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  3. CSV Data Transformer
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CSV Data Transformer

Transform CSV columns with 25+ operations: text manipulation (uppercase, lowercase, trim), number formatting, date conversion, extraction patterns, and custom pipelines

Clean and reshape CSV column values by stacking predefined transformations. Pick a column, choose an operation from a menu, set its parameters, and the tool rewrites that column. Change case, trim and pad, find-and-replace, take a substring, extract digits or letters, format numbers and dates, build a slug, or mask sensitive values, all without writing a script.

Rows never leave your deviceMore csv & data analysisJump to full guide

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A sample run

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)
CSV Data Transformer produces

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.

About the CSV Data Transformer

Clean and reshape CSV column values by stacking predefined transformations. Pick a column, choose an operation from a menu, set its parameters, and the tool rewrites that column. Change case, trim and pad, find-and-replace, take a substring, extract digits or letters, format numbers and dates, build a slug, or mask sensitive values, all without writing a script.

How to use

  1. 1Upload your CSV
  2. 2Select a column and choose a transformation from the menu
  3. 3Configure its parameters (for example, replacement text or decimal places)
  4. 4Stack more transformations if needed and check the preview
  5. 5Apply to all rows and download the result

Key features

  • Text operations: case, trim, pad, replace, substring, split, concat, reverse, dedupe words
  • Extraction: keep digits, keep letters, email domain
  • Number operations: round, absolute, thousands separator, percentage, currency
  • Date reformatting, URL slug, and value masking
  • Concatenate one column into another with a separator
  • Stack and toggle multiple transformations that run in order
  • Preview before applying to all rows

How it works

Each transformation targets one column and is chosen from a categorized menu rather than written as a formula. Text operations include uppercase, lowercase, title case, trim (both sides, left, or right), remove all whitespace, find-and-replace, add a prefix or suffix, substring, split-and-keep a part, concatenate with another column using a separator, pad left or right to a target length, reverse, and dedupe repeated words. Extraction operations keep only digits, keep only letters, or pull the domain from an email address. Number operations cover rounding to a number of decimals, absolute value, thousands separators, percentage, and currency formatting. There is also date reformatting, a URL-slug builder, and a mask operation that hides the middle of a value (for example, a credit card number) while leaving a few characters visible at each end.

You can stack several operations and they run top to bottom, so each step feeds the next, and any step can be toggled off without deleting it. Transformations are applied in place to the chosen column; the tool does not evaluate arithmetic expressions or create brand-new computed columns, though concatenate can join one other column into the target. A preview lets you check results before applying to all rows and downloading.

Where this fits a data pipeline

  • Data normalization

    Standardize inconsistent formatting, trim spaces, unify date formats, normalize case, across an entire column.

  • Combining fields

    Concatenate a First name column into a Last name column (with a space separator) to build a single name field.

  • Date reformatting

    Convert dates from MM/DD/YYYY to ISO 8601 format (YYYY-MM-DD) for database import.

  • Data masking

    Replace sensitive column values with masked versions (e.g., show only last 4 digits of a phone number).

Tips & best practices

  • Chain transformations top-to-bottom, each step feeds into the next.
  • Use the preview to check edge cases (empty cells, unexpected formats) before applying to all rows.

Frequently asked questions

Can I reference another column?

The Concatenate operation can join one other column into the target column, with a separator you choose. There is no general arithmetic or expression engine that references multiple columns.

Is there an undo if I make a mistake?

Transformations are previewed before applying, and each step can be toggled off without deleting it. You can also re-upload the original file to start over.

Can it reformat dates?

Yes. The Format Date operation converts a date column from one format to another. The data is changed in place rather than added as a new column.

Private by design

Rows and columns are parsed and transformed in memory in your browser. No record ever reaches a server.