Welcome to Python for Business, Economics & Finance

Welcome to Python for Business, Economics & Finance#

This book is designed for the Data Analytics, Quantitative Methods and Statistics, and Data Analysis courses at the University of Winchester. Whether you’re completely new to programming or brushing up on your skills, this book will guide you step-by-step through Python fundamentals and data analysis techniques.

Author: Sakib Anwar

What You’ll Learn#

By the end of this book, you will be able to:

  • Write Python programs using variables, functions, and control flow

  • Work with data structures like lists and dictionaries

  • Load, clean, and manipulate data using pandas

  • Create visualisations with seaborn and matplotlib

  • Perform hypothesis testing and regression analysis

  • Build interactive dashboards with Streamlit

How to Use This Book#

📖 Reading#

Each chapter builds on the previous one. We recommend going through them in order, especially if you’re new to programming.

💻 Running Code#

The code examples in this book show real output, but the cells are not interactive. To run the code yourself, copy and paste it into Google Colab — a free, browser-based Python environment that requires no installation.

✏️ Exercises#

At the end of each chapter, you’ll find exercises to test your understanding. Give each exercise a genuine try before clicking the dropdown to reveal the solution.

Prerequisites#

No prior programming experience is required. However, you should be comfortable with:

  • Basic mathematics (arithmetic, percentages)

  • Using a web browser

  • A willingness to experiment and make mistakes!

Textbook Reference#

The lecture materials for this course are based on:

Békés, G., & Kézdi, G. (2021). Data analysis for business, economics, and policy. Cambridge University Press.

Website: gabors-data-analysis.com

Diez, D. M., Çetinkaya-Rundel, M., & Barr, C. D. (2019). OpenIntro Statistics (4th ed.). OpenIntro, Inc.

Website: openintro.org

Let’s Get Started!#

Ready to write your first Python program? Head to Chapter 1: Getting Started with Python.

Note

If you find any errors or have suggestions for improvement, please open an issue on GitHub.

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