Good day @jbreaper,
I am also doing the same course and have just completed my version of this project.
I can see, that you would like to have your project peer-reviewed, same as me.
I will start with my review of your project:
Project Goals and Data Description:
The introduction provides a clear understanding of the project’s main goal and the dataset being analyzed. Mentioning the ethical gathering of data is a good practice. The data categories are well-documented, and each category’s relevance to health insurance is outlined.
The analysis goals are outlined, emphasizing the investigation of the “charges” data point and its relationship with other factors such as age, BMI, smoking status, etc. The decision to categorize and subcategorize data points for a meaningful comparison is wise.
The project shows a good foundation with a well-defined goal and thoughtful consideration for data analysis. Refining documentation, expanding on analysis plans, and enhancing code modularity, and slimming it down into digestible chunks can further improve the project’s structure and readability.
The classes demonstrate a solid structure, effective use of dictionaries, and clear methods for data analysis. Improvements can be made in terms of documentation, consistent naming, and minor code refinements. Overall, it’s a well-organized codebase for analyzing medical insurance data.
This is my first review so, it may not be perfect.
Anyway, I would appreciate it if you could do the same and review my project as well.
Here is the link: GitHub - MSarib-Ibrahim1199/Medical-Insurance-Costs-Analysis-with-Python: Uncover insights into U.S. medical insurance costs using Python. Explore factors like age, smoking, family size, and BMI influencing healthcare charges. Gain valuable perspectives on the intricate dynamics shaping insurance expenditures.
Thanks in advance.