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Python Data Analysis - Third Edition

You're reading from  Python Data Analysis - Third Edition

Product type Book
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Pages 478 pages
Edition 3rd Edition
Languages
Authors (2):
Avinash Navlani Avinash Navlani
Profile icon Avinash Navlani
Ivan Idris Ivan Idris
Profile icon Ivan Idris
View More author details
Toc

Table of Contents (20) Chapters close

Preface 1. Section 1: Foundation for Data Analysis
2. Getting Started with Python Libraries 3. NumPy and pandas 4. Statistics 5. Linear Algebra 6. Section 2: Exploratory Data Analysis and Data Cleaning
7. Data Visualization 8. Retrieving, Processing, and Storing Data 9. Cleaning Messy Data 10. Signal Processing and Time Series 11. Section 3: Deep Dive into Machine Learning
12. Supervised Learning - Regression Analysis 13. Supervised Learning - Classification Techniques 14. Unsupervised Learning - PCA and Clustering 15. Section 4: NLP, Image Analytics, and Parallel Computing
16. Analyzing Textual Data 17. Analyzing Image Data 18. Parallel Computing Using Dask 19. Other Books You May Enjoy

Interactive visualization with Bokeh

Bokeh is an interactive, high-quality, versatile, focused, and more powerful visualization library for large-volume and streaming data. It offers interactive, rich charts, plots, layouts, and dashboards for modern web browsers. Its output can be mapped to a notebook, HTML, or server.

Both the Matplotlib and Bokeh libraries have different intentions. Matplotlib focuses on static, simple, and fast visualization while Bokeh focuses on highly interactive, dynamic, web-based, and quality visualization. Matplotlib is generally used for publication images while Bokeh is for a web audience. In the remaining sections of this chapter, we will learn basic plotting using Bokeh. We can create more interactive visuals for data exploration using Bokeh.

The simplest way to install the Bokeh library is with the Anaconda distribution package. To install Bokeh, use the following command:

conda install bokeh

We can also install it using pip. To install Bokeh using pip...

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