CSV Column Mapper — Rename, Reorder & Drop Columns (Free)
Map CSV columns to a new schema. Rename, reorder, drop, and add columns. Useful for import preparation and ETL. Free.
About CSV Column Mapper
A CSV column mapper lets you transform the column structure of a CSV — renaming columns, reordering them, dropping unused ones, and adding new constant-value columns — so you can prepare an export for a destination system that expects a specific schema without writing custom ETL code. The ZTools CSV Column Mapper offers a drag-and-drop UI for ordering, an inline rename for headers, dropdown filters for keeping/dropping columns, optional default values for added columns, and a live preview that shows how the mapped CSV will look.
Use cases
- Adapting a vendor CSV to your import format. Vendor sends columns [VendorID, ProductName, MSRP]. You import [sku, title, price]. Map columns and rename — done in seconds, no scripting.
- Cleaning up a CSV before sharing externally. Internal CSV has 30 columns; you only want to share 8 with a partner. Drop columns, rename remaining for clarity, send.
- Adding required columns with default values. Destination expects a "source" column on every row. Add it with default value "vendor_x" — every row gets it without touching the rest of the data.
- Reordering for tools that depend on column position. Some imports map by column position, not name. Drag columns into the right order before exporting — saves a "wrong column got mapped" debugging session.
How it works
- Paste or upload the CSV. Headers detected automatically. The mapper shows each column with its current name and a sample value.
- Pick the destination schema. Toggle each column: keep, drop, or rename. Drag rows to reorder columns.
- Add new columns with defaults. Click "Add column", give it a name and a default value. Optionally compute from existing columns (concat, default-if-empty).
- Live preview the mapped CSV. See the transformed first 10 rows in the preview pane. Catches mapping mistakes before exporting the full dataset.
- Export the mapped CSV. Download or copy. Original CSV is preserved in case you want to re-map differently.
Examples
Input: Source: vendor_id,product,msrp
Output: Mapped: sku,title,price (3 columns renamed, no changes to data).
Input: Source: 30 columns, want 8
Output: Drop 22 columns; output has only the 8 chosen, in the order you specified.
Input: Add a constant "source"="acme" column
Output: Every output row gets source=acme. New column added at the position you chose.
Frequently asked questions
Will the mapper modify my source CSV?
No — the original is preserved. The mapper produces a new mapped CSV; you can re-map with different settings without losing the source.
Can it merge columns or compute new values?
Limited support: concat (combine two columns into one), default-if-empty (fill blanks with a literal). For complex transformations, use a spreadsheet or scripting tool.
What if my source CSV has duplicate column names?
Duplicates are flagged. The mapper auto-suffixes them (col, col_2) so each is uniquely addressable. Rename to your destination scheme before exporting.
Does it preserve the data type of values?
CSV is plain text; there are no native types. Values pass through unchanged. If your destination expects numeric values, ensure your source values look numeric (no thousands separators, decimal-separator consistent).
Can I save a mapping for re-use?
Save as a JSON template (export from the mapper, import next time). Useful when you receive vendor CSVs with consistent shapes monthly.
Pro tips
- Always preview before exporting — column-mapping mistakes silently produce wrong output.
- Save a JSON mapping template for recurring imports; replays the same transformation in seconds.
- For one-time complex transforms, a spreadsheet may be faster than fighting with column-mapping rules.
- Drop unused columns to reduce file size and reviewer cognitive load — smaller CSVs are easier to review.
Reviewed by Ahsan Mahmood · Last updated 2026-05-05 · Part of ZTools.
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