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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

Exploring DuckDB’s Python API

In the previous chapter, we started our journey into using DuckDB and Python by getting the DuckDB Python client installed into a Jupyter Notebook-based environment, as well as unpacking the different ways to connect to DuckDB databases. In this chapter, we’ll continue where we left off by diving into a practically oriented walkthrough of the core components of the DuckDB Python API, which will enable you to hit the ground running working with DuckDB in Python.

More specifically, we’ll explore the following aspects of working with DuckDB in Python:

  • Interacting with DuckDB using the Relational API
  • Interacting with DuckDB using the Python DB-API
  • Consuming from and converting to Python in-memory data formats, including Apache Arrow tables, pandas Dataframes, and Polars Dataframes
  • How Python types are converted to DuckDB types
  • Using Python functions in DuckDB queries
  • Exception handling with DuckDB
...
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