Hands-on Python Programming for Beginners: Learn Practical Python Fast
- Length: 380 pages
- Edition: 1
- Language: English
- Publisher: AI Publishing LLC
- Publication Date: 2021-06-12
- ISBN-10: 1734790199
- ISBN-13: 9781734790191
- Sales Rank: #153972 (See Top 100 Books)
Hands-on Python Programming for Beginners — Learn Practical Python Fast
Are you ready to learn the essential concepts of practical Python fast?
Python is so popular today because writing programs in this language is easy. You’ll miss out if you fail to add Python knowledge to your arsenal. However, with this book, you can start coding in this language immediately—right now and right here.
Hands-on Python Programming for Beginners: Learn Practical Python Fast presents you with a hands-on, easy approach to learn practical Python fast.
How Is This Book Different?
The best way you can learn Python is by doing. It’s scientifically proven that practical learning has a profound impact on learners. Doing things practically, in fact, improves your learning experience. Practical learning also improves your understanding of Python concepts in a better way compared to just listening to lectures.
If your knowledge of Python and coding is minimal, this book is perfect for you. The reason is this learning by doing book will teach you all the practical skills that truly matter. This easy-to-follow Python book is nicely packaged with many extras: Python codes, exercises, references, and PDFs on the publisher’s website.
The extra learning materials will improve your learning experience. The book is divided into 13 chapters that include a lot of exercises with answers to practice. Examples are also included to explain complex concepts. The content is organized step by step to help you learn how to code in Python the correct way. The author has worked systematically to help you write better Python code.
You start with the installation of Python in the first chapter itself. And at the end of this chapter, you learn to write your first program in Python. Jumping straight to Python makes it easier for you to follow along. Plus, right through this book, Jupyter Notebook is used to write as well as explain the code. You are provided easy access to the datasets used in this book to facilitate quick learning.
You also work on three hands-on mini-projects:
- A Simple GUI-Based Calculator in Python
- Alarm Clock with Python
- Hangman Game in Python
The graphs, images, and scripts are clear and present you with easily understandable visuals to the text description. This book is a great option for self-study, even if you’re at the level of an intermediate learner.
Overall, you can trust this learning by doing book to help you accomplish your Python career goals faster.
The topics covered include:
- Environment Setup and Writing Your First Program in Python
- Python Variables and Data Types
- Python Operators
- Decision Making and Iteration Statements in Python
- Functions in Python
- Object-Oriented Programming with Python
- Exception Handling with Python
- Reading and Writing Data from Files and Sockets
- Regular Expressions in Python
- Some Useful Python Modules
- Creating Custom Modules in Python
- Creating GUI in Python
- Python Libraries for Data Science: NumPy, Pandas, and Matplotlib
Hit the BUY NOW button and begin your Python Learning journey.
Title Page Copyright How to contact us About the Publisher AI Publishing is Looking for Authors Like You Download the PDF version Get in Touch with Us Table of Contents Preface Book Approach Who Is This Book For? How to Use This Book? About the Author Chapter 1: Introduction 1.1. History of Python 1.2. Uses of Python 1.3. Commonly Used Python IDEs 1.4. Environment Setup 1.4.1. Windows Setup 1.4.2. Mac Setup 1.4.3. Linux Setup 1.4.4. Using Google Colab Cloud Environment 1.5. Writing Your First Program 1.6. Python Syntax Chapter 2: Python Variables and Data Types 2.1. Python Variables 2.2. Python Data Types 2.2.1. Numeric Types 2.2.2. Strings 2.2.3. Boolean Variables 2.2.4. Lists 2.2.5. Tuples 2.2.6. Dictionaries Exercise 2.1 Exercise 2.2 Chapter 3: Python Operators 3.1. What Are Python Operators 3.2. Arithmetic Operators 3.2.1. Addition Operator 3.2.2. Subtraction Operator 3.2.3. Multiplication Operator 3.2.4. Division Operator 3.2.5. Modulus Operator 3.2.6. Exponent Operator 3.3. Comparison Operators 3.3.1. Equality Operator 3.3.2. Inequality Operator 3.3.3. Greater Than Operator 3.3.4. Smaller Than Operator 3.3.5. Greater Than or Equals to Operator 3.3.6. Smaller Than or Equals to Operator 3.4. Assignment Operators 3.4.1. Assignment 3.4.2. Add and Assign 3.4.3. Subtract and Assign 3.4.4. Multiply and Assign 3.4.5. Divide and Assign 3.4.6. Take Modulus and Assign 3.4.7. Take Exponent and Assign 3.5. Logical Operators 3.5.1. AND Operator 3.5.2. OR Operator 3.5.3. NOT Operator 3.6. Membership Operators 3.6.1. The in Operator 3.6.2. The not in Operator 3.7. Identity Operators 3.7.1. The is Operator 3.7.2. The is not Operator Exercise 3.1 Exercise 3.2 Chapter 4: Decision Making and Iteration Statements in Python 4.1. Conditional Statements in Python 4.1.1. If and Else Statements 4.1.2. Elif Statements 4.1.3. Ternary Operator 4.1.4. Nesting Conditional Statements 4.2. Iteration Statements in Python 4.2.1. For Loop 4.2.2. While Loop 4.2.3. Nested Loops 4.2.4. Continue Pass and Break Statements 4.2.5. List Comprehensions in Python Exercise 4.1 Exercise 4.2 Chapter 5: Functions in Python 5.1. What Are Functions? 