Transform CSV columns with 25+ operations: text manipulation (uppercase, lowercase, trim), number formatting, date conversion, extraction patterns, and custom pipelines
Apply column-level transformations to your CSV data using a formula-like syntax. Trim whitespace, change case, format dates, extract substrings, perform arithmetic on numeric columns, or create new computed columns, all without writing a script.
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Convert between CSV and JSON formats
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You need to add a `full_name` column from `first` + `last` and uppercase the `code` column in one pass.
Transforms
new full_name = first + " " + last · code = UPPER(code)
Output
first,last,code,full_name Dana,Lee,ab12,DANA LEE ... (full_name added, code upper-cased)
Column-level transforms (concatenate, case, split, derive) are applied across every row at once, so reshaping a file does not require a script. Chaining several steps before export turns a messy source into pipeline-ready data in one screen.
Apply column-level transformations to your CSV data using a formula-like syntax. Trim whitespace, change case, format dates, extract substrings, perform arithmetic on numeric columns, or create new computed columns, all without writing a script.
Standardize inconsistent formatting, trim spaces, unify date formats, normalize case, across an entire column.
Add a "Total" column that multiplies Quantity by Price, or a "Full Name" column that concatenates First and Last.
Convert dates from MM/DD/YYYY to ISO 8601 format (YYYY-MM-DD) for database import.
Replace sensitive column values with masked versions (e.g., show only last 4 digits of a phone number).
Each transformation is defined per column using an expression builder. Supported operations include string functions (trim, upper, lower, replace, substring, split, concat), numeric functions (round, floor, ceil, abs, basic arithmetic), date functions (parse, format, add days, difference), and conditional logic (if-else based on value tests). You can chain multiple transformations on the same column and create entirely new columns from expressions referencing existing ones.
A live preview updates as you build transformations so you can verify results before applying them to the full dataset.
Yes. Use column names in expressions to create computed values, for example, {Quantity} * {Price} for a total column.
Transformations are previewed before applying. You can also re-upload the original file to start over.
The tool recognizes ISO 8601, US (MM/DD/YYYY), European (DD/MM/YYYY), and several other common formats. You can specify a custom format string if needed.
Rows and columns are parsed and transformed in memory in your browser. No record ever reaches a server.