Are for-loops in pandas really bad? When should I care?

For-loops are not inherently "bad" in pandas. In certain situations, they can offer advantages over using more conventional "vectorized" approaches. Consider using a for-loop when:

• Working with small data: Vectorized functions introduce overhead for handling index/axis alignment, mixed datatypes, and missing data. For small datasets, for-loops may be faster.
• Dealing with object/mixed dtypes: Pandas treats strings as objects, and string operations are inherently difficult to vectorize. List comprehensions often outperform vectorized methods with mixed dtypes.
• Using the str/regex accessor functions: Vectorized string operations (e.g., str.contains) can be slower than pre-compiling a regex pattern and iterating over the data using re.compile.

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