Subject Guides: Data Science: Working with Python

Download Python

In order to get started, you'll need to download Python. You can download Python by itself from the Python Software Foundation here or you can install the Anaconda distribution of Python. Anaconda includes Python, Jupyter notebooks capability, many pre-installed Python packages, and more, making it easy to get started quickly.

Python Libraries

Python has a lot of pre-existing packages (also called libraries), written by other Python users and available for installation. You can find Python packages on PyPI, the Python Package Index.

This overview of popular Python libraries provides a starting point for finding applicable libraries. For more advanced users, this comprehensive list of packages by topic includes links to further resources.

If using the Anaconda distribution of Python, many libraries come pre-installed. This tutorial covers the steps needed to install additional packages.

AU Library Search

Introductory Materials

Plotting and Programming in Python (Software Carpentry)

This series of lessons from Software Carpentry is a great resource for beginners. The focus is on working with one data set from start to end. Highlighted packages include pandas and matplotlib.

Python for Everybody

Materials for learning Python. You can take the course through several different platforms for free to get a certificate.

Learn Python the Hard Way by Zed Shaw
Call Number: QA76.73.P98 S53 2014
ISBN: 9780321884916
Publication Date: 2013-10-01
In Learn Python the Hard Way, Third Edition, you'll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you'll learn how software works; what good programs look like; how to read, write, and think about code; and how to find and fix your mistakes using tricks professional programmers use.
Learn Python Programming by Fabrizio Romano; Heinrich Kruger
Call Number: Online
ISBN: 9781801815093
Publication Date: 2023-01-01
Learn Python Programming, Third Edition is both a theoretical and practical introduction to Python, an extremely flexible and powerful programming language that can be applied to many disciplines. This book will make learning Python easy and give you a thorough understanding of the language. You'll learn how to write programs, build modern APIs, and work with data by using renowned Python data science libraries. This book is for everyone who wants to learn Python from scratch, as well as experienced programmers looking for a reference book. Prior knowledge of basic programming concepts will help you follow along, but it's not a prerequisite.

Advanced Materials

The library has a lot of eBooks on Python. The following titles are just a small selection. Please search our catalog to find many more options or use the AU Library Search bar on the left.

Advanced Python Programming by Quan Nguyen
Call Number: Online
ISBN: 1801814015
Publication Date: 2022-03-25
Pythons powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages. In this book, youll explore the tools that allow you to improve performance and take your Python programs to the next level.
Python for Geeks by Muhammad Asif
Call Number: Online
ISBN: 1801070113
Publication Date: 2021-10-20
Python for Geeks will teach you how to advance in your career with the help of expert tips and tricks. By the end of this Python book, you'll be able to do some serious Python programming for large-scale complex projects. Prior experience with Python will help you get the most out of this book.
Advanced Python Development by Matthew Wilkes
Call Number: Online
ISBN: 1484257928
Publication Date: 2020-07-26
This book builds on basic Python tutorials to explain various Python language features that aren't routinely covered: from reusable console scripts that play double duty as micro-services by leveraging entry points, to using asyncio efficiently to collate data from a large number of sources. Along the way, it covers type-hint based linting, low-overhead testing and other automated quality checking to demonstrate a robust real-world development process. Who This Book Is For: Developers at the mid to senior level who already have Python experience.

Jupyter Notebook Tutorials

28 Jupyter Notebook tips, tricks, and shortcuts
Topics include keyboard shortcuts, adjusting output display of variables, IPython magic commands, and more.
Advanced Jupyter notebook tricks (part 1)
Topics include running different languages (e.g., R) in in notebook cells, batching notebooks runs, and exporting notebooks as HTML.
Advanced Jupyter notebook tricks (part 2)
This article covers building interactive dashboards with Jupyter using ipywidgets.
Markdown cheatsheet
This is meant to be a quick reference guide for Markdown syntax. Add headers, emphasis, lists, links, tables, videos, and more.
Ten Simple Rules for Reproducible Research in Jupyter Notebooks
This pre-print lays out 10 guidelines for effectively using Jupyter notebooks in the context of reproducible research.