{"uid":"cap_LUcPaavr_LQ6ZMMMkwbKJ","slug":"trade-observations-string-normalisation-and-date-by-category-pivot-8b5e6eaf","name":"Trade Observations String Normalisation and Date by Category Pivot","description":"Trade observations — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied trade observations records (export_amount, import_amount). 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-06-035?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","export_amount","import_amount"],"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},"export_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"import_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","export_amount":10,"import_amount":1},{"date":"2026-10-02","region":"group-b","row_id":"row-2","export_amount":20,"import_amount":2},{"date":"2026-10-03","region":"group-a","row_id":"row-3","export_amount":15,"import_amount":3},{"date":"2026-10-04","region":"group-b","row_id":"row-4","export_amount":30,"import_amount":4}],"maxItems":200,"minItems":1},"field":{"enum":["export_amount","import_amount"],"type":"string","default":"export_amount"}}},"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_WKBjvbaWt7Dwv8VC0YrEH","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 produces a date-by-category pivot table for trade observation records (export_amount and import_amount) across up to 200 rows.","exampleAgentPrompt":"Can you normalize the region strings and pivot my trade observations by date and category? Here are 4 rows with export_amount and import_amount fields — row-1: 2026-10-01, group-a, export 10, import 1; row-2: 2026-10-02, group-b, export 20, import 2; row-3: 2026-10-03, group-a, export 15, import 3; row-4: 2026-10-04, group-b, export 30, import 4 — and I want the pivot run on export_amount.","exampleUseCases":[{"title":"Regional export trend pivot","prompt":"I have 50 rows of trade data with regions and dates — can you normalize the region names and pivot the export_amount by date and region so I can see totals per category over time?"},{"title":"Import amount date breakdown","prompt":"Take these trade observation records and run string normalisation on the region column, then give me a date-by-category pivot for import_amount across all the rows I'm sending."},{"title":"Multi-region trade data cleanup","prompt":"I've got a messy trade dataset with inconsistent region labels and export figures for about 120 rows — can you clean up the strings and create a date pivot grouped by region for the export_amount field?"}],"resultDescription":"Two local analytical reports: (1) a string-normalised version of the region field across supplied rows, and (2) a date-by-category pivot table for the chosen field (export_amount or import_amount), aggregating values across up to 200 trade observation rows grouped by date and region.","failureModes":["More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, region, date, export_amount, import_amount) cause validation errors","Invalid date format (not YYYY-MM-DD) rejected by pattern constraint","Numeric values outside ±1,000,000,000,000 range rejected","Invalid field enum value (not export_amount or import_amount) causes error","Empty rows array (minItems: 1) rejected"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation of categorical/region labels AND a date-by-category pivot table in a single $0.01 call for up to 200 trade observation rows. It is purpose-built for trade economics data (export_amount, import_amount) and delivers two complementary reports using shared local engines — no external lookups, live data, or predictions involved. Prefer this over general data tools when your input is structured trade records with region, date, and amount fields.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:31:11.458Z","isFirstParty":false,"canonicalSlug":"trade-observations-string-normalisation-and-date-by-category-pivot-8b5e6eaf"}