5.2. Defining and Calling Functions 5.3. Parameterized Functions 5.4. Returning Values from Functions 5.5. Global and Local Variables and Functions 5.6. Lambda Functions 5.7. Recursive Functions 5.8. Function Decorators 5.8.1. Returning a Function 5.8.2. Passing a Function as a Parameter 5.8.3. Creating Decorators 5.9. Iterators and Generators 5.9.1. Iterators 5.9.2. Generators Exercise 5.1 Exercise 5.2 Chapter 6: Object-Oriented Programming with Python 6.1. What Is Object-Oriented Programming? 6.2. Defining Classes and Creating Objects 6.3. Declaring Methods and Variables in a Class 6.4. Class Constructors 6.5. Class Members vs. Instance Members 6.6. Create Iterators Using Classes 6.7. Inheritance in Python 6.7.1. A Simple Example of Inheritance 6.7.2. An Advanced Example of Inheritance 6.7.3. Calling Parent Class Constructor via a Child Class 6.7.4. Polymorphism Exercise 6.1 Exercise 6.2 Chapter 7: Exception Handling with Python 7.1. What Are Exceptions? 7.2. Handling Multiple Exceptions 7.3. Individually Handling Different Exceptions 7.4. The Finally and Else Block 7.5. User-Defined Exceptions Exercise 7.1 Exercise 7.2 Chapter 8: Reading and Writing Data from Files and Sockets 8.1. Importing Files in Python 8.2. Working with Text Files 8.2.1. Reading Text Files 8.2.2. Writing/Creating Text Files 8.3. Working with CSV Files 8.3.1. Reading CSV Files 8.3.2. Writing CSV Files 8.4. Working with PDF Files 8.4.1. Reading PDF Files 8.4.2. Writing PDF Files 8.5. Sending and Receiving Data Over Sockets 8.5.1. Sending Data Through Sockets 8.5.2. Receiving Data Through a Socket Exercise 8.1 Exercise 8.2 Chapter 9: Regular Expressions in Python 9.1. What is Regex? 9.2. Specifying Patterns Using Meta Characters 9.2.1. Square Brackets [] 9.2.2. Period (.) 9.2.3. Carrot (^) and Dollar ($) 9.2.4. Plus (+) and Question Mark (+) 9.2.5. Alteration (|) and Grouping () 9.2.6. Backslash 9.2.7. Special Sequences 9.3. Regular Expression Functions in Python 9.3.1. The findall() function 9.3.2. The split() function 9.3.3. The sub() and the subn() functions 9.3.4. The search() Exercise 9.1 Exercise 9.2 Chapter 10: Some Useful Python Modules 10.1. Python Debugger 10.2. Collections Module 10.2.1. Counters 10.2.2. Default Dictionaries 10.2.3. Named Tuples 10.3. DateTime Module 10.3.1. Working with Time Only 10.3.2. Working Dates Only 10.4. Math Module 10.5. Random Module 10.6. Find Execution time of Python Scripts 10.6.1. Using Time Module 10.6.2. Using Timeit Module 10.6.3. The ##timeit Command Exercise 10.1 Exercise 10.2 Chapter 11: Creating Custom Modules in Python 11.1. Why You Need Modules? 11.2. Creating and Importing a Basic Module 11.3. Creating and Importing Multiple Modules 11.4. Adding Classes to Custom Modules 11.5. Importing Modules from a Different Path 11.6. Adding Modules to Python Path Exercise 11.1 Exercise 11.2 Chapter 12: Creating GUI in Python 12.1. Creating a Basic Window 12.2. Working with Widgets 12.2.1. Adding a Button 12.2.2. Adding a Text Field 12.2.3. Adding a Message Box 12.2.4. Adding Multiple Widgets 12.3. Creating a Layout Exercise 12.1 Exercise 12.2 Chapter 13: Useful Python Libraries for Data Science 13.1. NumPy Library for Numerical Computing 13.1.1. Creating NumPy Arrays 13.1.2. Reshaping NumPy Arrays 13.1.3. Array Indexing and Slicing 13.1.4. NumPy for Arithmetic Operations 13.1.5. NumPy for Linear Algebra Operations 13.2. Pandas Library for Data Analysis 13.2.1. Reading Data into Pandas Dataframe 13.2.2. Filtering Rows 13.2.3. Filtering Columns 13.2.4. Sorting Dataframes 13.3. Matplotlib for Data Visualization 13.3.1. Line Plots 13.3.2. Titles Labels and Legends 13.3.3. Scatter Plots 13.3.4. Bar Plots 13.3.5. Pie Charts Exercise 13.1 Exercise 13.2 Project 1: A Simple GUI-Based Calculator in Python Importing the Required Libraries Creating Main Window Adding Widgets and Logic Project 2: Alarm Clock with Python Importing the Required Libraries Creating Main Window Adding Widgets and Logic Project 3: Hangman Game in Python Importing the Required Libraries Creating Main Window Adding Widgets and Logic From the Same Publisher Exercise Solutions Exercise 2.1 Exercise 2.2 Exercise 3.1 Exercise 3.2 Exercise 4.1 Exercise 4.2 Exercise 5.1 Exercise 5.2 Exercise 6.1 Exercise 6.2 Exercise 7.1 Exercise 7.2 Exercise 8.1 Exercise 8.2 Exercise 9.1 Exercise 9.2 Exercise 10.1 Exercise 10.2 Exercise 11.1 Exercise 11.2 Exercise 12.1 Exercise 12.2 Exercise 13.1 Exercise 13.2 Back Cover
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