Python

Python Crash Courses

University Libraries at the University of North Carolina at Chapel Hill
UNC Research Computing

Setup

Installing the Anaconda Distribution.

If you run into problems during installation, please come 30 minutes early to the first session for help.

View our introductory orientation to Python and Spyder (YouTube) before Week 1.

Basics

Week 1

We’ll introduce fundamental Python concepts like variables, object types, and indexing.

Week 2

We’ll return to the Introductory Materials to review fundamental concepts, packages, file paths, and a few important extensions, then we’ll work through an example using data on COVID-19.

Practice Exercises (Introduction)

Exercises
Solutions

Intro to Data

Week 3

We’ll introduce a format for literate programming: Jupyter Notebooks. Then, we’ll get started with Pandas for Data in Python.

Week 4

We’ll continue with Pandas and explore some visualization tools by applying them to some simple research questions about a dataset.

Week 5

We’ll finish up some topics in Pandas and base Python, and survey some other useful tools.

Pandas Exercises

Exercises
Solutions

Getting Help!

• Davis Library Research Hub
• Odum Statistical Walk-in Help
• Research Computing (and UNC’s clusters)
  • Open OnDemand (Longleaf Access Required)

References and Resources

• Automate the Boring Stuff with Python
• Python Cheatsheets
• Python Programming for the Humanities
• Python Data Science Handbook This free ebook emphasizes Numpy, Scipy, Matplotlib, Pandas and other data analysis packages in Python, assuming some familiarity with the basic principles of the language.
  • Whirlwind Tour of Python
• University Libraries’ Text and Data Mining Guide
• Stack Overflow
• Google!

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