List, Pandas and Concurrency | Dataford Interview Questions

Tell me about your experience with List vs tuple, Pandas, Numpy, and multithreading vs concurrency.

Implement summarize_batches(batches, max_workers) to demonstrate these concepts in one practical task. batches is a non-empty list of non-empty numeric lists, and the function must return one summary dictionary per batch in the original order. Use tuples for immutable worker inputs, NumPy and Pandas for calculations, and a thread-based concurrency approach.

Input and Output

batches is list[list[int | float]]; max_workers is an integer. Return list[dict], where each dictionary contains count, mean, and median.

Constraints

1 <= len(batches) <= 1000
1 <= len(batches[i]) <= 1000
1 <= max_workers <= len(batches)
Values are finite integers or floating-point numbers
Every batch is non-empty

Function Signature

def summarize_batches(batches, max_workers):

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