These are programming tutorials for the Boulder Solar REU. Ultimately, the goal is to help you feel comfortable manipulating data for your research. The tutorials begin with significant instruction. As they progress, they guide you towards solving independent programming tasks.
python-intro/2024: These notebooks are part of the 2024 Python tutorial. Challenges.ipynb contains some coding challenges if you're already experienced in Python, or want some additional practice. Python_101_presenter_view.ipynb is used for the presentation, but isn't intended for use during the Python 101 tutorial. Feel free to use it as reference afterwards.
python-intro/2022: These notebooks are from 2022's tutorial, and provide an applications-based comprehensive overview of Python as a programming language. python_tutorial_1.ipynb covers how to navigate Jupyter notebooks, write and evaluate basic expressions in Python, variables and variable types, commenting, and breaking down Python code into smaller parts to understand it. python_tutorial_2.ipynb covers manipulating strings, invoking methods, working with arrays, and user-defined functions.
These notebooks are good to use for future reference or if you don't understand some aspect of the tutorial. They can be worked through independently for additional practice, and explain each step thorougly, unlike the Python 101 or the challenges documents from 2024.
These notebooks were modified from Berkeley's Data8 data science course: http://data8.org, and were originally created by Wendy Carande and Allison Liu.
reu_programming/programming_1: These files are for the Programming Skills pt.1 on Day 3 of bootcamp. In this tutorial, you will do an exploratory data analysis of GOES Satellite data that has been pre-uploaded to GitHub for you to use. You will also write functions to do calculations and plot data.
reu_programming/programming_2: These files are for the Programming Skills pt.2 on Day 3 of bootcamp. In this tutorial, you will retrieve Solar Dynamics Observatory AIA data from the internet, import it into your programming environment, and put it in a format that is easier to work with. Then you will use skills learned in Programming Skills 1 to interpret the data.