Python for MBAs

Python for MBAs is an excellent book for introducing this very useful programming language to business people who don't have programming experience.  In today's world it is a useful skill to acquire, and this versatile language can be very useful in many areas of business.  The case studies and exercises are all relevant and based on real world  examples so you can see exactly how you could make use of the language.  The book is accessible, easy to read and easy to understand.  Overall a great book and skill to learn.

I have always hope to explore the areas of learning some simple programme language but it always look very intimidating. Appreciate the work of this book to make Python accessible to non-programmers.

There is no question that the ability to harness technology has become an essential skill in business today.  It is also the case that Python has become one of the most widely adopted programming languages, largely due to its versatility in solving problems and its user-friendly accessibility.  So, despite the many self-help texts the already exist in this area, there is always room for another, especially one that seeks to acclimate beginners to the field quickly and competently.  That is exactly what Python for MBAs attempts to accomplish and, for the most part, it succeeds in doing just that.

According to the authors, two business school faculty with considerable experience teaching the subject, the book is aimed at people who have never written computer code before, but feel the need to understand at least some part of this rapidly expanding area before the world passes them by altogether.  In particular, the authors want to show readers how they can use Python to automate some of their daily tasks—such as financial record-keeping or responding to messages—as well as condensing large, unwieldly databases into more useable forms.  To do this, they divide the writing into two distinct parts: Basic Python Skills and Dataset Management.

As promised, the book really does start at the beginning with an explanation of how to download the Python program and set up a home computer to facilitate the best programming environment.  That is followed in Part 1 by three fairly compact chapters in which the basics of the language itself are presented, including how variables are created and used, conditional (i.e., True or False) statements, data lists, simple loop structures, and basic functions.  All of this information is quite well explained and nicely illustrated with several examples.  In fact, readers are repeatedly encouraged to work through these exercises on their own to gain confidence in each of the skills.  If there is a shortcoming in this part of the text it would be that it seemed a little too terse and limited in presenting Python’s many features, although the discussion may be just enough to accomplish the authors’ goals.

In Part 2, the tone of the project changes considerably as the topic shifts from developing basic programming skills to learning to organize and manage large databases.  The motivation for the entire second half of the book is the analysis of a case study the authors have written on Dig, a New York-based restaurant chain, and how the company used data analytics to improve its operations.  Essentially, each of the five chapters in this part is devoted to acquainting the reader with various aspects of Pandas, which a Python-compatible software library used for manipulating large data bases and performing statistical and graphical analysis on that information.  Once again, the authors do an excellent job of explaining each new topic that arises and applying case-based problems as examples.

Overall, I liked Python for MBAs and I think it will be a useful tool to introduce some essential material.  However, I also found the book’s title to be a little misleading in that it promises to be more about developing Python programming skills than it actually delivers.  In reality, the text is more centered on database management, with only as much Python knowledge as necessary to facilitate that aim; a title such as Managing Databases With Python  might have been more appropriate.  Also, the book may be difficult to use in a classroom setting because its exposition is so heavily tied to the authors’ embedded case study and it lacks the type of end-of-chapter problems and exercises found in traditional texts.  Still, this is a worthy effort that should meet the needs of a sizeable audience of business professionals.

_Python for MBAs_ by Mattan Griffel and Daniel Guetta is a high-level introduction to the Python programming language with special care taken to describe aspects of the language that will be of interest to business students and users. The book provides a good overview to both the Python programming language, the use of the Pandas data analytics module, and additional content customized for business needs, including data aggregation and advanced analytics.

The first part of the book, comprising chapters 1-4, serves as an introduction to the Python programming language. The introduction is both basic and complete, one that new users will find useful and advanced users will want to merely skim through. The introduction is well written, but contains nothing that isn't in many other Python language introductions.

The next three chapters, numbers 5-7, serve as an overview of the Python Pandas data analytics module, including how to load, examine, modify, and plot data using this library. This is the beginning of the part of the book that will be interesting to business students and users, as many of their interests will involve this type of activity. Again, the description is solid, but contains nothing that might not be found in other places, for example Joel Grus's _Data Science from Scratch_, or Jake VanderPlas's _Python Data Science Handbook_.

The final two chapters focus on data aggregation and advanced analytic techniques, and these are both useful and specialized to the interest of business students.

On the whole, the book is competent, well-written, and interesting. Most of the topics are covered in other sources, many of them freely available, but what is unique in this book is their summary here. One imagines that the book arose from a programming class for business students, and that it would serve similar niches well.

Python is probably the most versatile of the modern programming languages. In my research institutions I see it used from engineers working on supercomputers to archaeologists cataloguing ancient artifacts. Therefore, I think it should be must too for economists/entrepreneurs to have the basics of this programming  language to manage numbers and simulations in a much more powerful way that Excel for instance may provide. This book then covers a perceived gap. The volume is easy to follow. It requires however some familiarity with how to use computers.