{"uid":"cap_Aj7w5c4QoTI6zK0H3zMCX","slug":"returns-handling-analytics-numeric-distribution-date-by-category-pivot-d41102b4","name":"Returns Handling Analytics — Numeric Distribution & Date-by-Category Pivot","description":"Returns handling — Numeric distribution + Date by category pivot: Numeric distribution + Date by category pivot for supplied returns handling records (returned_units, processing_minutes). 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-04-083?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","store_group","date","returned_units","processing_minutes"],"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},"returned_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"processing_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","store_group":"group-a","returned_units":10,"processing_minutes":1},{"date":"2026-10-02","row_id":"row-2","store_group":"group-b","returned_units":20,"processing_minutes":2},{"date":"2026-10-03","row_id":"row-3","store_group":"group-a","returned_units":15,"processing_minutes":3},{"date":"2026-10-04","row_id":"row-4","store_group":"group-b","returned_units":30,"processing_minutes":4}],"maxItems":200,"minItems":1},"field":{"enum":["returned_units","processing_minutes"],"type":"string","default":"returned_units"}}},"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_AgyHPN1iqLJF1aT3AWxEF","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":"Computes two statistical reports (numeric distribution and date-by-category pivot) on supplied returns handling data (returned_units, processing_minutes) for up to 200 rows.","exampleAgentPrompt":"Can you run a numeric distribution and date-by-category pivot on my returns handling data? Here are my records with row IDs, store groups like 'east-region' and 'west-region', dates in YYYY-MM-DD format, returned_units counts, and processing_minutes — analyze the returned_units field across up to 150 rows.","exampleUseCases":[{"title":"Returns volume distribution by store group","prompt":"I have 120 rows of returns data from our three store groups — North, South, and Online — with dates and returned_units counts for each row. Can you run a numeric distribution and a date-by-category pivot on the returned_units field so I can see how return volumes are spread across groups and over time?"},{"title":"Processing time outlier investigation","prompt":"We track how many minutes it takes to process each return at our fulfillment centers. I have 80 records with row IDs, store_group labels, dates, and processing_minutes values. Please compute the numeric distribution and date-by-category pivot for processing_minutes so I can spot which groups or dates have unusually long processing times."},{"title":"Monthly returns trend pivot for retail report","prompt":"I'm preparing a monthly retail operations report and need to analyze about 200 returns records from October. Each row has a store_group, a date, returned_units, and processing_minutes. Can you produce a numeric distribution plus a date-by-category pivot on returned_units so I have the stats I need for the report?"}],"resultDescription":"Two local analytical reports: (1) a numeric distribution for the selected field (returned_units or processing_minutes) showing statistical spread across all supplied rows, and (2) a date-by-category pivot breaking down the same field by date and store_group category — both computed from the supplied data with no external lookups.","failureModes":["Fewer than 1 row submitted — request rejected","More than 200 rows submitted — exceeds row limit","Invalid date format (not YYYY-MM-DD) — schema validation error","Unknown field value outside enum [returned_units, processing_minutes] — schema validation error","Missing required fields (row_id, store_group, date) — validation failure","Null numeric values in selected field may produce incomplete distribution statistics"],"whenToPreferThis":"Choose this endpoint when you have up to 200 returns handling records and need both a statistical numeric distribution and a date-by-category pivot in a single low-cost call. Ideal for retail operations teams doing offline/batch analytics on supplied data without needing live data access, predictions, or external enrichment. At $0.01 USDC for two reports, it is cost-effective for routine periodic analysis of returns metrics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:43:14.922Z","isFirstParty":false,"canonicalSlug":"returns-handling-analytics-numeric-distribution-date-by-category-pivot-d41102b4"}