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PYTHON FOR THE PHYSICIST (or Astronomer or Mathematician or Chemist or any field with data) This is meant as an introductory workshop on Python coding for the sciences. Many university physical science curricula do not require a formal coding course. However, the higher level courses expect amateur coding knowledge. Hopefully this can serve as a bridge for undergrads who are being faced with the challenge of using code without getting to formally learn it. While most of the code in this repository is in the form of Jupyter Notebooks, you can go to roarkhabegger.github.io/courses/python/ to go through the course with your own code editor. The webpages there contain the same material, just in a different format. Instead of Jupyter cells, you can copy the code for problems/examples into a script and run it. This tutorial begins with an introduction to coding and python in general (Intro_To_Python). After a basic understanding of the language and usage, I focus more on the physics problems we can solve with coding (Num_Methods_X). Once you have a grasp on the python language, your 'usefulness' as a researcher will be correlated with how well you understand the problem at hand and also how effectively you can translate a solution into code. Therefore, instead of esoteric explanations of why the code works the way it does, I want to provide examples and problems and let YOU solve them. Initially, these problems may take a couple lines but they will evolve into open-ended algorithm design. NOTE: You will only grow as a coder if you give effort on the exercises. Coding is a beautiful rabbit hole of challenge and satisfaction. But the most true coding adage is GIGO: Garbage In Garbage Out. Generally used in regards to data processing, I think it applies to every coder's work. So please, do yourself a favor: be focused and determined when trying to type code. Just because it doesn't work the first time does not mean your entire idea/method/alogrithm is wrong. Keep trying! Given enough time, the code will work the way you want it to.
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Introduction to Python coding with Numerical Methods lessons focused on physics problems
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