Turn Cleanup Into an Algorithm
Convert a manual data-cleaning task into a sequenced algorithm with validation checks.
A Friday revenue CSV contains account IDs with spaces, currency as text, duplicate invoice rows, and occasional malformed amounts. Input contract -> ordered transformations -> validation checks -> exception route The common shortcut is to clean by sight: fix visible cells, sum the column, and hope no invisible formatting or duplicate-key issue remains. Define valid input Require account_id, invoice_id, invoice_month, and amount; reject rows missing any required field. A cleanup algorithm needs preconditions so bad rows do not silently flow downstream. Normalize identifiers Trim spaces, uppercase account IDs, and standardize invoice month to YYYY-MM before matching. Normalize keys before joins…
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