Pandas Data Manipulation Task (UberEats Analytics)

Prompt Given one or more UberEats-related tables (e.g., orders, merchants, users, event logs), use Pandas to perform the required data cleaning, joins, aggregations, and derived metric computations, and output a resulting DataFrame. Expected skills (depending on the prompt): merge/join groupby.agg ordering/window-like operations (sort_values, cumcount, rank, shift) missing/outlier handling reshaping (pivot_table, melt) Note: The original post does not include the exact schemas, transformations, or expected output, so it cannot be completed into a fully specified coding question.