I'm looking to enhance my Python and R skills as I'm interested in a university economics project. I have some experience with Python from CS courses, particularly with basic recursion, SciPy, NumPy, and Matplotlib for curve fitting and plotting in physics labs. I'm aiming to develop my abilities in several areas, including linear regression, data cleaning, APIs, web scraping, machine learning models, causal inference methods, Git or version control, and survey design.
I'm hoping someone could suggest a project (or several smaller ones) that would allow me to learn these skills effectively. Ideally, I'd like a project in both Python and R, and I'd appreciate it if they're related to economics. A bit of context: I've dabbled in linear and nonlinear regression and some basic data cleaning, but I'm not familiar with APIs or Git yet. Survey design might be complex, so I'm open to focusing on the theoretical aspects if needed.
3 Answers
For data cleaning, check out the Pandas library. It’s super helpful! And for machine learning, scikit-learn is a great starting point. Both are well-documented and have a ton of examples online to help you get started!
Git is simple to understand—it’s like making copies of your project before trying new things. If you mess something up, you can revert to your previous work. Learning Git will be really useful for version control in your projects!
Ahh thank you!
You could scrape housing data from the Zillow API and then try predicting prices using various models. This project would cover a lot of the skills you're looking to learn while being highly relevant to economics!
Thanks, I think something like this'll work!
Thank you, I'll check those out!