{"uid":"cap_MSFPTcjynuoRUfGuup0QP","slug":"supplier-fill-string-normalisation-explicit-missing-value-fill-54939055","name":"Supplier Fill — String Normalisation + Explicit Missing-Value Fill","description":"Supplier fill — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied supplier fill records (ordered_units, received_units). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-retail-06-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","ordered_units","received_units"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"store_group":{"type":"string","default":"","maxLength":80},"ordered_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"received_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","ordered_units":10,"received_units":1},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","ordered_units":20,"received_units":2},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","ordered_units":15,"received_units":3},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","ordered_units":30,"received_units":4}],"maxItems":200,"minItems":1},"field":{"enum":["ordered_units","received_units"],"type":"string","default":"ordered_units"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_NDzOpUis_R63utGYPeoCU","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Normalises string fields and fills missing ordered_units or received_units values using zero, mean, or median imputation across up to 200 supplier fill rows.","exampleAgentPrompt":"I have a supplier fill dataset with up to 50 rows including store_group, date, ordered_units, and received_units — some received_units are null. Can you normalize the string fields and fill the missing received_units using the median method?","exampleUseCases":[{"title":"Fill null ordered units for retailer","prompt":"I've got a supplier fill table with 80 rows where some ordered_units are null — can you normalize the strings and fill in those missing ordered_units using the mean across the dataset?"},{"title":"Zero-fill missing received units","prompt":"My supplier records for store group 'region-west' have several missing received_units values across 30 rows — please normalize the store group strings and fill all the nulls with zero."},{"title":"Median imputation for inventory audit","prompt":"Before my weekly inventory audit, I need you to clean up this supplier fill dataset of 120 rows: normalize the string columns and use median imputation to fill any missing ordered_units values."}],"resultDescription":"Returns up to 2 analytical reports per call covering: (1) string normalisation results for string fields such as store_group, and (2) explicit missing-value fill results for the specified numeric field (ordered_units or received_units), using the chosen imputation method (zero, mean, or median). Processed rows reflect corrected/filled values for up to 200 input rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, ordered_units, received_units) on any row — validation error","Invalid date format not matching YYYY-MM-DD pattern — schema rejection","Numeric values outside allowed range (-1e12 to 1e12) — validation error","Invalid enum value for field or method — schema rejection","Empty rows array — minimum items violation"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local (no external lookup) string normalisation and numeric missing-value imputation on supplier fill records (ordered_units, received_units) for up to 200 rows at low cost. Ideal for pre-processing retail supply chain data before aggregation or reporting when all data is already supplied and no prediction or external enrichment is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:50:18.983Z","isFirstParty":false,"canonicalSlug":"supplier-fill-string-normalisation-explicit-missing-value-fill-54939055"}