Welcome to the official GitHub repository for . This repo contains the datasets, code examples, and exercises referenced in the book. Whether you're following along with the chapters or diving deeper into the material, this repository provides everything you need to practice and apply the concepts covered.
📖 About the Book This book is a comprehensive guide to mastering data analysis, covering both technical and strategic skills essential for early to mid-career data analysts and data scientists. From asking the right questions to designing effective metrics, and from mastering data structuring to leveraging modern tools and technologies, this book equips you with the knowledge to succeed in any analytics role.
📁 Repository Contents
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Datasets
Folder: datasets/ Description: Contains all the datasets used in the book's examples and exercises. Each dataset includes a brief description and notes on its source or purpose.
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Code Examples
Folder: examples/ Description: Contains Python, SQL, and dbt code snippets illustrating the concepts and techniques discussed in the book. Organized by chapter for easy navigation.
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Exercises
Folder: exercises/ Description: Hands-on exercises to reinforce your learning. Each exercise includes instructions, starter code, and solution files where applicable.
🚀 Getting Started
git clone https://github.com/mona-kay/effective-data-analysis.git
cd effective-data-analysis
Ensure you have Python installed (3.12 recommended). Install required Python packages:
pip install -r requirements.txt
Explore the Folders Navigate to datasets/ to load the sample datasets. Open the examples/ folder for chapter-specific scripts. Complete the exercises in exercises/.
Run Examples Follow the instructions in the book to execute the code examples and explore the results.
📬 Contact
If you have questions or feedback about the repo or the book, reach out via GitHub Issues or connect on .