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Messy Data Cleanup Plan

Clean a messy spreadsheet or CSV: the standard mess taxonomy, the fix per problem in the right order, and the checks that prove it's clean.

Clean this data: {{data_description}} (paste a sample + describe the full set: rows, where it came from, what it's for). Diagnose against the mess taxonomy: duplicates (exact and fuzzy — 'Jon Smith'/'John Smith'), inconsistent formats (dates, phones, casing, whitespace), mixed types in columns, merged-cells and header archaeology, encoding gremlins, and missing values (distinguish blank-means-zero from blank-means-unknown — it changes the fix). Give: the cleanup sequence (order matters — dedupe after normalising, not before), the tool-appropriate method per fix ({{tool}} formulas/features or steps), and the post-clean validation: row counts reconciled, spot-checks, and the summary stats that would expose a botched clean.

Fields like {{ this }} are placeholders — replace them with your own details, or let Aria ask you for them.

data-cleaning csv spreadsheets

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