Description
Book SynopsisThis book is an introduction to programming with Python for MBA students and others in business positions who need a crash course. Beginning with fundamentals such as variables, strings, lists, and functions, it builds up to data analytics and practical ways to derive value from large and complex datasets.
Trade ReviewBusiness leaders everywhere increasingly need top technology and data skills to stay competitive. Mattan Griffel and Daniel Guetta bring Python to life through clear and compelling stories and case studies, showing you how to use the power of variables, strings, and lists to immediately help your business and analytics. -- Glenn Hubbard, dean emeritus and Russell L. Carson Professor of Finance and Economics, Columbia Business School
In the data-driven economy, there is an enormous demand for hybrid professionals who are simultaneously broad and deep across business and technical fields. Mattan Griffel and Daniel Guetta have done a great job providing a practical, step-by-step guide for commercially minded individuals to upskill quickly in the technical arena. This will be required reading for all those in my team who need to rapidly learn fundamental data and analytical skills. -- Afsheen Afshar, founder and CEO, Pilot Wave Holdings Management
Business education is changing to prepare MBA students for careers in the digital age and to provide an understanding of the technological capabilities and analytics tools driving this digital transformation. Griffel and Guetta are experts in Python and its use in business analytics. This book will be an incredible resource for teaching programming to students in MBA programs and for business practitioners and managers. -- Costis Maglaras, dean and David and Lyn Silfen Professor of Business, Columbia Business School
Table of ContentsIntroduction
Part I1. Getting Started with Python
2. Python Basics, Part 1
3. Python Basics, Part 2
4. Python Basics, Part 3
Part II5. Introduction to Data in Python
6. Exploring, Plotting, and Modifying Data in Python
7. Bringing Together Datasets
8. Aggregation
9. Practice
What’s Next?
Notes
Index
