{"uid":"cap_LbP2ByS0x4clv57fKlDOf","slug":"competitor-supplied-prices-numeric-distribution-explicit-missing-0d43832d","name":"Competitor Supplied Prices — Numeric Distribution + Explicit Missing-Value Fill","description":"Competitor supplied prices — Numeric distribution + Explicit missing-value fill: Numeric distribution + 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-07-085?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_jI1LEnWBKjpbUb_aNgiKZ","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":"Analyzes up to 200 rows of competitor price data by computing a numeric distribution report and filling missing values in list_price or package_quantity using zero, mean, or median imputation.","exampleAgentPrompt":"I have up to 200 rows of competitor price data with company group, date, list_price, and package_quantity — some list_price values are null. Can you run a numeric distribution report on list_price and fill in the missing values using median imputation?","exampleUseCases":[{"title":"Impute missing competitor list prices","prompt":"I have a dataset of 150 competitor price records from the last quarter. Some list_price entries are null — can you fill them using median imputation and also show me the full numeric distribution of list_price across those rows?"},{"title":"Analyze package quantity spread by group","prompt":"I need two reports on my competitor data: a numeric distribution of package_quantity, and a fill of any missing package_quantity values using the mean. There are about 80 rows covering groups A, B, and C."},{"title":"Zero-fill missing prices before downstream export","prompt":"Before I export my competitor pricing dataset, I want to zero-fill any missing list_price values and get a distribution summary of list_price for the 200 rows I have — company_group, date, and row_id are all populated already."}],"resultDescription":"Returns two analytical reports: (1) a numeric distribution summary of the selected field (list_price or package_quantity) across up to 200 supplied rows, and (2) a dataset with missing values in the selected field explicitly filled using the chosen method (zero, mean, or median). No external lookups or predictions are made — all computation is performed locally on the supplied data.","failureModes":["Exceeding 200 rows causes a rejection or truncation error","Invalid or missing row_id, company_group, or date fields cause schema validation failures","Date strings not matching YYYY-MM-DD pattern are rejected","Choosing an unsupported imputation method (not zero, mean, or median) causes an error","All values in the target field being null may cause mean/median to be undefined","Numeric values outside the allowed range cause validation errors","Empty rows array returns an error due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you already have structured competitor pricing data (up to 200 rows) and need both a distribution summary and missing-value imputation in a single call, without requiring any live market lookup, external enrichment, or predictive modeling. It is ideal for data cleaning pipelines before exporting or visualizing competitor price data, especially when null values in list_price or package_quantity need to be handled systematically.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:07.553Z","isFirstParty":false,"canonicalSlug":"competitor-supplied-prices-numeric-distribution-explicit-missing-0d43832d"}