{"uid":"cap_nWEQubO3j1RBlAHxBJUy5","slug":"business-event-participation-string-normalisation-two-measure-06e39840","name":"Business Event Participation — String Normalisation + Two-Measure Correlation","description":"Business event participation — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation 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-19-033?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}}},"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_yTSthQgIhvQp_x7h_qsUX","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 a two-measure correlation between attendee_count and company_count across up to 200 business event participation rows, returning two analytical reports.","exampleAgentPrompt":"Can you run string normalisation and a two-measure correlation on my business event participation data? I have 4 rows with company groups like 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, attendee counts of 10, 20, 15, and 30, and company counts of 1, 2, 3, and 4 — I want two reports back showing how attendee count and company count relate.","exampleUseCases":[{"title":"Event ROI correlation analysis","prompt":"I have records from 12 business conferences this year — each row has the event date, a company group label, how many attendees showed up, and how many companies participated. Can you normalise the company group strings and tell me whether higher company count correlates with more attendees? I need two separate reports."},{"title":"Trade show participation benchmarking","prompt":"We ran 50 trade show events across two groups, 'enterprise' and 'smb', and I want to clean up the group name strings and then see the statistical correlation between attendee_count and company_count across all rows. Can you give me two analytical reports?"},{"title":"Quarterly event data QA and stats","prompt":"Here are 80 rows of our quarterly networking event data — each has a row ID, date, company group, attendee count, and company count. Please normalise the string fields and compute a two-measure correlation so I can see how attendee numbers relate to company participation numbers."}],"resultDescription":"Returns two independent analytical reports: (1) string-normalised versions of the input text fields (such as company_group), and (2) a two-measure correlation result quantifying the statistical relationship between attendee_count and company_count across the supplied rows. No external lookups or predictions are made; all computation uses local analytical engines on the supplied data.","failureModes":["Exceeding 200 rows causes a validation error; trim input to 200 rows or fewer","Missing required fields (row_id, company_group, date, attendee_count, company_count) results in schema validation failure","Dates not matching YYYY-MM-DD pattern are rejected","Null values in both numeric measures may produce undefined or null correlation output","Sending fewer than 1 row fails minItems constraint","Extreme numeric values (beyond ±1,000,000,000,000) are rejected"],"whenToPreferThis":"Choose this endpoint when you have tabular business event participation data with exactly two numeric measures (attendee_count and company_count) and need both string normalisation of categorical fields and a statistical correlation between those two measures in a single API call. It is best suited for offline/batch analysis of up to 200 rows with no need for live data, predictions, or external enrichment. Prefer alternatives if you need more than two measures correlated, more than 200 rows processed, or real-time event data integration.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:57:19.144Z","isFirstParty":false,"canonicalSlug":"business-event-participation-string-normalisation-two-measure-06e39840"}