Python Bokeh

Python Bokeh is an interactive visualization library that targets modern web browsers for presentation. Its goal is to provide a toolkit that can be used to create beautiful and meaningful visualizations, without having to write complex code. Bokeh allows Python programmers to easily create interactive plots, dashboards, and data applications that can be shared on the web.

Features of Python Bokeh

• Bokeh provides a flexible layer for creating and manipulating plot layouts.
• It provides a wide range of visualizations, including line, scatter, bar, and area charts, heatmaps, and more.
• Bokeh allows for easy interactive customization of plot elements.
• Bokeh provides a simple mechanism for creating widgets that can be used for interactive data exploration and manipulation.
• Bokeh provides server capabilities, enabling the creation of data-driven applications with real-time or streaming data updates.
• Bokeh integrates smoothly with other Python data manipulation and analysis tools like Pandas, NumPy, and Scikit-learn.

Basic Usage of Python Bokeh

To use Python Bokeh, start by installing it via pip:

pip install bokeh

Next, create a basic plot by specifying the data and the type of plot, such as a line chart:

import numpy as np
from bokeh.plotting import figure, output_file, show

x = np.linspace(0, 5, 100)
y = np.sin(x)

output_file("line.html")

p = figure(title="Simple Line Plot")
p.line(x, y)

show(p)

This will create a simple line chart and display it in a new browser window.

Conclusion

Python Bokeh is a powerful and flexible tool for creating interactive visualizations and data applications. With its intuitive syntax and robust features, Bokeh makes the creation of stunning data-driven applications achievable for Python programmers of all skill levels.