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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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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

Hands-On Exploratory Data Analysis with DuckDB

DuckDB is particularly well-suited to data analysis workflows due to its versatility and highly optimized performance, allowing practitioners to scale data analysis workflows beyond what they would be otherwise able to achieve on their local machine. Previously, we have been focusing more on covering core DuckDB concepts and features, with a bit of data analysis thrown in as examples. In this chapter, we’ll be putting the data analysis workflow first by taking what we’ve learned about using DuckDB and using these foundations to perform some hands-on exploratory analysis of a dataset. This will allow us to explore different approaches for performing effective data analysis with DuckDB.

More specifically, in this chapter, we’ll cover the following topics:

  • Loading our dataset from a CSV file and applying some data cleaning steps, before writing it to a DuckDB database for our analysis
  • Using the JupySQL...
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