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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

Product type Paperback

Published in Jun 2024

Publisher Packt

ISBN-13 9781803241005

Length 382 pages

Edition 1st Edition

Languages

Python

Concepts

Data Analysis

Authors (2):

Ned Letcher

Simon Aubury

View More author details

Table of Contents (15) Chapters

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

Why subscribe?

14. Other Books You May Enjoy

Technical requirements

The exercises in this chapter require that you have a Python virtual environment set up with the necessary dependencies installed and also have a Jupyter Notebook-compatible IDE set up. If you have not done so already, please follow the instructions in the Technical requirements section of Chapter 7 before jumping into the examples in this chapter.

GitHub repository

You will find data and the code examples covered in this chapter in the chapter_08 folder in the book’s GitHub repository:

https://github.com/PacktPublishing/Getting-Started-with-DuckDB/tree/main/chapter_08.

Obtaining the dataset

To help us unpack DuckDB’s Relational API for Python, we’re going to explore the Seattle Pet Licenses dataset, which contains information about pet licenses that have been registered in the city of Seattle. We’ll be performing a small amount of exploratory data analysis (EDA) over this dataset, which will give us an opportunity to...

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Authors (2)

Simon Aubury

Simon Aubury

Simon Aubury has been working in the IT industry since 2000 as a data engineering specialist. He has an extensive background in building large, flexible, highly available distributed data systems. Simon has delivered critical data systems for finance, transport, healthcare, insurance, and telecommunications clients in Australia, Europe, and Asia Pacific. In 2019, Simon joined Thoughtworks as a principal data engineer and today is associate director of data platforms at Simple Machines in Sydney, Australia. Simon is active in the data community, a regular conference speaker, and the organizer of local and international meetups and data engineering conferences.

See other products by Simon Aubury

Ned Letcher

Ned Letcher

Ned Letcher has worked as a data science and software engineering consultant since completing his PhD in computational linguistics in 2018 and currently works at Thoughtworks. He has designed and developed data-powered products and services across a range of industries and helped organizations and teams improve the effectiveness of their data processes and workflows. Ned has also worked as a Python trainer, supporting both tertiary students and data professionals across various organizations. He is active in the data community, speaking at and helping organize meetups and conferences, as well as contributing to a range of open source projects.

See other products by Ned Letcher

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