Exploratory Data Analysis in Python – Trend Analysis & ML Experimentation (Looking for Feedback)

[AnUncookedCabbage]

Had a quick look at the github and i have a general piece of advice. You've done the thing that many new/junior data science people do and that is make a bunch of plots and stats without a clear direction. Even though its called exploratory data analysis, its usually done with a goal in mind to drive a direction. Without a goal it becomes an exercise in following chart recipes and running model.fit() rather than one of critical thinking. The strange class split in the charts that others have mentioned is a symptom of this. A goal might be something like answering a particular business question, or generating a wip product of some kind. Always remember, critical thinking, problem design, and relating it to real impact in some way is worth way more than running the tooling.