2020: GitHub / website (inc., Astropy, Pandas, Altair, Git/Github, linear regression, resampling, and debugging)

2021: GitHub / website (inc., Astropy and Pandas)

2022: GitHub / website (inc., Astropy and Pandas)

2023: GitHub / website

Welcome to the 2023 AstroPGH Python Boot Camp for summer undergraduate students and early PhD students new to Python. This 3 day program is designed to help you learn the basics of using Python for astrophysics and physics research.

Boot Camp

Installation and Setup

Python

Please install Python 3 before the Boot Camp. I recommend using the Anaconda package manager for Python 3.10 and then install the following packages in the terminal:

conda install numpy scipy astropy matplotlib jupyter ipython pandas
conda install -c conda-forge jupyterlab

• Conda Users Guide

Test Your Installation

1. Open a new terminal.
2. Type ipython into the terminal to open an interactive python session (the prompt should say In [1]:).
3. Copy this code:

   import numpy
   import scipy
   import matplotlib
   import astropy
   import pandas
   

4. Type into the iPython shell the word paste, and press enter.
5. If no errors are raised, you’re ready for bootcamp. You may close the terminal window.

If you are having difficulties with installation, please do not hesitate to reach out to Brett Andrews on Slack or via email.

Instructors

• Brett Andrews: Organizer
• Yasha Kaushal: Python Basics
• Bob Caddy: Data Structures
• Marcell Howard: Functions and Modules
• Lina Florez: Matplotlib
• Yoki Salcedo: Numpy 1a
• Alan Pearl: Numpy 1b
• Travis Court: Numpy 2a
• Sedona Price: Numpy 2b
• Emily Biermann: Numpy 3a
• Collin McLeod: Numpy 3b
• Helena Richie: Numpy 4a
• David Setton: Numpy 4b

Schedule

Time (EDT)	Monday (5/22)	Tuesday (5/23)	Wednesday (5/24)
10:00-11:15	Python Basics	Numpy 1a	Numpy 3a
11:45-1:00	Data Structures	Numpy 1b	Numpy 3b
2:00-3:15	Functions and Modules	Numpy 2a	Numpy 4a
3:45-5:00	Matplotlib	Numpy 2b	Numpy 4b

This material is based upon work supported by the National Science Foundation grant number AST-2009251. Any opinions, findings, and conclusions or recommendations expressed on this website are those of the participants and do not necessarily reflect the views of the National Science Foundation or the participating institutions.