I’ve recently started experimenting with the programming language Python. My main goal is to apply Python to data science projects when needed. I’m still in the super early stages of learning the basic concepts, working with packages, and just seeing the broader picture of what it has to offer, but so far it’s been relatively straightforward and clean. Working with Jupyter Notebooks is a huge factor in what makes it so convenient and user-friendly. Jupyter is basically an IDE that is online and has a very similar feel to Google Docs, Sheets, etc. and allows users to create in a more comfortable, convenient environment. I really love it so far. Anyways, below is a small dashboard I created. The data and assignment were both from a course on Udemy which served as my introduction to Python, although at this point I’m looking for more project-based tutorials. The visualizations are running off of a package called Seaborn, which is incredibly flexible and intuitive. Seaborn works on top of Matlplotlib, which is one of the core packages that comes with Python and allows for the calculations necessary for a lot of data science projects. Finally, if you want to review my code and let me know what you think, check it out at GitHub.
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