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  • Book Overview & Buying Getting Started with DuckDB
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Getting Started with DuckDB

Getting Started with DuckDB

By : Simon Aubury, Ned Letcher
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Getting Started with DuckDB

Getting Started with DuckDB

5 (1)
By: Simon Aubury, Ned Letcher

Overview of this book

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.
Table of Contents (15 chapters)
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Connecting to DuckDB in Python

When working with DuckDB in Python, the first thing to consider is how you’ll connect to a target DuckDB database from your Python code. Even though DuckDB runs embedded within a parent process, meaning that you don’t have to worry about authenticating to a remote server, you still need to consider how your Python process will make and manage connections to potentially multiple DuckDB databases.

In this section, we’ll be covering the two broad ways to issue commands to DuckDB databases in Python:

  1. Using the default in-memory database: This database is automatically created for you when you import the duckdb module. The default database provides a convenient way to quickly perform activities such as ad-hoc data analysis when you know you will only need a single database in your session. This is what you will connect to when you invoke a function from the duckdb module that interacts with a database, such as duckdb.sql() and...
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Getting Started with DuckDB
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