Search icon
Subscription
0
Cart icon
Close icon
You have no products in your basket yet
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Essential PySpark for Scalable Data Analytics

You're reading from  Essential PySpark for Scalable Data Analytics

Product type Book
Published in Oct 2021
Publisher Packt
ISBN-13 9781800568877
Pages 322 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Sreeram Nudurupati Sreeram Nudurupati
Profile icon Sreeram Nudurupati

Table of Contents (19) Chapters

Preface 1. Section 1: Data Engineering
2. Chapter 1: Distributed Computing Primer 3. Chapter 2: Data Ingestion 4. Chapter 3: Data Cleansing and Integration 5. Chapter 4: Real-Time Data Analytics 6. Section 2: Data Science
7. Chapter 5: Scalable Machine Learning with PySpark 8. Chapter 6: Feature Engineering – Extraction, Transformation, and Selection 9. Chapter 7: Supervised Machine Learning 10. Chapter 8: Unsupervised Machine Learning 11. Chapter 9: Machine Learning Life Cycle Management 12. Chapter 10: Scaling Out Single-Node Machine Learning Using PySpark 13. Section 3: Data Analysis
14. Chapter 11: Data Visualization with PySpark 15. Chapter 12: Spark SQL Primer 16. Chapter 13: Integrating External Tools with Spark SQL 17. Chapter 14: The Data Lakehouse 18. Other Books You May Enjoy

Chapter 11: Data Visualization with PySpark

So far, from Chapter 1, Distributed Computing Primer, through Chapter 9, Machine Learning Life Cycle Management, you have learned how to ingest, integrate, and cleanse data, as well as how to make data conducive for analytics. You have also learned how to make use of clean data for practical business applications using data science and machine learning. This chapter will introduce you to the basics of deriving meaning out of data using data visualizations.

In this chapter, we're going to cover the following main topics:

  • Importance of data visualization
  • Techniques for visualizing data using PySpark
  • Considerations for PySpark to pandas conversion

Data visualization is the process of graphically representing data using visual elements such as charts, graphs, and maps. Data visualization helps you understand patterns within data in a visual manner. In the big data world, with massive amounts of data, it is even...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime}