Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Review Help
Search
Personal finance with Python : using pandas, Requests, and Recurrent
Humber M., Apress, New York, NY, 2018. 117 pp. Type: Book (978-1-484238-01-1)
Date Reviewed: Jan 31 2019

I have probably said this way too many times in reviews, but it remains true and to the point: one of the great things about learning Python programming is that it allows you to move more easily into other areas that you might want to learn about. In this case, you can go from knowing a bit about Python to developing a greater and more technical understanding of personal finance. This book uses examples of Python code to illustrate financial concepts such as return on investment (ROI), currency conversion, loan amortization (payoff schedule), budgeting, and simple portfolio management. I am a Python programmer and I manage my own portfolio. So I was very excited to see this title come out. Sadly, I was also very disappointed.

The audience for this book, according to the author, “is anyone interested in Python, personal finance, or how to combine the two!” So, let’s look at it from each of these perspectives. Other than code samples, there is very little Python in the book. There are no tutorials or basic introductions to Python concepts. So you can type in the examples and hope they work, but if they don’t, or if you want to modify them, you are out of luck. This gets worse in the later chapters where pandas is introduced and the code becomes even more arcane. Thus, instead of “anyone interested in Python” the author should have said “anyone with a working knowledge of Python programming and some exposure to pandas.”

We have the same problem with “anyone interested in personal finance.” For example, if you are not already familiar with the concept of internal rate of return (IRR), you are not going to learn it from the brief explanation or the terse code example. It gets worse with amortization--a more difficult concept--using pandas DataFrames, where graphics are needed to explain the programming loops. Thus, “interested” should be replaced with “with a solid foundation,” as the reader will not get that from this book.

Finally, let’s consider those readers who “combine the two.” Let’s say you are someone with a working knowledge of Python programming and a solid foundation in personal finance. The code samples might be useful to save you the trouble of having to write them yourself. However, if you really do have that background, writing the code needed to implement these concepts should not present a major challenge. Still, one has to ask why pandas was introduced when simpler Python constructs could have been used just as well. Granted, pandas does make it easier, but easier for what? Certainly not for explaining or understanding the financial concepts. And it doesn’t make the coding easier if you must first master pandas concepts to use the code.

In summary, all that can be said is that there is a great need for a book on Python and personal finance. Unfortunately, this book is not the answer.

More reviews about this item: Amazon

Reviewer:  J. M. Artz Review #: CR146407 (1904-0089)
Bookmark and Share
  Reviewer Selected
Featured Reviewer
 
 
Python (D.3.2 ... )
 
 
Financial (J.1 ... )
 
Would you recommend this review?
yes
no
Other reviews under "Python": Date
Practical Python
Hetland M., APress, LP, 2002.  648, Type: Book (9781590590065)
Mar 28 2003
Python programming: an introduction to computer science
Zelle J., Franklin B, 2003. Type: Book (9781887902991)
Dec 2 2004
Foundations of Python network programming
Goerzen J., APress, LP, Berkeley, CA, 2004.  512, Type: Book (9781590593714)
Dec 26 2004
more...

E-Mail This Printer-Friendly
Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright 1999-2024 ThinkLoud®
Terms of Use
| Privacy Policy