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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

Exploring DuckDB’s Python API

In the previous chapter, we started our journey into using DuckDB and Python by getting the DuckDB Python client installed into a Jupyter Notebook-based environment, as well as unpacking the different ways to connect to DuckDB databases. In this chapter, we’ll continue where we left off by diving into a practically oriented walkthrough of the core components of the DuckDB Python API, which will enable you to hit the ground running working with DuckDB in Python.

More specifically, we’ll explore the following aspects of working with DuckDB in Python:

Interacting with DuckDB using the Relational API
Interacting with DuckDB using the Python DB-API
Consuming from and converting to Python in-memory data formats, including Apache Arrow tables, pandas Dataframes, and Polars Dataframes
How Python types are converted to DuckDB types
Using Python functions in DuckDB queries
Exception handling with DuckDB

...

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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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