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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 1: Hi Optimus!

Optimus is a Python library that loads, transforms, and saves data, and also focuses on wrangling tabular data. It provides functions that were designed specially to make this job easier for you; it can use multiple engines as backends, such as pandas, cuDF, Spark, and Dask, so that you can process both small and big data efficiently.

Optimus is not a DataFrame technology: it is not a new way to organize data in memory, such as arrow, or a way to handle data in GPUs, such as cuDF. Instead, Optimus relies on these technologies to load, process, explore, and save data.

Having said that, this book is for everyone, mostly data and machine learning engineers, who want to simplify writing code for data processing tasks. It doesn't matter if you want to process small or big data, on your laptop or in a remote cluster, if you want to load data from a database or from remote storage – Optimus provides all the tools you will need to make your data processing task easier.

In this chapter, we will learn about how Optimus was born and all the DataFrame technologies you can use as backends to process data. Then, we will learn about what features separate Optimus from all the various kinds of DataFrame technologies. After that, we will install Optimus and Jupyter Lab so that we will be prepared to code in Chapter 2, Data Loading, Saving, and File Formats.

Finally, we will analyze some of Optimus's internal functions to understand how it works and how you can take advantage of some of the more advanced features.

A key point: this book will not try to explain how every DataFrame technology works. There are plenty of resources on the internet that explain the internals and the day-to-day use of these technologies. Optimus is the result of an attempt to create an expressive and easy to use data API and give the user most of the tools they need to complete the data preparation process in the easiest way possible.

The topics we will be covering in this chapter are as follows:

  • Introducing Optimus
  • Installing everything you need to run Optimus
  • Using Optimus
  • Discovering Optimus internals
You have been reading a chapter from
Data Processing with Optimus
Published in: Sep 2021
Publisher: Packt
ISBN-13: 9781801079563
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