📔
intro-to-python
  • An Introduction to Programming in Python (for Business Students)
  • exercises
    • Data Flow Diagramming Exercise
    • Developer Collaboration Exercise
    • README
    • "Web App" Exercise
      • checkpoints
        • Checkpoint 5: Bootstrap Layout
        • Checkpoint 4: Submitting Data from Web Forms
        • Checkpoint 3: Rendering HTML Pages
        • Checkpoint 1: Routing
        • Checkpoint 2: Modular Organization
      • "Web App" Exercise - Further Exploration
    • hello-world
      • "Hello World (Local)" Exercise
      • "Hello World (Local w/ Version Control)" Exercise
      • "Hello World (Colab)" Exercise
    • "Interface Capabilities" Exercise
    • "Continuous Integration 1, 2, 3" Exercise
    • "Web Service" Exercise
      • "Web Service" Exercise - Further Exploration
    • "Testing 1, 2, 3" Exercise
    • "Command-line Computing" Exercise
      • "Command-line Computing" Exercise
      • Professor Rossetti's Mac Terminal Configuration
      • Command-line Computing Exercise
    • "Codebase Cleanup" Assignment
    • "List Comprehensions" Exercise
    • "Groceries" Exercise
      • Python Datatypes (a.k.a. "Groceries") Exercise
      • Python Datatypes (a.k.a. "Groceries") Exercise
    • "Rock, Paper, Scissors" Exercise
      • "Rock, Paper, Scissors" Exercise
    • README
    • "Monthly Sales Predictions" Exercise
    • Setting up your Local Development Environment
    • "Chart Gallery" Exercise
    • "Run the App" Exercise
    • "Web Requests" Exercise
    • "API Client" Exercise
    • "Custom Functions" Exercise
    • Process Diagramming Exercise
  • notes
    • python
      • packages
        • The bigquery Package
        • The PySimpleGUI Package
        • The dotenv Package
        • The matplotlib Package
        • The requests Package
        • The altair Package
        • The gspread Package
        • The PyMySQL Package
        • The psycopg2 Package
        • The selenium Package
        • The seaborn Package
        • The pytest Package
        • The SpeechRecognition Package
        • The flask Package
        • The pandas Package
        • The spotipy Package
        • The pipenv Package
        • The nltk Package
        • The sqlalchemy Package
        • The pymongo Package
        • The plotly Package
        • The BeautifulSoup Package
        • The sendgrid Package
        • The fpdf Package
        • The autopep8 Package
        • The tweepy Package
        • The twilio Package
        • The tkinter Package
      • Python Datatypes Overview
        • Numbers
        • Classes
        • Dates and Times
        • Strings
        • None
        • Dictionaries
        • Booleans
        • Lists
        • Class Inheritance
      • Control Flow
      • Python Modules
        • The webbrowser Module
        • The time Module
        • The csv Module
        • The sqlite3 Module
        • The itertools Module
        • The json Module
        • The math Module
        • The os Module
        • The statistics Module
        • The random Module
        • The pprint Module
        • The datetime Module
        • The collections Module
      • Printing and Logging
      • Comments
      • Syntax and Style
      • Functions
      • Variables
      • Errors
      • Docstrings
      • File Management
      • User Inputs
      • Debugging
    • clis
      • The git Utility
      • Heroku, and the heroku Utility
      • Anaconda
      • The chromedriver Utility
      • The brew Utility (Mac OS)
      • The pdftotext Utility
      • The python Utility
      • The pip Utility
    • Software
      • Software Licensing
      • Software Documentation
      • Software Ethics
      • Software Testing Overview
      • Application Programming Interfaces (APIs)
      • Software Version Control
      • Software Refactoring Overview
    • devtools
      • The VS Code Text Editor
      • Code Climate
      • Travis CI
      • GitHub Desktop Software
      • Git Bash
      • Google Colab
    • Information Systems
      • Computer Networks
      • Processes
      • Datastores
      • Information Security and Privacy
      • People
    • Technology Project Management
      • Project Management Tools and Techniques
      • The Systems Development Lifecycle (SDLC)
    • hardware
      • Servers
    • Environment Variables
  • projects
    • "Executive Dashboard" Project
      • testing
      • "Exec Dash" Further Exploration Challenges
    • The Self-Directed (a.k.a "Freestyle") Project
      • "Freestyle" Project - Demonstration
      • "Freestyle" Project - Implementation (TECH 2335 Version)
      • "Freestyle" Project - Implementation
      • "Freestyle" Project Proposal
      • plan
    • "Robo Advisor" Project
      • Robo Advisor Project - Automated Testing Challenges
      • "Robo Advisor" Further Exploration Challenges
    • "Shopping Cart" Project
      • "Shopping Cart" Project - Automated Testing Challenges
      • "Shopping Cart" Further Exploration Challenges
      • "Shopping Cart" Project Checkpoints
  • License
  • Exam Prep
  • units
    • Unit 4B: User Interfaces and Experiences (Bonus Material)
    • Unit 5b: Databases and Datastores
    • Module 1 Review
    • Unit 7b: Processing Data from the Internet (Bonus Material)
    • Unit 9: Software Products and Services
    • Unit 8: Software Maintenance and Quality Control
    • Unit 7: Processing Data from the Internet
    • Unit 6: Data Visualization
    • Unit 5: Processing CSV Data
    • Unit 4: User Interfaces and Experiences
    • Unit 3: Python Datatypes
    • Unit 12: Project Presentations
    • Unit 2: Python Language Overview
    • Unit 11: Project Implementation Sprint
    • Unit 1: The Python Development Environment
    • Unit 10: Software Planning, Analysis, and Design
    • Unit 0: Onboarding
    • Unit 5B: Advanced Data Analytics
  • Contributor's Guide
Powered by GitBook
On this page
  • Numeric Operations
  • Formatting as Currency
  • Advanced Operations

