{"uid":"cap_RlK6BNE2Mzp1VY6qBwLRZ","slug":"price-basket-observations-numeric-interval-filter-explicit-missing-cb9ce1a2","name":"Price Basket Observations — Numeric Interval Filter + Explicit Missing-Value Fill","description":"Price basket observations — Numeric interval filter + Explicit missing-value fill: Numeric interval filter + Explicit missing-value fill for supplied price basket observations records (item_price, quantity_weight). 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-economics-07-135?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","item_price","quantity_weight"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"item_price":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"quantity_weight":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","item_price":10,"quantity_weight":1},{"date":"2026-10-02","region":"group-b","row_id":"row-2","item_price":20,"quantity_weight":2},{"date":"2026-10-03","region":"group-a","row_id":"row-3","item_price":15,"quantity_weight":3},{"date":"2026-10-04","region":"group-b","row_id":"row-4","item_price":30,"quantity_weight":4}],"maxItems":200,"minItems":1},"field":{"enum":["item_price","quantity_weight"],"type":"string","default":"item_price"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_uw6cnQ3Uufh5i96NMuJqs","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":"Filters price basket observation rows by a numeric interval on a chosen field and fills missing values using a specified method (zero, mean, or median), returning up to 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 150 rows of price basket data with item_price and quantity_weight columns — some prices are null. Can you filter the rows where item_price falls between 0 and 500, fill any missing item_price values using the median, and give me 2 analytical reports on the result?","exampleUseCases":[{"title":"Clean retail price basket for analysis","prompt":"I've got about 80 rows of retail basket observations with item_price and quantity_weight. Some item_price entries are missing — fill them with the median and only keep rows where item_price is between 5 and 250. Give me both analytical reports."},{"title":"Filter grocery quantity data by weight range","prompt":"Here are 120 grocery basket records. I want to filter so only rows with quantity_weight between 0.5 and 50 are kept, and fill any null quantity_weight values with the mean. Run the two reports on the cleaned data."},{"title":"Zero-fill missing prices in economics dataset","prompt":"I have an economics dataset of 60 price basket observations — some item_price values are null. Please fill the missing item_price values with zero and filter to only include rows where item_price is between 0 and 1000, then produce the two summary reports."}],"resultDescription":"Two local analytical reports covering the interval-filtered and missing-value-filled price basket observation rows. Reports summarize the cleaned dataset (up to 200 rows) based on item_price or quantity_weight, reflecting the chosen fill method (zero, mean, or median) and numeric min/max bounds. No external lookups or predictions are included.","failureModes":["More than 200 rows submitted — request rejected or truncated","Invalid date format in row (must match YYYY-MM-DD)","Minimum value exceeds maximum value in interval filter — may return empty result set","Null row_id or row_id exceeding 80 characters — validation error","Field value outside allowed numeric range (±1,000,000,000,000) — schema rejection","Payment of 0.01 USDC not completed — 402 response returned"],"whenToPreferThis":"Choose this endpoint when you have tabular price basket observation data (item_price, quantity_weight) that needs both numeric range filtering and missing-value imputation in a single call, and you want two analytical reports on the cleaned result. It is ideal for small-to-medium datasets (up to 200 rows) where you want a fast, self-contained local computation without external lookups or live market data. Prefer it over general-purpose analytics tools when your specific workflow involves economics or retail basket data cleaning at low cost ($0.01 per call).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:50:48.380Z","isFirstParty":false,"canonicalSlug":"price-basket-observations-numeric-interval-filter-explicit-missing-cb9ce1a2"}