{"uid":"cap_9uw_9jNHGiQzS91ifJoIJ","slug":"business-event-participation-numeric-interval-filter-trailing-mean-18b2f29c","name":"Business Event Participation — Numeric Interval Filter + Trailing Mean Series","description":"Business event participation — Numeric interval filter + Trailing mean series: Numeric interval filter + Trailing mean series for supplied business event participation records (attendee_count, company_count). 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-19-126?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","attendee_count","company_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"attendee_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_count":1,"company_group":"group-a","attendee_count":10},{"date":"2026-10-02","row_id":"row-2","company_count":2,"company_group":"group-b","attendee_count":20},{"date":"2026-10-03","row_id":"row-3","company_count":3,"company_group":"group-a","attendee_count":15},{"date":"2026-10-04","row_id":"row-4","company_count":4,"company_group":"group-b","attendee_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["attendee_count","company_count"],"type":"string","default":"attendee_count"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_JpQafAUBK8ZvZBnbbn_6b","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":"Filters business event participation rows by a numeric interval and computes a trailing mean time series for attendee_count or company_count, returning 2 analytical reports for up to 200 supplied rows.","exampleAgentPrompt":"I have 150 rows of business event participation data with attendee_count and company_count by date and group — can you filter rows where attendee_count is between 10 and 500, then compute a trailing mean series with a window of 7 using the attendee_count field?","exampleUseCases":[{"title":"Attendee range filtering with rolling average","prompt":"Here are my 80 event participation records by date. Filter them to only include rows where attendee_count is between 20 and 300, and then give me a trailing mean series with a window of 5 for the attendee_count field."},{"title":"Company count trend smoothing","prompt":"I've got 120 rows of business event data. I want to filter by company_count between 1 and 50 and compute a trailing mean series with a window of 3 on company_count — can you run both reports for me?"},{"title":"Outlier exclusion before trend analysis","prompt":"Can you take these 200 business event participation rows, exclude any where attendee_count falls outside the range of 5 to 250, and then generate a trailing mean series with a window of 10 on attendee_count?"}],"resultDescription":"Returns 2 analytical reports per call: (1) a numeric interval-filtered subset of the supplied rows based on the specified field, minimum, and maximum thresholds; and (2) a trailing mean time series computed over the specified window size for the chosen field (attendee_count or company_count). All computation is performed locally on the supplied data — no external lookups or live data are used.","failureModes":["Fewer than 1 or more than 200 rows supplied — request rejected","Invalid date format (not YYYY-MM-DD) — validation error","Window size outside 2–200 range — validation error","Minimum greater than maximum — may produce empty filtered result set","Null values in the selected field — may affect trailing mean calculation","Missing required row fields (row_id, company_group, date) — schema validation error"],"whenToPreferThis":"Choose this endpoint when you have pre-collected business event participation data (up to 200 rows) and need both a numeric range filter and a trailing mean time series computed in a single call. It is ideal for smoothing event attendance trends, excluding outliers by numeric bounds, and getting two complementary analytical views in one low-cost operation. Prefer it over general-purpose analytics when your data fits the business event participation schema (attendee_count, company_count) and you need a fast, deterministic, no-side-effect computation without live data dependencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:55:47.994Z","isFirstParty":false,"canonicalSlug":"business-event-participation-numeric-interval-filter-trailing-mean-18b2f29c"}