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. 900k_USA_dump.txt
: Use StandardScaler or MinMaxScaler to ensure numerical features (like "Income" or "Age") are on a similar scale. If you are working on a legitimate data
: Use One-Hot Encoding for nominal data (e.g., "State") or Label Encoding for ordinal data. I recommend using verified
If you transition to a legitimate dataset, here is the standard workflow for preparing features: