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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​

  1. Paste or upload the CSV — Headers detected automatically. The mapper shows each column with its current name and a sample value.
  2. Pick the destination schema — Toggle each column: keep, drop, or rename. Drag rows to reorder columns.
  3. 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).
  4. Live preview the mapped CSV — See the transformed first 10 rows in the preview pane. Catches mapping mistakes before exporting the full dataset.
  5. 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.

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.

Try it now​

The full csv-column-mapper runs in your browser at https://ztools.zaions.com/csv-column-mapper — no signup, no upload, no data leaves your device.

Open the tool ↗

Last updated: 2026-05-05 · Author: Ahsan Mahmood · Edit this page on GitHub