CSV Editor
Edit CSV data in an interactive spreadsheet-style table editor
View, edit, clean, merge and convert CSV data in a table rather than in a text editor.
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Edit CSV data in an interactive spreadsheet-style table editor
View and browse CSV files in a clean table layout in browser
Remove extra spaces, fix encodings, and sanitize CSV data automatically
Detect and delete duplicate rows in any CSV or XLSX file
Merge multiple CSV files by appending rows or joining on a key column
Convert CSV files to JSON arrays with configurable key mapping
Flatten JSON arrays into CSV rows with automatic header detection
Convert between TSV (tab-separated) and CSV or JSON formats
Change the delimiter of any delimited text file, comma, tab, pipe, semicolon
Often used alongside these, from other categories.
CSV is the format everything can read and nothing agrees on: delimiters vary, quoting rules vary, encodings vary, and a spreadsheet application will happily mangle a column of long numbers or leading zeros the moment it opens one. Working on the raw data in a table view avoids that entire category of damage. These tools parse the file in your browser, which matters because the CSVs people need to clean are usually exports containing customer records.
Spreadsheet applications guess at types on import: phone numbers lose leading zeros, long IDs become scientific notation, and anything that looks like a date becomes one. Viewing and editing the file as text-typed columns first means those conversions never happen.
Merging files with inconsistent headers, trailing whitespace or mixed line endings produces a file with subtly duplicated columns. Normalising each input first (trim, fix encoding, align headers) turns the merge into a trivial step.
Two rows that differ only in whitespace, capitalisation or a trailing empty column are duplicates to a person and distinct to a program. Decide which columns define identity before removing anything, and keep the original file until you have checked the result.
CSV is strictly rectangular; JSON is a tree. Converting JSON to CSV means flattening nested objects into dotted column names, and converting back does not necessarily reconstruct the original nesting. Round trips are lossy in a way that is easy to miss until it matters.