{"uid":"cap_ZDjN37HA2kieDhAwKnQik","slug":"price-basket-observations-string-normalisation-date-by-category-pivot-51fd4901","name":"Price Basket Observations — String Normalisation + Date by Category Pivot","description":"Price basket observations — String normalisation + Date by category pivot: String normalisation + Date by category pivot 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-07-035?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"}}},"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_ZUOYZ0XPnqDpZeoPAciSa","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":"Runs two local analytical reports on price basket observation data: string normalisation and a date-by-category pivot, for up to 200 rows of item_price or quantity_weight records.","exampleAgentPrompt":"Can you run string normalisation and a date-by-category pivot on my price basket observations? I have rows with item_price values across regions like group-a and group-b, dated from 2026-10-01 to 2026-10-04, and I want both reports for the item_price field.","exampleUseCases":[{"title":"Regional price basket pivot analysis","prompt":"I have 150 rows of price basket observations with item prices across three regions and weekly dates — can you normalise the strings and pivot the data by date and category so I can see how prices vary across regions over time?"},{"title":"Quantity weight distribution by category","prompt":"Take my basket records with quantity_weight values across multiple regions and dates and give me both reports: the string-normalised version and the date-by-category pivot, using the quantity_weight field."},{"title":"Economics data cleanup and summary","prompt":"I've got about 80 price basket rows for an economics report — each has a date, region, item price, and quantity weight. Can you normalise the text fields and produce a date-by-category pivot for item_price so I can spot patterns by region?"}],"resultDescription":"Returns two analytical reports for the supplied price basket observation rows: (1) a string normalisation report cleaning and standardising text fields, and (2) a date-by-category pivot table grouping either item_price or quantity_weight values by date and region/category. No external data is fetched; all analysis runs locally on the supplied rows.","failureModes":["Rows array is empty or exceeds 200 items — validation error returned","Invalid date format (not YYYY-MM-DD) in any row — schema validation failure","item_price or quantity_weight values outside allowed numeric range — rejection","Missing required fields (row_id, region, date) on any row — schema error","Invalid field selector (not 'item_price' or 'quantity_weight') — enum validation error","Payment not provided or insufficient USDC — 402 Payment Required"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of price basket observation data (with item_price and quantity_weight fields) and need both string normalisation and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal for offline, local analytical processing of economics or retail basket data without any live lookups or predictions. Prefer it over general-purpose analytics tools when you need these two specific report types bundled together cheaply.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T13:06:43.508Z","isFirstParty":false,"canonicalSlug":"price-basket-observations-string-normalisation-date-by-category-pivot-51fd4901"}