Python For Beginners. 2 Books in 1: A Completed Guide to Master the Basics of Python Language Programming and Data Science. Learn Coding Fast with Examples and Tips

✍ Scribed by Julian McKinnon

• Tongue: English
• Leaves: 370
• Category: Library

✦ Synopsis

Included in this Book Collection are:

Book N.1: Python Programming for Beginners: A Step-by-Step Guide to Learn one of the Most Popular and Easy Programming Languages. Learn Basic Python Coding Fast with Examples and Tips

This book gives a comprehensive guide on the following:

• The basic background of python
• Data types in python
• Operators - the types and their uses
• Loops and functions
• Exception handling
• Variable scope and lifetime in python functions
• Modules
• Working with files
• Object-oriented programming
• Real-world examples of python
• Getting started; python tips and tricks
• Common programming challenges
• ... AND MORE!!!

Book N.2 Data Science with Python: The Ultimate Step-by-Step Guide for Beginners to Learn Python for Data Science

This book gives a comprehensive guide on the following:

• What is data science?
• Basics of python
• The best python libraries for data science
• Data science and applications
• The lifecycle of data science
• Probability, statistics and data types
• Most common data science problems
• Comparison of python with other languages
• Data cleaning and preparation
• Data visualization
• ... AND MORE!!!

✦ Table of Contents

Python For Beginners
PYTHON PROGRAMMING
Introduction
The Parts You Should Know about the Python Code
Getting That Environment Set Up
Chapter 1. Basic Background of Python
What Is Python?
Why Python?
Installing Python
Using a Text Editor
Using an IDE
Your First Program
Code Comments and Your Program
Chapter 2. Data Types in Python
Strings
Numeric Data Type
Booleans
List
Variables
User-Input Values
Chapter 3. Operators - The Types and Their Uses
The Types
The Operator Precedence
The Logical Operators
Chapter 4. Loops and Functions
LOOPS
Nested if Statements in Python
For Loop in Python
Range() Function in Python
Using for Loop with Else
While Loop in Python
Using While Loop with Else
Python’s Break and Continue
Continue Statement in Python
Pass Statement in Python
Functions in Python
Calling a Function in Python
Docstring
Python Function Return Statement
Random Function in Python
Iterators
Manually Iterating Through Items in Python
Explaining the Loop
Creating Custom Iterator in Python
Infinite Iterators
Closure Function in Python
Projects - Implementing Simple Calculator in Python
Chapter 5. Exception Handling
What Is Exception Handling?
Handling the Zero Division Error Exception
Using Try-Except Blocks
Reading an Exception Error Trace Back
Using Exceptions to Prevent Crashes
The Else Block
Failing Silently
Handling the File Not Found Exception Error
Checking If File Exists
Try and Except
Creating a New File
Chapter 6. Variable Scope and Lifetime in Python Functions
Function Types
Keywords Arguments in Python
Arbitrary Arguments
Recursion in Python
Python Anonymous Function
Python’s Global, Local and Nonlocal
Creating a Local Variable in Python
Python’s Global and Local Variable
Python’s Nonlocal Variables
Global Keyword in Python
Creating Global Variables across Python Modules
Python Modules
Module Import
Import Statement in Python
Importing All Names
Module Search Path in Python
Reloading a Module
Dir() built-in Python function
Python Package
Number Conversion
Type Conversion
Mathematics in Python
Random Function in Python
Lists in Python
Nested Lists
Accessing Elements from a List
Chapter 7. Modules
How to Create a Module?
Import Statement
Locate a Module
Syntax of PYTHONPATH
Chapter 8. Working with Files
Reading from a File
File Pointer
File Access Modes
Writing to a File
Practice Exercise
Summary
Chapter 9. Object-Oriented Programming
Classes and Objects
Chapter 10. Real-World Examples of Python
Data Science
Machine Learning
Applications in Web Development
Automation
Things We Can Do in Python
Comment
Reading and Writing
Files
Integers
Triple Quotes
Variables
The Scope of a Variable
Modifying Values
The Assignment Operator
Chapter 11. Getting Started; Python Tips and Tricks
Web Scraping
Chapter 12. Common Programming Challenges
Debugging
Working Smart
User Experience
Estimates
Constant Updates
Problems Communicating
Security Concerns
Relying on Foreign Code
Lack of Planning
Finally
Conclusion
Introduction
Effectiveness of Libraries for Python
There Is Always Someone Available to Help in the Python Community
Chapter 1: What Is Data Science?
The Importance of Data Science
How Is Data Science Used?
The Lifecycle of Data Science
The Components of Data Science
Chapter 2: Basics of Python
Python IDEs
Getting Started with Python
Data Types
Functions and Modules
Object-Oriented Programming
Class Inheritance
Regular Expressions
Match and Search Functions
Exception Handling
File Handling
Chapter 3: The Best Python Libraries for Data Science
Core Libraries and Statistics
Visualization
Machine Learning Libraries
Deep Learning
Chapter 4: Data Science and Applications
Banking and Finance
Health and Medicine
Oil and Gas
The Internet
Travel and Tourism
Chapter 5: The Lifecycle of Data Science
The Discovery Phase
The Data Preparation Phase
The Model Planning Phase
The Operationalize Phase
The Communicate Results Phase
Chapter 6: Probability, Statistics, and Data Types
Real-Life Probability Examples
Statistics
Data Types
The Importance of Data Types
Statistical Methods
Descriptive Statistics
Chapter 7: Most Common Data Science Problems
Management Expects the World
Misunderstanding How Data Works
Taking the Blame for Bad News
Communication as a Solution
Chapter 8: Comparison of Python with Other Languages
Python versus Java comparison
Python versus C#
Python versus JavaScript
Python versus Perl
Python versus Tcl
Python versus Smalltalk
Python versus C++
Python versus Common Lisp and Scheme
Python versus Node.js
Coding Everything in JavaScript
Python versus PHP
Chapter 9: Data Cleaning and Preparation
What Is Data Preparation?
Why Do I Need Data Preparation?
What Are the Steps for Data Preparation?
Handling the Missing Data
Chapter 10: Data Visualization
Data Visualization to the End-User
Matplotlib
Visualization Using Pandas
The Objective of Visualization
The Simplest Method to Complex Visualization of Data
Overview of Plotly
Heat Maps
Conclusion