Combine multiple CSV files into one
Combine multiple CSV files into one. Whether you need a simple vertical stack (append rows) or a horizontal join on a shared key column, this merger handles both. Column alignment is automatic, even when files have different headers.
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Compare two CSV files side-by-side, find added/removed/modified rows, key-based or positional matching, highlight differences, and download comparison report
You have monthly export files with identical columns and need one combined CSV for the year.
Input
jan.csv, feb.csv, mar.csv (same schema)
Output
combined.csv, one header, 3 files’ rows concatenated in order
Files are stacked with the header kept once and column order reconciled by name, so a reordered column in one file does not silently misalign data. It warns on schema mismatches rather than producing a corrupt merge.
Combine multiple CSV files into one. Whether you need a simple vertical stack (append rows) or a horizontal join on a shared key column, this merger handles both. Column alignment is automatic, even when files have different headers.
Stack monthly CSV reports into a single annual dataset for analysis.
Join a customer list with a separate CSV of purchase history using a shared customer ID.
Reassemble files that were previously split for emailing or batch processing.
Vertical merging (union) appends rows from all files, intelligently matching columns by name and filling gaps when one file has columns the others lack. Horizontal merging (join) works like a database JOIN, pick a key column present in each file and the tool matches rows, supporting inner, left, right, and full outer join types. A preview table shows the merged result before you commit.
For vertical merges, the tool creates a superset of all columns and fills missing values with empty cells. For joins, only matched key rows are combined.
There is no hard limit. Performance depends on total row count and your browser memory.
The tool flags potential duplicates. For thorough deduplication, use the CSV Duplicate Remover afterward.
Rows and columns are parsed and transformed in memory in your browser. No record ever reaches a server.