{"uid":"cap_17ujpghcbR3i-Ou-GgPHz","slug":"purchase-orders-string-normalisation-two-measure-correlation-5adf5edc","name":"Purchase Orders String Normalisation + Two-Measure Correlation","description":"Purchase orders — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied purchase orders records (ordered_amount, received_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-retail-19-033?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","ordered_amount","received_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"store_group":{"type":"string","default":"","maxLength":80},"ordered_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"received_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","ordered_amount":10,"received_amount":1},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","ordered_amount":20,"received_amount":2},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","ordered_amount":15,"received_amount":3},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","ordered_amount":30,"received_amount":4}],"maxItems":200,"minItems":1}}},"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_FZ5GSOjlXn-uih5HJrI6b","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 computes two-measure correlation between ordered_amount and received_amount across up to 200 purchase order rows, returning two analytical reports.","exampleAgentPrompt":"Can you normalize the string fields in my purchase order records and run a correlation analysis between ordered_amount and received_amount? I have about 50 rows with store groups like 'group-a' and 'group-b' across dates in October 2026 — I want two reports: one on string normalisation and one on how the two amounts correlate.","exampleUseCases":[{"title":"Retail fulfillment correlation check","prompt":"I have 120 purchase order rows from our two store groups — each row has an ordered_amount and a received_amount. Can you normalize the text fields and tell me how strongly those two measures correlate across the dataset?"},{"title":"Data quality audit on purchase orders","prompt":"We just exported our purchase order records for Q4 — about 80 rows with dates, store group labels, and two dollar amounts per row. Can you clean up the string fields and give me a correlation report showing whether what we ordered lines up with what we actually received?"},{"title":"Supply chain discrepancy analysis","prompt":"Run string normalisation and a two-measure correlation analysis on these 45 purchase order records for our retail outlets — I want to see if ordered_amount and received_amount move together or if there are systematic gaps between the two."}],"resultDescription":"Returns two independent analytical reports: (1) a string normalisation report that standardises text fields such as store_group across all submitted rows, and (2) a two-measure correlation report quantifying the statistical relationship between ordered_amount and received_amount across the dataset. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, ordered_amount, received_amount) cause row rejection","Date strings not matching YYYY-MM-DD pattern fail schema validation","Submitting fewer than 1 row returns an error","Null values in both numeric measures may reduce correlation reliability","Payment of 0.01 USDC not included causes HTTP 402 response"],"whenToPreferThis":"Choose this endpoint when you have up to 200 purchase order rows with ordered_amount and received_amount fields and need both string normalisation and a correlation report in a single low-cost API call. It is purpose-built for retail purchase order analytics and requires no external data or live lookups, making it ideal for offline or batch data-quality and fulfillment-analysis workflows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:50:43.171Z","isFirstParty":false,"canonicalSlug":"purchase-orders-string-normalisation-two-measure-correlation-5adf5edc"}