Profile a dataset before changing anything

Step-by-step approach

1. Identify the intended row count and which columns should be numeric or unique.
2. Use CSV Data Profiler to review missing values and distinct-value counts.
3. Look for unexpected min/max ranges and mixed data representations.
4. Decide on cleaning rules before rewriting the dataset.
5. Keep the profile alongside the original file for reproducibility.

What this does not solve

Browser tools can validate known structures and transform available data, but cannot restore deleted or corrupted bytes, infer unknown business facts, or guarantee that a target system will import every field as intended.