Python for Everybody - Dr. Chuck

100 Mathematical Python Coding Exercises with Solutions Keys Unleash the. Page 2/31 About the book Python Workout presents 50 exercises that focus on 

ads

Part of the document


It is quite natural for academics who are continuously told to "publish or perish"
to want to always create something from scratch that is their own fresh creation.
This book is an experiment in not starting from scratch, but instead "remixing"
the book titledThink Python: How to Think Like a Computer Scientistwritten
by Allen B. Downey, Jeff Elkner, and others.
In December of 2009, I was preparing to teachSI502 - Networked Programmingat
the University of Michigan for the fifth semester in a row and decided it was timeto
write a Python textbook that focused on exploring data instead of understanding
algorithms and abstractions. My goal in SI502 is to teach people lifelongdata
handling skills using Python. Few of my students were planning to be professional
computer programmers. Instead, they planned to be librarians, managers, lawyers,
biologists, economists, etc., who happened to want to skillfully use technology in
their chosen field.
I never seemed to find the perfect data-oriented Python book for my course, so I
set out to write just such a book. Luckily at a faculty meeting three weeks before
I was about to start my new book from scratch over the holiday break, Dr. Atul
Prakash showed me theThink Pythonbook which he had used to teach his Python
course that semester. It is a well-written Computer Science text with a focus on
short, direct explanations and ease of learning.
The overall book structure has been changed to get to doing data analysis problems
as quickly as possible and have a series of running examples and exercises about
data analysis from the very beginning.
Chapters 2-10 are similar to theThink Pythonbook, but there have been major
changes. Number-oriented examples and exercises have been replaced with data-
oriented exercises. Topics are presented in the order needed to build increasingly
sophisticated data analysis solutions. Some topics liketryandexceptare pulled
forward and presented as part of the chapter on conditionals. Functions are given
very light treatment until they are needed to handle program complexity rather
than introduced as an early lesson in abstraction. Nearly all user-defined functions
have been removed from the example code and exercises outside of Chapter 4. The
word "recursion"