Column Consistency Checker
Check a single CSV file for structural consistency — rows with the wrong number of fields, and columns that unexpectedly mix data types.
Row Field-Count Issues
Column Type Consistency
How to use Column Consistency Checker
- Start by providing the required input: Drop a CSV file. Use Load Sample to try example data first.
- No additional settings need to be configured.
- This tool has no separate run button; its results update as you add or change the input.
- Review the result or preview on the page and confirm it matches your input before using or sharing it.
CSV files that "look fine" until something parses them wrong
A CSV can open cleanly in a spreadsheet app and still have rows with the wrong number of fields, or a column that's supposed to be all numbers but has a few stray text entries — problems that only surface once something tries to process the file programmatically. Catching that before it happens saves a confusing debugging session later.
What "mixed types" actually flags
A column where most values parse as numbers but a handful are text (or vice versa) usually means a data-entry error, a placeholder value like "N/A" mixed into numeric data, or a genuinely inconsistent export — all worth a second look before the file goes anywhere important.
What row issues does this catch?
Any row with more or fewer fields than the header row defines — a common symptom of an unescaped comma or quote inside a cell during export.
Does this check consistency across multiple files?
No — this checks within one file. For comparing column schemas across several files before merging them, use the Multi-File Schema Checker instead.
What counts as a "date" type?
Any value JavaScript's date parser recognizes and that contains a 4-digit year — a reasonably broad but not exhaustive definition.