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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

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Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781803241005
Length 382 pages
Edition 1st Edition
Languages
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Authors (2):
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Ned Letcher Ned Letcher
Author Profile Icon Ned Letcher
Ned Letcher
Simon Aubury Simon Aubury
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Simon Aubury
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Toc

Table of Contents (15) Chapters Close

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 14. Other Books You May Enjoy

Working with geospatial data

Geospatial data describes the location and attributes of spatial objects. The DuckDB spatial extension adds support for working with geospatial data types. With the spatial extension loaded, we can store, query, analyze, and manipulate geospatial data in DuckDB using SQL commands.

The primary data type that the spatial extension introduces is the GEOMETRY data type. Underlying each GEOMETRY object is a more specific geometric subtype, such as POINT and LINE, which we will see shortly as part of researching a trip to the wine regions of France. We’ll be using geospatial data to calculate the distances between locations, and we’ll also be applying spatial filters to find candidate wine destinations to visit.

The spatial extension

Our first step is to install and load the DuckDB spatial extension:

INSTALL spatial;
LOAD spatial;

With the extension installed and loaded, let’s start our exploration of Paris. Imagine we are next...

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