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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

Loading Data into DuckDB

DuckDB is a flexible analytical database that can handle a variety of data types and workloads. A common task when working with DuckDB is loading data from external data sources, such as comma-separated values (CSV), JavaScript Object Notation (JSON), and Apache Parquet files. In this chapter, we will introduce the basic concepts and methods for loading data into DuckDB and provide some examples and best practices to help you get started.

You will learn how to load data into DuckDB from external data sources, how to create tables using SQL commands, and how to load data from various sources and formats, including CSV, JSON, and Parquet files, along with exploring some of the considerations when working with compressed columnar formats. We will also use DuckDB to query and analyze a public dataset, in addition to reviewing how we can export data from DuckDB.

In this chapter, we’re going to cover the following main topics:

Loading CSV files...

The rest of the chapter is locked

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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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