{"uid":"cap_f5_lrXEBZcZ8urQGrZNG0","slug":"customer-segment-observations-grouped-numeric-summary-explicit-bced40e5","name":"Customer Segment Observations — Grouped Numeric Summary + Explicit Missing-Value Fill","description":"Customer segment observations — Grouped numeric summary + Explicit missing-value fill: Grouped numeric summary + Explicit missing-value fill for supplied customer segment observations records (account_count, revenue_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-company-16-099?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","account_count","revenue_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"account_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"revenue_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","account_count":10,"company_group":"group-a","revenue_amount":1},{"date":"2026-10-02","row_id":"row-2","account_count":20,"company_group":"group-b","revenue_amount":2},{"date":"2026-10-03","row_id":"row-3","account_count":15,"company_group":"group-a","revenue_amount":3},{"date":"2026-10-04","row_id":"row-4","account_count":30,"company_group":"group-b","revenue_amount":4}],"maxItems":200,"minItems":1},"field":{"enum":["account_count","revenue_amount"],"type":"string","default":"account_count"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_CSf4q0dxhtRtfCZqSodSc","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 a grouped numeric summary and fills missing values for customer segment observation records (account_count, revenue_amount) across up to 200 rows.","exampleAgentPrompt":"I have a set of customer segment records with company_group, date, account_count, and revenue_amount — some values are null. Can you group them by company and compute a numeric summary, then fill the missing account_count values using median imputation? Here are up to 200 rows.","exampleUseCases":[{"title":"Monthly revenue rollup by company group","prompt":"I have 150 rows of customer segment observations with company_group, date, and revenue_amount — some revenue figures are missing. Can you group them by company and give me a numeric summary, filling the missing revenue_amount values using the mean?"},{"title":"Account count gap-fill before dashboard load","prompt":"Before I push our segment data to the dashboard, can you fill in the null account_count values using median imputation and give me a grouped summary by company_group? I have about 80 rows covering Q3."},{"title":"Zero-fill missing segments for compliance report","prompt":"I need to prepare a compliance export from our customer segment table — any null account_count entries should be replaced with zero. Can you also give me a grouped numeric summary by company_group across these 200 rows?"}],"resultDescription":"Returns two reports: (1) a grouped numeric summary (e.g. count, min, max, mean per company_group) for the specified field across all supplied rows, and (2) the same dataset with missing values in the chosen field explicitly filled using the selected method (zero, mean, or median). Both reports are computed locally without external lookups.","failureModes":["More than 200 rows submitted — request rejected","Missing required fields (row_id, company_group, date) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Invalid fill method value not in [zero, mean, median] — enum error","Invalid field value not in [account_count, revenue_amount] — enum error","Empty rows array — minimum item count violation"],"whenToPreferThis":"Choose this endpoint when you need both grouped aggregate statistics and missing-value imputation for customer segment data (account_count or revenue_amount) in a single low-cost call. Ideal for pre-processing segment exports before dashboards, reports, or downstream ML pipelines when you have up to 200 rows and do not need external data enrichment or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T12:48:34.704Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-grouped-numeric-summary-explicit-bced40e5"}