Form the foundation of our data stack. NumPy provides fast n‑dimensional arrays and vectorized math, while pandas adds DataFrame/Series abstractions for tabular data, joins, group‑bys, and time series. Together, they power ETL, cleaning and normalization, feature engineering, exploratory analysis, and quality checks. We rely on them as the first layer for preparing datasets and feeding downstream ML/LLM pipelines