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Data Normalizer

Normalize finance datasets into canonical columns and value formats.

Normalize Dataset

AI-generated

Summary

Normalize a dataset of JSON objects by mapping and renaming columns, and normalizing values for amount, date, percentage, category, currency, and accounting period fields into canonical formats.

Inputs

  • Add Currency Column — Boolean to normalize or create the currency column using the specified default currency.
  • Accounting Period Column — Name of the column where the generated accounting period in YYYY-MM format will be written.
  • Accounting Period Date Column — Name of the date column used to generate the accounting period. If empty, accounting period generation is skipped.
  • Amount Columns — Comma-separated list of columns to normalize to decimal string format.
  • Category Columns — Comma-separated list of category columns to trim and collapse repeated whitespace.
  • Column Mapping — JSON object mapping source column names to canonical column names.
  • Currency Column — Column to normalize or create with an ISO currency code; used only if Add Currency Column is true.
  • Date Columns — Comma-separated list of date columns to normalize to ISO date format YYYY-MM-DD.
  • Default Currency — Default ISO currency code to use when the currency column is missing or blank.
  • Percentage Columns — Comma-separated list of percentage columns to normalize.
  • Percentage Output Mode — Whether to emit normalized percentages as decimal ratios or percent strings.
  • Rename Columns — JSON object specifying additional rename rules applied after column mapping.

Output shape

a single object representing the normalization result envelope containing normalized rows, column name mapping, and a summary object

The output includes rowCount, columnCount, a mapping of original to final column names, and statistics on normalized values and any warnings or errors encountered during normalization.

Examples

Example 1: Normalize a dataset with configured column mappings and normalization rules

Set amountColumns to 'amount,total', dateColumns to 'date', addCurrencyColumn to true with defaultCurrency 'USD', and set columnMapping to map source columns to canonical names.

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