If you transition to a legitimate dataset, here is the standard workflow for preparing features:
If you are working on a legitimate data science project and need to practice feature engineering, I recommend using verified, public datasets. Here are a few safe alternatives: 900k_USA_dump.txt
: Handle missing values by using imputation (mean/median) or dropping incomplete rows. If you transition to a legitimate dataset, here
: Create new variables, such as calculating "Years of Credit History" from "Account Open Date." I recommend using verified