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CSV Drag-and-Drop Mapper

Reorder, rename, and map CSV columns visually. Save templates. Upload new files and apply instantly. 100% browser-based.

100% LOCALDrag-and-drop mappingAuto-match headersTemplate save/loadLive preview

Visually map CSV columns to target fields

CRM, e-commerce, and accounting exports all have different column orders. Drag source headers onto target fields, save the mapping as a template, and apply it to new files with one click.

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Drop your CSV here or click to upload

Max 5MB · All processing in your browser

Data Source & Legal Disclaimer

Effective: 2026

Sources: Browser-side processing (no external API)

This tool runs 100% in your browser. All computation happens locally on your device — your input is never uploaded to any server. Results are for reference only.

See all data sources & update policy →

How CSV column mapping works — illustrated

CSV exports from CRM, e-commerce, and accounting tools almost never match the column layout your target system expects. This tool parses the file with a character-level RFC 4180 state machine — so quoted commas and newlines stay inside their fields — then lets you drag each source header onto a target field. Each target field holds at most one source column (a one-to-one mapping), and every saved mapping is a reusable template.

From source export to target schema

Source headers are dragged onto target fields; the tool auto-matches by normalized name, and the output reorders and renames columns to the target layout.

Worked example

Nadia is a marketing operations analyst migrating a Shopify customer export into her CRM. The export and the CRM use completely different column names and order.

Export:Her file has headers name, email, phone, product, qty and total_price across 1,204 rows; the CRM import expects full_name, email_address, phone_number, product_name, quantity and price.
Auto-match:She drops the file in; the tool parses all rows and auto-maps all 6 of 6 columns — email and phone by normalized name, qty by the abbreviation rule (qty → quantity), and total_price by substring match (total_price contains price).
Verify:She glances at the mapping chips — every source column shows its target, and the live preview already shows the columns in the CRM's expected order. No manual fixes needed.
Reuse:She saves the mapping as Shopify-to-CRM and applies it to next week's export with a single click — no re-dragging.

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About this tool

What is this tool?

Visually map, reorder, and rename CSV columns with drag-and-drop. Auto-match headers. Save templates. 100% in-browser, free, no signup.

Drag-and-drop mappingAuto-match headersTemplate save/loadLive preview

What Is the CSV Drag-and-Drop Mapper?

The CSV Mapper is a free, browser-based tool that lets you visually map CSV columns to target field names. Instead of manually editing CSV headers or writing scripts, you drag source columns onto target fields. The tool auto-matches headers by name similarity, supports custom target field names, and lets you save mapping templates for reuse on future files. All processing happens in your browser — no data is uploaded.

Who Should Use This Tool?

E-commerce sellers who need to reformat product feeds for different platforms (Shopify, Amazon, eBay). CRM administrators migrating contacts between systems. Accountants converting bank exports to accounting software formats. Data analysts who regularly transform CSV data from multiple sources. Anyone who regularly needs to reformat CSV files for different target systems.

How to Use the CSV Mapper

Upload your CSV file or use the sample data. The tool parses and shows source columns on the left. Define your target field names on the right. Drag source columns onto target fields to map them — the tool auto-matches similar names. Preview the mapped output in real-time. Save the mapping as a template for future use. Export the remapped CSV with one click.

Frequently Asked Questions

Can I save my mapping for reuse?

Yes. Enter a template name and click Save Template. The mapping and target field names are stored in your browser localStorage. Click Load Last Template to apply it to a new file instantly.

What happens to columns I don't map?

Unmapped columns are kept in the output with their original header names. Only mapped columns get renamed to the target field name.