: A classic resource for academic and professional datasets.
: Offers thousands of structured datasets (CSV, JSON) for tasks like credit scoring, housing prices, or demographic analysis. 900k_USA_dump.txt
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: : A classic resource for academic and professional datasets
: Create new variables, such as calculating "Years of Credit History" from "Account Open Date." JSON) for tasks like credit scoring
: Use One-Hot Encoding for nominal data (e.g., "State") or Label Encoding for ordinal data.
: Provides extensive, anonymized USA demographic data for feature engineering. How to Prepare Features for a Standard Dataset
If you transition to a legitimate dataset, here is the standard workflow for preparing features: