Focused purpose
What this tool does
Merge multiple CSV or TSV files locally with reordered, missing or extra columns. Review schema mapping and file order, then download without an account.
- ✓ Header-based schema union
- ✓ Manual column mapping
- ✓ Missing-column preview
- ✓ File order control
Workflow
How to use it
- 01
Add files and confirm each parse.
- 02
Review header mappings and incompatibilities.
- 03
Choose order, preview totals and export.
Available controls
Available options
- Require identical columns or union all schemas.
- Map renamed headers manually.
- Reorder source files.
- Fill missing fields with empty values.
Two compatible monthly files
Example before and after
Columns are reordered and one file adds an optional city field.
Before
january.csv id,name 1,Ada february.csv name,id,city Linus,2,Helsinki
After
id,name,city 1,Ada, 2,Linus,Helsinki
Expected result: The schema union aligns fields and appends rows in file order.
Practical scenarios
Common use cases
Combine monthly exports.
Unify regional datasets with reordered columns.
Append partner feeds with optional fields.
HONEST LIMITS
Important limitations
- iMerging appends rows; it does not match records by key.
- iColumns with the same name but different meanings require manual review.
FAQ
Questions about this tool
Do files need columns in the same order?
No. Header mapping aligns columns independently from their position.
What happens to missing columns?
They are shown before merge and exported as empty cells unless you change the mapping.
Is merge the same as join?
No. Merge stacks rows; join matches rows from two tables using keys.