Recommendations for Python Resources

Hey everyone,

I’m an educator and amateur astronomer applying to planetary science graduate programs. I’ve been trying to teach myself data analysis techniques mostly for exoplanet characterization via transmission spectroscopy. My Python skills are a bit rusty so I’m looking for recommendations for perhaps an online Python course or other resources that directly build relevant skills. I’m also looking for any tutorials or educational resources for learning data analysis techniques for light curve fitting, Bayesian methods, limb darkening models, and others related to atmospheric retrievals. I would like to be able to better understand resources such as NASA’s ExoCTK - the exoplanet characterization toolkit, PandExo, and the transit software packages found here - I’ve found data analysis python courses on coursera and EdX but none specifically geared toward planetary science.

Thank you!

Hi @CJCollin37, @mariodamore @michaelaye ould maybe point you in right direction about Python training and educational resources?

I don’t know if a course specific to python + planetary science exist, at least I never found it.

Some python resource I suggest :

Have fun and let us know how is it going!

@nmanaud and @mariodamore, thank you both for the suggestions! I’ll check them out asap.

I’ve spent a lot of time working through the first link, the Python Data Science Handbook, and found it very helpful so far. I also decided to just reach out to some pros and one in particular, Michael Zhang, has been super helpful. I figured I might as well just get my hands dirty so I downloaded his tool PLATON for atmospheric retrievals and forward models for exoplanet transmission spectroscopy and have been using the skills I learned in the python handbook to play with PLATON and understand it. So far so good and I’m learning a lot. My next step will be to look at some publications and try to replicate the data I see there. I appreciate your suggestions, they definitely gave me the push I needed to dive into this stuff, so thanks!

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