CSV Column Extractor

Select, reorder, and extract specific columns from CSV data files.

CSV Input

Drop a CSV file or click to browse

CSV Column Extractor

Use this tool to pick and reorder columns from any CSV file without opening Excel or writing code. After loading your CSV (paste or drag-and-drop), each column appears as a toggleable row. Check the columns you want to keep, uncheck the ones to drop, and use the arrow buttons to reorder them. The output CSV is rebuilt live with only your selected columns in your chosen order, preserving all data rows. Supports quoted fields and embedded commas. All processing runs entirely in your browser — no data is uploaded to any server.

Built and maintained by Meet Shah · Last updated 27 July 2026

What this tool is used for

Reducing a wide export to the handful of columns you actually need.
Reordering columns to match the format an importer expects.
Removing columns containing personal data before sharing a file.
Producing a narrow file for a quick analysis without opening a spreadsheet.
Checking which columns an unfamiliar export actually contains.

Frequently Asked Questions

Does it handle quoted fields containing commas?: Yes — that is the whole reason to use a parser rather than `split(",")`. `"Smith, John",42` is two fields, not three, and a naive split silently shifts every column after it. Doubled quotes inside a quoted field are unescaped correctly too.
Are the extracted columns re-quoted?: Only where needed. A value containing a comma, a quote or a newline is wrapped in quotes with internal quotes doubled, per RFC 4180 — so the output is valid CSV that survives being fed straight back into another tool.
Can I reorder columns while extracting?: Yes: the output follows the order you select, not the order in the file. That makes this a quick way to reshape a spreadsheet export for an importer that insists on a particular column sequence.
What if rows have different lengths?: A short row yields empty values for the missing columns rather than shifting data left. Ragged rows usually mean an unescaped delimiter somewhere upstream — worth fixing at the source, since no amount of downstream parsing recovers the lost boundary.
Why is this better than a spreadsheet?: It never touches your data's types. Opening a CSV in Excel converts anything that resembles a date, drops leading zeros from postcodes and part numbers, and turns long IDs into scientific notation — silently, and without a way back.
Should columns be selected by name or position?: By name where a header exists — positions shift whenever a column is inserted upstream, and the failure is silent because the extraction still returns data, just the wrong column.

Common errors and gotchas

Selecting by position when the source's column order is not guaranteed between exports.
Overlooking a quoted field containing commas, which a naive split misaligns.
Losing the header row, which turns the first record into column names downstream.
Assuming column names are unique, when duplicates make a name-based selection ambiguous.
Removing a column that another column's meaning depended on, such as a units field.