Python and Data Manipulation Questions

Demonstrate practical proficiency in Python for data exploration and preprocessing. Expect to perform data cleaning, joins, group by aggregations, pivots and reshaping, vectorized operations, missing value handling, and basic performance tuning using libraries such as NumPy and Pandas. Show how to write readable, testable, and efficient code for sampling, feature extraction, and quick prototyping, and how to scale to larger data sets using chunking or streaming approaches.