Programming Across Disciplines

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Python Across Disciplines
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Table of Contents

1.1.   Introduction 1.2.   About the Author & Contact Info 1.3.   Book Conventions 1.4.   What (Who) is a Programmer? 1.5.   Programming Across Disciplines 1.6.   Foundational Computing Concepts 1.7.   About Python 1.8.   First Steps 1.8.1 Computer Setup 1.8.2 Python print() Function 1.8.3 Comments
2.1. About Data 2.2. Data Types 2.3. Variables 2.4. User Input 2.5. Data Structures (DS)         2.5.1. DS Concepts         2.5.2. Lists         2.5.3. Dictionaries         2.5.4. Others 2.6. Files         2.6.1. Files & File Systems         2.6.2. Python File Object         2.6.3. Data Files 2.7. Databases
3.1. About Processing 3.2. Decisions         3.2.1 Decision Concepts         3.2.2 Conditions & Booleans         3.2.3 if Statements         3.2.4 if-else Statements         3.2.5 if-elif-else Statements         3.2.6 In-Line if Statements 3.3. Repetition (a.k.a. Loops)         3.3.1 Repetition Concepts         3.3.2 while Loops         3.3.3 for Loops         3.3.4 Nested Loops         3.3.5 Validating User Input 3.4. Functions         3.4.1 Function Concepts         3.4.2 Built-In Functions         3.4.3 Programmer Defined Functions 3.5. Libraries         3.5.1 Library Concepts         3.5.2 Standard Library         3.5.3 External Libraries 3.6. Processing Case Studies         3.6.1 Case Studies         3.6.2 Parsing Data
4.1. About Output 4.2. Advanced Printing 4.3. Data Visualization   4.4 Sound
  4.5 Graphics
  4.6 Video
  4.7 Web Output
  4.8 PDFs & Documents
  4.9 Dashboards
  4.10 Animation & Games
  4.11 Text to Speech

5.1 About Disciplines 5.2 Accounting 5.3 Architecture 5.4 Art 5.5 Artificial Intelligence (AI) 5.6 Autonomous Vehicles 5.7 Bioinformatics 5.8 Biology 5.9 Bitcoin 5.10 Blockchain 5.11 Business 5.12 Business Analytics 5.13 Chemistry 5.14 Communication 5.15 Computational Photography 5.16 Computer Science 5.17 Creative Writing 5.18 Cryptocurrency 5.19 Cultural Studies 5.20 Data Analytics 5.21 Data Engineering 5.22 Data Science 5.23 Data Visualization 5.24 Drone Piloting 5.25 Economics 5.26 Education 5.27 Engineering 5.28 English 5.29 Entrepreneurship 5.30 Environmental Studies 5.31 Exercise Science 5.32 Film 5.33 Finance 5.34 Gaming 5.35 Gender Studies 5.36 Genetics 5.37 Geography 5.38 Geology 5.39 Geospatial Analysis ☯ 5.40 History 5.41 Humanities 5.42 Information Systems 5.43 Languages 5.44 Law 5.45 Linguistics 5.46 Literature 5.47 Machine Learning 5.48 Management 5.49 Marketing 5.50 Mathematics 5.51 Medicine 5.52 Military 5.53 Model Railroading 5.54 Music 5.55 Natural Language Processing (NLP) 5.56 Network Analysis 5.57 Neural Networks 5.58 Neurology 5.59 Nursing 5.60 Pharmacology 5.61 Philosophy 5.62 Physiology 5.63 Politics 5.64 Psychiatry 5.65 Psychology 5.66 Real Estate 5.67 Recreation 5.68 Remote Control (RC) Vehicles 5.69 Rhetoric 5.70 Science 5.71 Sociology 5.72 Sports 5.73 Stock Trading 5.74 Text Mining 5.75 Weather 5.76 Writing
6.1. Databases         6.1.1 Overview of Databases         6.1.2 SQLite Databases         6.1.3 Querying a SQLite Database         6.1.4 CRUD Operations with SQLite         6.1.5 Connecting to Other Databases
Built-In Functions Conceptss Data Types Date & Time Format Codes Dictionary Methods Escape Sequences File Access Modes File Object Methods Python Keywords List Methods Operators Set Methods String Methods Tuple Methods Glossary Index Appendices   Software Install & Setup
  Coding Tools:
  A.  Python ↗   B.  Google CoLaboratory ↗   C.  Visual Studio Code ↗   D.  PyCharm IDE ↗   E.  Git ↗   F.  GitHub ↗
  Database Tools:
  G.  SQLite Database ↗   H.  MySQL Database ↗

Python Across Disciplines
by John Gordon © 2023

Table of Contents

6.0 Chapter Overview     6.1. Databases
        6.1.1 Overview of Databases         6.1.2 SQLite Databases         6.1.3 Querying a SQLite Database         6.1.4 CRUD Operations w/SQLite         6.1.5 Connecting to Other Databases     6.2. Object Oriented Programming
            6.2.1. Introduction to OOP             6.2.2. Unified Modeling Language             6.2.3. Classes & Objects             6.2.4. Abstraction             6.2.5. Encapsulation             6.2.6. Inheritance             6.2.7. Polymorphism             6.2.8. Exception Handling             6.2.9. Codealong: Employees             6.2.10. Codealong: Cars     6.3. Graphical User Interfaces
            6.3.1. Introduction to GUIs
            6.3.2. Tkinter
            6.3.3. Codealong: Login Form
            6.3.4. Codealong: Data Entry Form
    6.4. Algorithms & Data Structures
            6.4.1. Introduction to Algorithms
            6.4.2. Searching
            6.4.3. Sorting
            6.4.4. Metrics
            6.4.5. Nodes
            6.4.6. Linked Lists 1
            6.4.7. Linked Lists 2
            6.4.8. Stacks
            6.4.9. Queues
            6.4.10. Heaps
            6.4.11. Trees
            6.4.12. Graphs
            6.4.13. Maps
            6.4.14. Hashing
            6.4.15. Cryptography
    6.5. Additional Advanced Topics
            6.5.1. APIs
            6.5.2. Automation
            6.5.3. Recursion
            6.5.4. More About Datasets
            6.5.5. Large Language Models
            6.5.6. Text Analysis
            6.5.7. Web Scraping
            6.5.8. Data Science
            6.5.9. Machline Learning
            6.5.10. Natural Lang Processing
            6.5.11. Artificial Intelligence
            6.5.12. Cython
            6.5.13. PyPy
            6.5.14. Multi-Threading
            6.5.15. Parallel Processing

Table of Contents » Reference Materials : Tuple Methods

Tuple Methods

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Python tuples are immutable sequences, and they have a limited set of methods reflecting their simplicity and immutability. The primary methods include count(value), which returns the number of times a specified value appears in the tuple, and index(value, [start, [end]]), which finds the first occurrence of a specified value and can optionally be restricted to a subsequence of the tuple. Due to the immutable nature of tuples, methods that modify the data, like those found in lists, are absent. This limited set of methods ensures that tuples remain a fast, lightweight, and reliable data structure for storing ordered, unchangeable sequences of elements, making them ideal for storing data that should not be modified, like coordinates or fixed configurations.

Tuple Method	Description
count()	Returns the number of times var appears in the list. General Form: `tuple_var.count(var)`
index()	Returns the index of the first element with the specified value (var). General Form: `tuple_var.index(var)`

© 2023 John Gordon
Cascade Street Publishing, LLC