This text introduces the foundations of computational thinking: a novel approach to computer science problems which provides the tools to reduce complicated problem statements into simple-to-understand statements. This text radically redefines how introductory Python programming courses are structured and enables students of all backgrounds to learn the basics. This text can be used as an accompaniment to a structured course or by self-learners as it contains the tools to mimic the traditional classroom environment. This book is geared towards novice programmers by providing in-depth and easy-to-understand methodologies. This text will progressively introduce the fundamental concepts of computer science, and, once students have mastered the basics, the book dives into the use of cutting-edge Python programming techniques. Students will learn about the history of computer science, the internal components of a computer, creation of variables, data types, arrays, abstract data structures, if/else branching structures, for and while looping structures, functions, and finally the use of high-powered libraries for the analysis of real-world data sets. Regardless of a student's background knowledge, with dedication and commitment, all students will be able to learn the basics of Python in no time! 

Table of Contents:
1. Introduction  Preface Why Python? 2 .The Computer What Is a Computer? An Abbreviated History of Computational Devices Components of the Computer Computer Processor Memory Storage Devices Motherboard 3. Introduction to Computational Thinking and Pseudocode Decomposition Abstraction Pattern Matching Algorithm Pseudo Cod Process Visualization Strategies 4. The Anaconda Environment and Python The Key Features of Python Getting Started with Python Introduction to the Spyder Environment Adding Additional Modules and Libraries to Python Installing Third-Party Libraries 5. First Programs in Python Programming Within the Command Console Variable Assignment Python Scripts Strings and Text Data in Python Nuts and Bolts of Programs Specifying Numeric Input From the User The Print Command and Formatting Outpu Problem Sets 6. Data Types and Arrays Data Types Lists Dictionaries and Associative Arrays Uniqueness of Data Types Type and Variable IDs Reserved Namespaces Math Package and Operations Chapter Problem Sets 7. Mathematical Logic An Introduction to Logic Basics of Mathematical Logic Boolean Logic and Truth Tables Conditional Statements Chapter Problem Sets 8. Branching Structures (If/Else, IF/Elseif/Else) Conditional Statements and Boolean Logic If Branching Structures If/Else Conditional Structures If/Elif/Else Structures Nested If/Else Structures Boolean Expression Tricks Chapter Problem Set 9. Introduction to Looping Structures While Loops in Python For Loop in Python Value Selection, Updating Lists, and Looping Structures Applying Operations Over Lists of Elements Nested Looping Structures Chapter Problem Sets 10. Introduction to Functions Defining Functions in Python Input and Output Handling With Functions Functions and Efficient Code Design Dynamic Typing and Python Functions Variable Scope and Functions Top-Down Programming and Driver Files Chapter Problem Sets 11. Tables and Plotting With PANDAS and MATPLOTLIB Introduction to Pandas Tables and Pandas Getting Started With Pandas Basics of Pandas DataFrames Pandas Data Manipulation Techniques Chapter Problem Sets 12. Plotting Applications With Matplotlib Line Plots Histograms and Bar Plots Scatter Plots Chapter Problem Sets