Filter and select specific columns from CSV files
Select only the columns you need and discard the rest. Upload a CSV, check the columns to keep, and download a trimmed file, useful when a data source gives you 50 columns but you only need 5.
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You must share a dataset with a partner but strip the email and phone columns first.
Input
Keep: id, country, plan · Drop: email, phone, notes
Output
A CSV with only id, country, plan, in the order you specified
Selecting columns to keep (or drop) and reordering them is a one-step way to produce a safe, minimal extract for sharing. Because it runs locally, the sensitive columns never leave your machine even momentarily.
Select only the columns you need and discard the rest. Upload a CSV, check the columns to keep, and download a trimmed file, useful when a data source gives you 50 columns but you only need 5.
This is a pure column operation: it changes which columns appear and in what order, but never touches your rows or rewrites a single value. The CSV is parsed with PapaParse (empty lines skipped), and every column starts checked. Each column in the picker shows its header name and a live "Original: Column N → Position: M" label, so you can see exactly where it will land in the output. The export is built by reading each retained column in your chosen order and copying the cell across verbatim (missing cells become an empty string), then re-serialized with PapaParse's unparse and downloaded as "<originalname>_columns.csv". Because no parsing of numbers or dates happens, leading zeros, currency symbols, and date formats survive untouched.
For wide files, a search box filters the picker itself so you can locate one column among dozens by typing part of its name, and All / None / Invert buttons let you flip the whole selection at once (Invert is handy when you want everything except a few sensitive fields). Reordering works either by dragging a column or with its up/down arrows, and Reset restores the original column order while leaving your checkbox choices intact. A "First row contains headers" toggle controls whether the top row is treated as column names or as data, and a live preview pane (toggleable) shows the first 10 rows of the trimmed, reordered result before you commit. If the upload has malformed quotes or an unrecognizable delimiter the load is rejected, whereas rows with the wrong field count load through with a non-fatal mismatch warning.
Strip unnecessary columns from a large export to shrink the file before sharing.
Remove sensitive columns (SSN, email, phone) before passing data to external teams.
Trim a CSV down to the exact columns a target system expects.
Yes. Drag columns into the order you want and the exported file reflects that order.
Rows and columns are parsed and transformed in memory in your browser. No record ever reaches a server.