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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 Amazon S3

Amazon S3 is one of the most popular choices for an object storage service. Many organizations use it for a data lake, a data repository that stores both structured and unstructured data.

In this recipe, we’ll look at how to read from and write to an S3 bucket in Polars.

Getting ready

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

Let’s create an S3 bucket. I introduce how to do that in the following steps, but if you prefer reading the documentation on your own, here’s a useful link: https://docs.aws.amazon.com/AmazonS3/latest/userguide/creating-bucket.html.

Here are the steps for creating an S3 bucket:

  1. Navigate to https://aws.amazon.com/ and sign in to your account.
  2. You can either type S3 in the search bar, click on Services on the top left, or just choose S3 in Recently visited if you see one.
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