback
callback = CustomJS(args=dict(title=p.title), code="""
    title.text = 'Updated Title: ' + new Date().toLocaleTimeString();
""")

p.js_on_event('tap', callback)  # Title updates on plot tap
show(p)

Best Practices for Title Implementation

When working with titles in Bokeh, keep these important guidelines in mind:

• Keep titles concise and descriptive
• Use appropriate font sizes for readability
• Maintain consistent styling across multiple plots
• Consider mobile responsiveness when setting font sizes

Conclusion

The Bokeh title property provides powerful tools for creating professional-looking plot titles. By combining these features with proper legend customization, you can create clear and informative visualizations.

Remember to balance aesthetics with readability when designing your plot titles, and always consider your audience when choosing title styles and formatting options.