DuckDB: Up and Running

Fast Data Analytics and Reporting
This practical book explains how DuckDB leverages Python libraries and tools for data analytics, machine learning, and AI. Author Wei-Meng Lee helps developers, data engineers, data analysts, and data scientists get started.

DuckDB is an open source in-process database created for OLAP workloads. It provides key advantages that separate this database from more mainstream OLAP solutions, including embeddability, compatibility with SQL, optimization for fast and efficient analytics, and integration with Python. This practical book shows you how DuckDB leverages Python libraries and tools for data analytics, machine learning, and AI.

Author Wei-Meng Lee shows developers, data engineers, data analysts, and data scientists how to get started. You'll learn the primary features and functions of DuckDB, explore use cases and best practices, and examine practical examples of how DuckDB can be used for a variety of data analytics tasks. You'll also dive into specific topics including how to import data into DuckDB, work with tables, perform exploratory data analysis, visualize DuckDB data, perform spatial analysis, and use DuckDB with JSON files, Polars, and JupySQL.

You'll also explore:

• The purpose of DuckDB and its main functions
• How to conduct data analytics tasks using DuckDB
• Methods for integrating DuckDB with pandas, Polars, and JupySQL
• How to use DuckDB to query your data
• Ways to perform spatial analytics using DuckDB's spatial extension
• How to work with a diverse range of data including Parquet, CSV, and JSON

Wei-Meng Lee is a technologist and founder of Developer Learning Solutions, a company that provides hands-on training on the latest technologies.

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