5 Ways to Clean Messy CSV Data

Real-world CSV files are rarely tidy. Extra whitespace, inconsistent casing, duplicate rows and stray delimiters can all get in the way of a clean import.

1. Trim whitespace. Leading and trailing spaces are the most common cause of failed lookups and mismatched joins. Trim every cell before you do anything else.

2. Normalise casing. Decide on a convention for text columns — lower, UPPER or Title Case — and apply it consistently so grouping and de-duplication behave predictably.

3. Remove duplicate rows. Duplicates inflate counts and skew analysis. Sort by a key column and drop exact repeats.

4. Standardise dates and numbers. Mixed formats (01/02/2025 vs 2025-02-01) break parsers. Pick one format and convert everything to it.

5. Handle empty cells intentionally. Decide whether a blank means zero, null, or 'unknown' — and fill accordingly instead of leaving ambiguity in the data.

You can do all of this in Vertex without writing a single line of code — open the editor, load your file, and use search, sort and bulk edit to tidy things up.