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Getting Started with DuckDB
A practical guide for accelerating your data science, data analytics, and data engineering workflows
Taschenbuch von Ned Letcher
Sprache: Englisch

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Beschreibung
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. Getting Started with DuckDB offers a practical overview of its usage. You'll learn to load, transform, and query various data formats, including CSV, JSON, and Parquet. The book covers DuckDB's optimizations, SQL enhancements, and extensions for specialized applications. Working with examples in SQL, Python, and R, you'll explore analyzing public datasets and discover tools enhancing DuckDB workflows. This guide suits both experienced and new data practitioners, quickly equipping you to apply DuckDB's capabilities in analytical projects. You'll gain proficiency in using DuckDB for diverse tasks, enabling effective integration into your data workflows.
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
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. Getting Started with DuckDB offers a practical overview of its usage. You'll learn to load, transform, and query various data formats, including CSV, JSON, and Parquet. The book covers DuckDB's optimizations, SQL enhancements, and extensions for specialized applications. Working with examples in SQL, Python, and R, you'll explore analyzing public datasets and discover tools enhancing DuckDB workflows. This guide suits both experienced and new data practitioners, quickly equipping you to apply DuckDB's capabilities in analytical projects. You'll gain proficiency in using DuckDB for diverse tasks, enabling effective integration into your data workflows.
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
Über den Autor
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.
Details
Erscheinungsjahr: 2024
Fachbereich: Betriebssysteme & Benutzeroberflächen
Genre: Importe, Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
ISBN-13: 9781803241005
ISBN-10: 1803241004
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Letcher, Ned
Hersteller: Packt Publishing
Verantwortliche Person für die EU: Books on Demand GmbH, In de Tarpen 42, D-22848 Norderstedt, info@bod.de
Maße: 235 x 191 x 21 mm
Von/Mit: Ned Letcher
Erscheinungsdatum: 24.06.2024
Gewicht: 0,712 kg
Artikel-ID: 129441707
Über den Autor
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.
Details
Erscheinungsjahr: 2024
Fachbereich: Betriebssysteme & Benutzeroberflächen
Genre: Importe, Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
ISBN-13: 9781803241005
ISBN-10: 1803241004
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Letcher, Ned
Hersteller: Packt Publishing
Verantwortliche Person für die EU: Books on Demand GmbH, In de Tarpen 42, D-22848 Norderstedt, info@bod.de
Maße: 235 x 191 x 21 mm
Von/Mit: Ned Letcher
Erscheinungsdatum: 24.06.2024
Gewicht: 0,712 kg
Artikel-ID: 129441707
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