Excel Numerical Data Normalization

I have several Excel workbooks filled exclusively with numerical fields that need to be brought onto a consistent scale. Your task is to write a clean, well-commented Python routine—pandas and NumPy (or scikit-learn) are fine—that:

• ingests each Excel file,
• applies the chosen normalisation method (z-score or min-max; I’m open to whichever you recommend and can justify),
• saves the normalised version back to Excel or CSV, and
• produces a concise summary report showing before-and-after statistics so I can confirm the transformation worked as intended.

All files share the same column structure, so you can assume uniform headers. Missing-value handling and duplicate removal are not priorities right now, but please write your code so those steps could be slotted in later if needed.

Deliverables: the Python script/notebook, any auxiliary modules, and one sample output file to demonstrate correctness. Once I can run your script locally and reproduce the normalised data and report without errors, the job is done.