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Getting Started with DuckDB

You're reading from   Getting Started with DuckDB A practical guide for accelerating your data science, data analytics, and data engineering workflows

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Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781803241005
Length 382 pages
Edition 1st Edition
Languages
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Authors (2):
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Ned Letcher Ned Letcher
Author Profile Icon Ned Letcher
Ned Letcher
Simon Aubury Simon Aubury
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Simon Aubury
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Toc

Table of Contents (15) Chapters Close

Preface 1. Chapter 1: An Introduction to DuckDB FREE CHAPTER 2. Chapter 2: Loading Data into DuckDB 3. Chapter 3: Data Manipulation with DuckDB 4. Chapter 4: DuckDB Operations and Performance 5. Chapter 5: DuckDB Extensions 6. Chapter 6: Semi-Structured Data Manipulation 7. Chapter 7: Setting up the DuckDB Python Client 8. Chapter 8: Exploring DuckDB’s Python API 9. Chapter 9: Exploring DuckDB’s R API 10. Chapter 10: Using DuckDB Effectively 11. Chapter 11: Hands-On Exploratory Data Analysis with DuckDB 12. Chapter 12: DuckDB – The Wider Pond 13. Index 14. Other Books You May Enjoy

Technical requirements

In this chapter, we’ll be working with Python inside a Jupyter Notebook environment. You will find the code examples covered in this chapter in the chapter_11 folder in this book’s GitHub repository, which can be found at https://github.com/PacktPublishing/Getting-Started-with-DuckDB/tree/main/chapter_11. To work through the exercises here, if you haven’t already, you’ll need to clone this repository to the machine you’ll be using.

Setting up the environment

To be able to run the code in this chapter, you’ll need to have a Python virtual environment set up with the necessary dependencies installed. You’ll also need a Jupyter-Notebook-compatible IDE setup. If you have not done so already, please follow the instructions in the Technical requirements section of Chapter 7 before jumping into the code in this chapter.

Obtaining the dataset

In this chapter, we’ll be working with one of the pedestrian...

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