ASTR 302, Winter 2018, University of Washington:

Python for Astronomy

Andrew Connolly

Location

• When: 11:00-12:20, Monday & Wednesday, Winter quarter 2019
• Where: PAB 360 (Physics-Astronomy Computer Lab)

Class Materials

• Syllabus and course description
• Lectures
• Homeworks

Class Description and Objectives

ASTR 302, “Python for Astronomy”, is a new course designed to teach how to effectively use Python for research and astronomical data analysis. We will begin with a gentle introduction to key tools and libraries used in astronomy, use these to analyze data (from kilobytes to tens of gigabytes!), visualize (sometimes large) datasets, automate analyses, and apply what we’ve learned to reproduce results of some key astronomy papers.

This course assumes the knowledge of Python and related astronomy libraries at the ASTR 300 level. It will give you the broad foundation needed to proceed to “ASTR 324: Introduction to AstroStatistics and Big Data in Astronomy”, or ASTR 497 “Big Data in Astronomy: Hands-on with Large Surveys”, or independent research projects.

By the end of this class you should expect to be able to:

• Use git and github to manage your code development
• Make use of Jupyter to develop and visualize your algorithms
• Run programs from the command-line and in a browser
• Query a database using SQL from the command-line or in a program
• Use Pandas and Scikit-learn to analyze your data

Class and Office hours

The grade will be broken down as:

• Homework 70%
• Final Project 30%
• There will be no final exam

Office hours are on a drop in basis and by appointment. My office is in the Physics and Astronomy building (B355). If the door is open feel free to drop in, or send me an email to arrange a time.

Useful Textbooks

We will largely rely on material freely available on the web; however, these two books may be useful for a more in-depth dive:

• Lutz: Learning Python
• VanderPlas: Python Data Science Handbook

(note: both are freely available as e-books through UW University Libraries).