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Polars Cookbook

You're reading from   Polars Cookbook Over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781805121152
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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Yuki Kakegawa Yuki Kakegawa
Author Profile Icon Yuki Kakegawa
Yuki Kakegawa
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Table of Contents (15) Chapters Close

Preface 1. Chapter 1: Getting Started with Python Polars FREE CHAPTER 2. Chapter 2: Reading and Writing Files 3. Chapter 3: An Introduction to Data Analysis in Python Polars 4. Chapter 4: Data Transformation Techniques 5. Chapter 5: Handling Missing Data 6. Chapter 6: Performing String Manipulations 7. Chapter 7: Working with Nested Data Structures 8. Chapter 8: Reshaping and Tidying Data 9. Chapter 9: Time Series Analysis 10. Chapter 10: Interoperability with Other Python Libraries 11. Chapter 11: Working with Common Cloud Data Sources 12. Chapter 12: Testing and Debugging in Polars 13. Index 14. Other Books You May Enjoy

Working with Google Cloud Storage

Google Cloud Platform (GCP) is another major cloud provider in the industry. Google Cloud Storage (GCS) is an object file store on GCP. Polars can work with it by utilizing the GCSFS library.

In this recipe, we’ll look at how to read from and write to a GCS in Polars.

Getting ready

You need your GCP account for this recipe. Follow the instructions in the link I mentioned under Technical requirements to create your GCP account.

Let’s first create a Google Cloud Storage bucket and upload a file to it:

  1. Navigate to Cloud Storage and click on CREATE.
Figure 11.34 – Creating a cloud storage bucket

Figure 11.34 – Creating a cloud storage bucket

  1. Enter your bucket name and leave the rest of the settings as they are. Note that each bucket name is globally unique. I suggest that you add your name or initials as a suffix. Once you have clicked CREATE to create a bucket, you may be asked to enforce public access prevention. Make...
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