Python Overview

About this repo

• notebooks/
  • src/: Folder containing raw python code created from the .ipynb files
  • Notebook Overview.ipynb: Information about the Jupyter notebook environment
  • Pandas Overview.ipynb: Overview of the pandas module for data manipulation
  • Practical Examples.ipynb: Some useful scenarios in Python
  • Python Basics.ipynb: Demonstrating basic Python functionality
  • blank.ipynb: Blank notebook to experiment with
• readme.md: You're reading it!
• reference.md: List of helpful tutorials / resources to get started with Python
• requirements.txt: List of python modules needed in order to run the .ipynb files in Binder

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Agenda:

Why are we here?

• Interest from my team after I demonstrated the UAT process in Python

What is Python?

• General purpose programming language
• Readable and beginner friendly
• Free to use
• Common in data science / ml

What can Python be used for?

• Manipulating data files (.csv, .xlsx, .json, .accdb, SQL DB)
• Solving equations / factoring / derivatives / integration
• Web scraping
• Trading stocks (dangerous)
• Automation
• Creating visualizations

Advantages

• Batteries included
• Concise syntax
• OS neutral
  • Mac / Windows / Linux
• Popular language = active support community

Gotchas / Drawbacks

• "Slow" / difficult to manage memory
  • Not really an issue for the practical things I'll be outlining
• Dynamically typed
  • Less explicit

What I will (and won't) be covering

• Yes
  • Demonstrate the types of problems Python can solve and be helpful with
  • Jupyter Notebook environment
  • Python basics
  • Rectangular data with pandas
  • Practical examples
  • Resources to learn more
• No
  • Setting up a Python environment
  • In depth explanation of python syntax

My Experience

• 3 / 4 years
• Learned by doing
  • pdf scraper
  • Recommender system
  • Bitcoin price logger
• Not an expert and not a software developer

Demo

• 

Potential Future Topics

• Version controlling notebooks
• sklearn
• statsmodels
• seaborn
• matplotlib
• BeautifulSoup
• Testing code with doctest