Was this helpful?

  1. notes
  2. python
  3. Python Datatypes Overview

Numbers

PreviousPython Datatypes OverviewNextClasses

Last updated 4 years ago

Was this helpful?

Reference: .

100 #> 100
-100 #> -100
0.45 #> 0.45

Numeric Operations

Numeric functions include the usual arithmetic operators:

100 + 5 #> 105
100 - 5 #> 95
100 * 5 #> 500
100 / 5 #> 20
100 + 5 * 2 #> 110
(100 + 5) * 2 #> 210

Boolean equality operators also apply:

100 == 100 #> True
100 == 100.0 #> True
100 == 99 #> False
100 == (99 + 1) #> True
True == 1 #> True
False == 0 #> True
round(4.5) #> 5.0
round(4.49) #> 4.0

round(4.49, 0) #> 4.0
round(4.49, 1) #> 4.5
round(4.49, 2) #> 4.49

Formatting as Currency

# using the format function:
"the price is ${0:.2f}".format(6.5) #> 'the price is $6.50'
"the price is ${0:,.2f}".format(1234567890.12345678) #> 'the price is $1,234,567,890.12'

# alternatively using a format string:
price = 6.5
f"the price is ${price:,.2f}" #> 'the price is $6.50'

price = 1234567890.12345678
f"the price is ${price:,.2f}" #> 'the price is $1,234,567,890.12'

Feel free to use (copy-paste) this function definition into your projects:

def to_usd(my_price):
    """
    Converts a numeric value to usd-formatted string, for printing and display purposes.

    Param: my_price (int or float) like 4000.444444

    Example: to_usd(4000.444444)

    Returns: $4,000.44
    """
    return f"${my_price:,.2f}" #> $12,000.71

Advanced Operations

Also reference the numeric functionality of these built-in Python modules:

Also reference the built-in round() function: .

Use to control how numbers will display when printed:

https://docs.python.org/3/library/stdtypes.html#numeric-types-int-float-complex
https://docs.python.org/3/library/functions.html#round
string formatting
math
random
statistics