⚡ Bolt: [performance improvement] Refactor iterrows to itertuples for faster iteration

[alinelena]

💡 What:
Replaced df.iterrows() with df.itertuples(index=False, name=None) for standard tuple access and df.to_dict('records') when dictionary key access is required in calculation and analysis scripts.

🎯 Why:
Iterating over Pandas DataFrames with iterrows() is a known performance bottleneck. It yields a Series object for each row which incurs substantial overhead. Moving to itertuples() and to_dict('records') significantly accelerates the iteration speed inside frequently evaluated loops.

📊 Impact:
Significantly reduces execution time during DataFrame iterations, which occur often during benchmark analyses parsing Reference values across many models.

🔬 Measurement:
To verify the improvement, examine the reduced runtime when evaluating tests or benchmark calculations that utilize read_excel followed by dictionary look-ups of labels. Compare the performance against previous iterrows implementations.

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PR created automatically by Jules for task 1198171667807176769 started by @alinelena

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