Adams Feature engineering of house price data set from Kaggle Used Python’s Pandas to load a dataset of 1460 rows with 81 features into Jupyter Notebook. Performed exploratory data analysis with Matplotlib, NumPy, Pandas, and Seaborn Imputed missing values, scaled features, handled rare categorical features among others.