{"uid":"cap_0lzSyVrkzTm9ndRGrSrc_","slug":"market-survey-observations-string-normalisation-numeric-row-ordering-ab73613d","name":"Market Survey Observations — String Normalisation + Numeric Row Ordering","description":"Market survey observations — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied market survey observations records (respondent_count, sample_weight). 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-06-025?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","respondent_count","sample_weight"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"sample_weight":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"respondent_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","sample_weight":1,"respondent_count":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","sample_weight":2,"respondent_count":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","sample_weight":3,"respondent_count":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","sample_weight":4,"respondent_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["respondent_count","sample_weight"],"type":"string","default":"respondent_count"}}},"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_BwIQypdwawVSiQ3zdoFY0","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 sorts rows numerically for market survey observation records containing respondent_count and sample_weight fields, producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you run string normalisation and numeric row ordering on my market survey data? I have 4 rows with company groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, and I want the analysis on the respondent_count field — give me the two reports.","exampleUseCases":[{"title":"Cleaning survey group labels before reporting","prompt":"I have market survey observations from three company groups collected last quarter — the company_group strings are inconsistently formatted. Can you normalise those strings and order all 80 rows by respondent_count so I get clean, sorted output in two reports?"},{"title":"Ordering survey rows by sample weight","prompt":"Take my 50 market survey observation rows with row IDs row-1 through row-50, company groups 'Alpha Corp' and 'Beta Ltd', dates in October 2026, and sort them by sample_weight numerically while also normalising the string fields — I need the two analytical reports."},{"title":"Pre-processing survey data for downstream analysis","prompt":"Before I feed my market survey results into our dashboard, can you clean up the string fields and sort the 120 rows numerically by respondent_count? Each row has a row_id, company_group, date, respondent_count, and sample_weight — I need two processed reports back."}],"resultDescription":"Two analytical reports covering the supplied market survey observation rows: one applying string normalisation to text fields (such as company_group) and one ordering rows numerically by the selected field (respondent_count or sample_weight). No external lookups or predictions are made; analysis is performed locally on the provided data.","failureModes":["Rows array empty or missing — returns validation error","More than 200 rows supplied — rejected with maxItems error","Invalid date format (not YYYY-MM-DD) — schema validation failure","field value not in enum ['respondent_count','sample_weight'] — rejected","Numeric fields out of allowed range (±1,000,000,000,000) — validation error","Payment not included or insufficient USDC — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local string normalisation and numeric row ordering on market survey data (respondent_count or sample_weight fields) without requiring any external data lookups, predictions, or live integrations. It is ideal for pre-processing up to 200 survey observation rows cheaply ($0.01 USDC for two reports). Prefer alternatives if you need pivot tables, histogram generation, weighted means, or other analytical transformations offered by sibling endpoints.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:32.901Z","isFirstParty":false,"canonicalSlug":"market-survey-observations-string-normalisation-numeric-row-ordering-ab73613d"}