{"uid":"cap_LbxEeKTZRx1o8EoZBlq1b","slug":"customer-segment-observations-daily-sum-series-explicit-missing-value-90630755","name":"Customer Segment Observations — Daily Sum Series + Explicit Missing-Value Fill","description":"Customer segment observations — Daily sum series + Explicit missing-value fill: Daily sum series + 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-16-145?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_BFhiuIfKvMcyEO3BQmKqT","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 daily sum time series and fills missing values (zero, mean, or median) for customer segment observation data (account_count, revenue_amount) across up to 200 rows.","exampleAgentPrompt":"Take my customer segment records (up to 200 rows with row_id, company_group, date, account_count, and revenue_amount) and compute the daily sum series for account_count, filling any missing values using the median method.","exampleUseCases":[{"title":"Daily revenue roll-up with gap filling","prompt":"I have 150 rows of customer segment observations with dates, company groups, and revenue_amount values — some are null. Can you compute the daily sum series for revenue_amount and fill in the missing entries using the mean?"},{"title":"Account count aggregation by segment","prompt":"Here are my customer segment rows with account_count and company_group fields. Please aggregate them into a daily sum series for account_count and use zero to fill any missing values."},{"title":"Multi-group segment reporting with null imputation","prompt":"I need a daily sum report for account_count across my company groups — the dataset has about 80 rows with some nulls. Run both the daily sum series and fill missing values using median so I get clean output for both reports."}],"resultDescription":"Returns two analytical reports: (1) a daily sum time series for the specified field (account_count or revenue_amount) aggregated across the supplied rows, and (2) the same series with explicit missing-value imputation applied using the chosen method (zero, mean, or median). Results cover up to 200 input rows processed locally without external lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required row fields (row_id, date, company_group) — validation error","Invalid date format (must match YYYY-MM-DD) — pattern validation failure","Numeric values outside allowed range (±1,000,000,000,000) — schema rejection","Empty rows array — minItems violation","Invalid method enum value — rejected with schema error","Invalid field enum value — rejected with schema error"],"whenToPreferThis":"Choose this endpoint when you have raw customer segment observation records (with account_count or revenue_amount) that need daily sum aggregation combined with explicit missing-value imputation in a single low-cost call. Ideal for offline/batch analytical prep of segment data up to 200 rows where no live data lookup, prediction, or external service is needed. The $0.01 flat rate covers two reports simultaneously, making it cost-efficient for dual-output needs.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T12:44:58.516Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-daily-sum-series-explicit-missing-value-90630755"}