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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

Table of Contents  »  Chapter 2 : Data (Input) : Data Types : Integers

Integers

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Contents

Overview

An integer in the context of programming and mathematics is a whole number (sometimes called a counting number) that can be positive, negative, or zero, but it does not include any fractional or decimal parts. In programming languages like Python, an integer is a fundamental data type that is used to represent these whole numbers. Integers are used extensively in various types of calculations and loops, as well as in indexing and more complex mathematical operations. I

Precision

In most programming languages, integers have a certain range of values they can represent, determined by the number of bits allocated for storing them in memory. In Python, however, integers have unlimited precision, meaning they can grow to have as many digits as needed, limited only by the available memory. This is a significant benefit of Python, this means we can specify an integer of (virtually) any length.

Examples of Integers in Python:

Mathematical Operations

In Python, we can perform mathematical calculations using Integers using operators which are symbols to represent valid arithmatic operations for integer values. Here are the first of these that we will explore:

Operation Operator Description & Examples
Addition
+

Combining two or more numeric values into a single total sum.

print(10 + 20)
print(10 + 20 + 30)
print(10 + 20 + 30 + 40 + 50 + 60)
Subtraction
-

Taking away one numeric value (or quantity) from another to find the difference between them.

print(20 - 10)
print(30 - 20 - 10)
print(10 - 20)
print(10 - 20 - 30)
Multiplication
*

Adding a number a certain number of times to produce a product.

print(10 * 20)
print(10 * 20 * 30)
print(10 * 20 * 30 * 40 * 50 * 60)
Division
/

Splitting a number into a specified number (the divisior) of equal parts. The result of dividing two integers (such as 10 / 3) will result in a fractional (decimal) part in the result, which is relevant related to data types. Integer division that results in a fractionl part will produce a floating point result. In computing, division by zero will cause an error because division by zero is mathematicaly undefined.

print(10 / 2)  # Note the result is an int
print(10 / 3)  # Note the result is a float (int part and decimal part)
print(10 / 0)  # Note that this example produces an error as the divisor cannot be zero because division by zero is undefined.
Floor (Integer) Division
//

The same as division (above), however the result will be an integer and any fractional (decimal) part in the result will be discarded.

print(10 // 2)  # Note the result is an int
print(10 // 3)  # Note the result is an int, the decimal part was discarded
Modulus
%

Same as division (above), however it determins if there is a remainder in the result of a division operation.

print(10 % 2)  # Note the result is zero because there is no remainder after the division
print(10 % 3)  # Note the result is 1 because there is a remainder after the division
Exponentiation
**

This operation raises the first number (the base) to the power of the second number (the exponent). The exponent signifies how many times the base is multiplied by itself.

print(10 ** 2)
print(10 ** 3)
print(10 ** 100)

Combining Operations

Any of the mathematical operators can be used in more complex (combined) mathematical calculations. Here are some examples:

print(10 + 20 - 15 * 5)
print(10 + (100 / 2))  # See the note about the use of parenthses below
print(10 ** (2 * 30)))  # See the note about the use of parenthses below

Order of Operations

In Python, the order of operations for mathematical operators follows the conventional mathematical hierarchy, which is consistent with the rules of arithmetic that are typically taught in mathematics (often remembered by the acronym PEMDAS/BODMAS). For the operators you've listed (+, -, *, /, //, %, and **), the order of precedence is as follows:

Parenthses

In Python, like math, we can use parenthses ( ) to isolate and group factors of our equations to override andn control the order of operations. See the examples in the Combining Operations section above.







© 2023 John Gordon
Cascade Street Publishing, LLC