{"uid":"cap__R8JQxYg6kq3jxaT5iJ52","slug":"competitor-supplied-prices-string-normalisation-explicit-missing-d4a303fc","name":"Competitor Supplied Prices — String Normalisation + Explicit Missing-Value Fill","description":"Competitor supplied prices — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied competitor supplied prices records (list_price, package_quantity). 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-company-07-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","list_price","package_quantity"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"list_price":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"package_quantity":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","list_price":10,"company_group":"group-a","package_quantity":1},{"date":"2026-10-02","row_id":"row-2","list_price":20,"company_group":"group-b","package_quantity":2},{"date":"2026-10-03","row_id":"row-3","list_price":15,"company_group":"group-a","package_quantity":3},{"date":"2026-10-04","row_id":"row-4","list_price":30,"company_group":"group-b","package_quantity":4}],"maxItems":200,"minItems":1},"field":{"enum":["list_price","package_quantity"],"type":"string","default":"list_price"},"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_OwcmdfQ7gaBXDriIeAZtB","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 numeric values (list_price, package_quantity) in competitor supplied prices records using statistical imputation methods (zero, mean, or median).","exampleAgentPrompt":"I have up to 200 rows of competitor supplied prices with some null list_price entries — can you run string normalisation and fill the missing list_price values using median imputation, then give me the two analytical reports?","exampleUseCases":[{"title":"Impute missing competitor list prices","prompt":"I've got a batch of 150 competitor pricing records where some list_price values are null — please clean the strings and fill those gaps using median imputation so I can use the data in our pricing model."},{"title":"Standardise package quantity data","prompt":"Our competitor price feed has messy string formatting and about 30 rows with missing package_quantity values — can you normalise the strings and fill the blanks using mean imputation across all rows?"},{"title":"Zero-fill missing prices for reporting","prompt":"I need to prep these 80 competitor supplied price records for a report — normalise the string fields and set any missing list_price entries to zero so nothing is blank in the output."}],"resultDescription":"Returns two independent analytical reports covering string normalisation results and explicit missing-value fills for up to 200 rows of competitor pricing data, applied to the specified numeric field (list_price or package_quantity) using the chosen imputation method (zero, mean, or median). No external lookups or predictions are performed; all processing is local.","failureModes":["More than 200 rows submitted — request rejected or truncated","Invalid date format (not YYYY-MM-DD) — validation error","Missing required field (row_id, company_group, date) — schema validation failure","Numeric value outside allowed range (±1,000,000,000,000) — rejected","Invalid enum value for field or method — schema validation error","Empty rows array — minItems constraint violation"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of competitor supplied pricing data that need both string normalisation and statistical missing-value imputation in a single low-cost call ($0.01 USDC). It is best suited for batch offline cleaning prior to analysis or reporting, not for real-time lookups or large-scale datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:03.952Z","isFirstParty":false,"canonicalSlug":"competitor-supplied-prices-string-normalisation-explicit-missing-d4a303fc"}