DuckDB Tutorial: Data Analysis with CLI and Python API

You can use DuckDB as a fast in-process database to perform complex queries against large datasets. It's designed for online analytical processing (OLAP) workloads and offers features such as simple installation, portability, feature-richness, speed, and a free open-source license. To get started with DuckDB, you'll need to set up a Daytona workspace with the DuckDB Playground environment in it. This involves creating a GitHub repository, cloning it, preparing the devcontainer.json file, committing and pushing changes to GitHub, verifying Daytona installation, and creating a Daytona workspace with the DuckDB Playground environment. You can then use DuckDB as a command-line interface (CLI) tool to create databases from CSV files, examine database structure, retrieve distinct values, export data to separate CSV files, and read data from exported CSV files. Additionally, you can integrate DuckDB with Python through its Client API for data analysis, visualization, and correlation. Throughout this guide, you'll perform various hands-on tasks to gain practical experience with using DuckDB in a Daytona Workspace.

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