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Data Processing with Optimus

You're reading from   Data Processing with Optimus Supercharge big data preparation tasks for analytics and machine learning with Optimus using Dask and PySpark

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781801079563
Length 300 pages
Edition 1st Edition
Languages
Concepts
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Authors (2):
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Dr. Argenis Leon Dr. Argenis Leon
Author Profile Icon Dr. Argenis Leon
Dr. Argenis Leon
Luis Aguirre Contreras Luis Aguirre Contreras
Author Profile Icon Luis Aguirre Contreras
Luis Aguirre Contreras
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started with Optimus
2. Chapter 1: Hi Optimus! FREE CHAPTER 3. Chapter 2: Data Loading, Saving, and File Formats 4. Section 2: Optimus – Transform and Rollout
5. Chapter 3: Data Wrangling 6. Chapter 4: Combining, Reshaping, and Aggregating Data 7. Chapter 5: Data Visualization and Profiling 8. Chapter 6: String Clustering 9. Chapter 7: Feature Engineering 10. Section 3: Advanced Features of Optimus
11. Chapter 8: Machine Learning 12. Chapter 9: Natural Language Processing 13. Chapter 10: Hacking Optimus 14. Chapter 11: Optimus as a Web Service 15. Other Books You May Enjoy

Chapter 3: Data Wrangling

Now that our data has been loaded in memory, we need to transform it so that it meets our needs. First, we will discuss transforming, searching, and replacing data, including strings, dates, emails, and URLs. When it comes to numerical data, we will review the mathematical and trigonometric functions available in Optimus.

To close this chapter, we will learn how to write some custom functions to expand the possibilities of data wrangling and improve Optimus.

The topics we will cover in this chapter are as follows:

  • Exploring Optimus data types
  • Operating columns
  • Experimenting with user-defined functions
lock icon The rest of the chapter is locked
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