Python CSV Data Cleansing

I have several CSV files that contain a mix of text and numeric columns. I need a Python script that reads these files, cleans obvious issues (extra whitespace, stray symbols, inconsistent number formats, blank rows) and then applies flexible filtering rules I can adjust myself later.

Key points
• Source files are plain CSV; no database or API connection is involved.
• The data is mixed, so the script must recognise both text and numeric fields and keep their types intact after processing.
• Filtering is the only required transformation for now—think along the lines of dropping rows that fail certain thresholds, keeping records that match specified keywords, or combining multiple filter conditions with AND/OR logic.

Deliverable
1. A well-commented Python script (ideally using pandas) that:
– Accepts an input folder path and outputs the cleaned, filtered results to a new CSV.
– Lets me tweak filter criteria easily in a configuration section or via command-line arguments.
2. A short README or inline docstring explaining any external libraries and how to run the script.

If you can make the code modular so I can add future steps like merging or aggregation later, that’s a plus.