High-performance Pandas: Speed and memory
Pandas is generous with dtypes by default: integers are often int64 even when the range is small. On millions of rows that wastes gigabytes. Optimization means choosing compact dtypes (category, int8, float32) and vectorized operations instead of Python loops and unnecessary .apply().
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