{"uid":"cap_5nmQzw-M3x38QDDvxvSn_","slug":"survey-participation-data-quality-audit-string-normalisation-weighted-f55e8248","name":"Survey Participation Data Quality Audit, String Normalisation & Weighted Mean","description":"Survey participation — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied survey participation records (respondents, invitations). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-education-10-205?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","course_group","date","respondents","invitations"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"invitations":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"respondents":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"course_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","invitations":1,"respondents":10,"course_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","invitations":2,"respondents":20,"course_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","invitations":3,"respondents":15,"course_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","invitations":4,"respondents":30,"course_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["respondents","invitations"],"type":"string","default":"respondents"}}},"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_VgPYcwG6uz-KCij4vPDs8","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":"Runs three analytical reports on survey participation records: a record quality audit, string normalisation, and a secondary-measure weighted mean — all processed locally against supplied data.","exampleAgentPrompt":"Can you audit the quality of these survey participation records, normalise the course_group strings, and compute a weighted mean on the respondents field? I have up to 50 rows with columns for row_id, date, course_group, respondents, and invitations.","exampleUseCases":[{"title":"Education survey data cleanup","prompt":"I have a batch of 80 survey participation rows from our course groups — some dates might be malformed and group names are inconsistently cased. Can you run a quality audit, normalise the course_group strings, and give me the weighted mean for respondents?"},{"title":"Invitation response rate analysis","prompt":"Run the three analytical reports on these 120 survey records — I want a quality audit of the rows, normalised course group labels, and a weighted mean computed on the invitations field."},{"title":"Pre-analysis data validation for survey team","prompt":"Before we hand this survey dataset off to the analytics team, can you do a record quality audit, clean up the string formatting in course_group, and calculate the weighted mean for respondents across all 35 rows?"}],"resultDescription":"Three local analytical reports: (1) a record quality audit flagging malformed, missing, or out-of-range values per row; (2) normalised string output for the course_group field; (3) a weighted mean of the selected measure (respondents or invitations) across the supplied rows. All processing is done on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, date, respondents, invitations, course_group) cause row-level errors","Date strings not matching YYYY-MM-DD pattern will fail validation","Null numeric values may be flagged in quality audit","Payment of 0.01 USDC not provided causes 402 rejection"],"whenToPreferThis":"Choose this endpoint when you need three specific analytical operations — quality auditing, string normalisation, and weighted mean computation — applied together to a batch of survey participation records (up to 200 rows) in a single low-cost API call. It is ideal for pre-processing educational survey data locally without any external data lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:34:46.757Z","isFirstParty":false,"canonicalSlug":"survey-participation-data-quality-audit-string-normalisation-weighted-f55e8248"}