Getting Started with DuckDB: A practical guide for accelerating your data science, data analytics, and data engineering workflows

Analyze and transform data efficiently with DuckDB, a versatile, modern, in-process SQL database

Key Features

- Use DuckDB to rapidly load, transform, and query data across a range of sources and formats

- Gain practical experience using SQL, Python, and R to effectively analyze data

- Learn how open source tools and cloud services in the broader data ecosystem complement DuckDB's versatile capabilities

- Purchase of the print or Kindle book includes a free PDF eBook

Book Description

DuckDB is a fast in-process analytical database. Its ease of use, versatile feature set, and powerful analytical capabilities make DuckDB a valuable addition to the data practitioner's toolkit.

Getting Started with DuckDB offers a practical overview of DuckDB's fundamentals and guidance for effectively using its powerful capabilities. Through extensive hands-on examples, you'll learn how to use DuckDB to load, transform, and query a variety of data sources and formats, including CSV, JSON, and Parquet files, semi-structured data, remotely-hosted files, and external databases. You'll also find out how to leverage DuckDB's performance optimizations and friendly SQL enhancements. You'll explore how to use DuckDB's extensions for specialized applications, such as geospatial analysis and text search over document collections. In addition to working through examples in SQL, Python, and R, you'll also dive into using DuckDB for analyzing public datasets and discover the wider ecosystem of open-source tools and cloud services that supercharge DuckDB-powered workflows and applications.

Whether you're a seasoned data practitioner or new to working with analytical data, this book will rapidly get you up to speed with DuckDB's versatile and powerful capabilities, enabling you to apply them in your analytical workflows and projects.

What you will learn

- Understand the properties and applications of a columnar in-process database

- Use SQL to load, transform, and query a range of data formats

- Discover DuckDB's rich extensions and learn how to apply them

- Use nested data types to model semi-structured data and extract and model JSON data

- Integrate DuckDB into your Python and R analytical workflows

- Effectively leverage DuckDB's convenient SQL enhancements

- Explore the wider ecosystem and pathways for building DuckDB-powered data applications

Who this book is for

If you're interested in expanding your analytical toolkit, this book is for you. It will be particularly valuable for data analysts wanting to rapidly explore and query complex data, data and software engineers looking for a lean and versatile data processing tool, along with data scientists needing a scalable data manipulation library that integrates seamlessly with Python and R. You will get the most from this book if you have some familiarity with SQL and foundational database concepts, as well as exposure to a programming language such as Python or R.

Table of Contents

- An Introduction to DuckDB

- Loading Data into DuckDB

- Data Manipulation with DuckDB

- DuckDB Operations and Performance

- DuckDB Extensions

- Semi-Structured Data Manipulation

- Setting up the DuckDB Python Client

- Exploring DuckDB's Python API

- Exploring DuckDB's R API

- Using DuckDB Effectively

- Hands-On Exploratory Data Analysis with DuckDB

- DuckDB - The Wider Pond