Data Science I with python

STAT 303-1-Sec20

Author

Lizhen Shi

Preface

Welcome to STAT 303-1 (Data Science with Python I), Section 20 at Northwestern University.

This book is designed to support your journey into data science, blending foundational concepts with hands-on practice. It builds on the original work of Professor Arvind Krishna, whose materials inspired the structure and spirit of this resource. The content has been thoughtfully updated to meet the evolving needs of students and the goals of the course.

In this first course, you will:

  • Learn to use essential Python libraries for data science, including but not limited to NumPy, Pandas, and Matplotlib. These three are the main focus, but you will also be introduced to other useful libraries and tools as needed for real-world data analysis.
  • Develop skills in Exploratory Data Analysis (EDA), transforming messy, real-world datasets into meaningful insights through visualization, summarization, and pattern discovery

The book is organized to guide you step-by-step:

  • Chapters 1–3: Set up your coding environment in VS Code, understand Python environments, and enhance your workflow
  • Chapters 4–5: Review key concepts from STAT 201. If you need a refresher, visit the STAT 201 ebook.
  • New material begins in Chapter 6 – Reading Data

Throughout the quarter, this resource will be updated and refined to improve clarity, depth, and alignment with our teaching objectives.

As a living document, your feedback and suggestions are always welcome. Contributions from students, instructors, and the broader academic community help make this book stronger and more effective.

If you have ideas for improving the textbook, please share your feedback or suggestions using our dedicated Textbook Improvement Form. Your input is invaluable in making this resource better for everyone.

Thank you for joining us on this learning adventure. We hope this book becomes a valuable companion as you build your skills and confidence in data science with Python.