Updated · Built and checked by the PlinzoTools team, formulas tested against published sources
Extract one or more specific columns from CSV data.
Your extracted columns will appear here.
This tool extracts one or more specific columns (by header name) from pasted CSV data, discarding the rest -- useful for pulling just the fields you need out of a larger export.
Paste your CSV data (with a header row) and type the exact header names you want to keep, separated by commas (e.g. name, email). The extracted columns appear instantly as new CSV output, in the order you typed the names.
The description on this page says columns are chosen by number, but the tool actually selects them by their header name. The first row of your CSV is treated as the header row, and the names you type in the columns field are matched against it. Typing 1,3 will not extract the first and third columns. It will look for headers literally named 1 and 3, and find none unless your file happens to have such headers. To extract columns, type the exact header text, separated by commas, for example name,age.
Suppose your hypothetical export has the header row name,email,age,city and several data rows. Enter email,name in the columns field. The output has a header row of email,name, followed by each row's email and name values in that order. The age and city columns are dropped, and the original order name,email is swapped to email,name. If you had typed Email with a capital E, no match would be found for that column and only name would come out.
The parser understands quoted fields. A comma inside double quotes stays part of the field, a doubled quote inside a quoted field becomes a single quote character, and line breaks inside quotes are kept. Both Windows and Unix line endings are accepted. Blank lines are skipped. The output is rewritten with a comma delimiter and a newline between rows. A field is wrapped in quotes again only when it contains a comma, a quote, or a newline, so quoting in the result may look different from your source even though the data is the same.
This is handy when you need only a few fields from a wide export, for example to share a list of names and emails without extra private columns, to prepare a smaller file for an import that accepts only certain fields, or to reorder columns to match a template. Review the output before sharing it, particularly when the purpose is to remove sensitive columns, and check that the columns you meant to exclude are actually absent. Everything runs in your browser, and the pasted data is not sent to a server.
No -- parsing and extraction happen entirely in your browser.
Yes -- names must match the headers in the first row exactly, including capitalisation. Names that do not match any header are skipped, and column numbers are not supported.
No. The tool matches header names, not positions. Type the exact header text of each column you want to keep.
Yes. Output columns follow the order in which you type the names, so typing email,name puts email first.
None of the names you typed matched a header exactly. Matching is case-sensitive and must match the header text, so check spelling and capitalization.
Yes. Quoted fields are read correctly and are re-quoted in the output when they contain a comma, a quote, or a line break.