Optimize Data Aggregation for Large-scale Datasets
Instruction: Explain how you would optimize a Pandas operation for aggregating a very large DataFrame (e.g., over 100 million rows) by multiple columns. Include considerations for memory management and processing speed.
Context: This question challenges the candidate to demonstrate their knowledge of Pandas' efficiency and scalability, particularly in handling large datasets efficiently without running into memory issues or excessive processing times.
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"In my previous projects, I've leveraged Pandas' categorize feature for non-numeric columns,...
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