{"uid":"cap_p90n2NhcfnvTQiIWlKP73","slug":"market-survey-observations-numeric-interval-filter-two-measure-3a1fec8d","name":"Market Survey Observations — Numeric Interval Filter + Two-Measure Correlation","description":"Market survey observations — Numeric interval filter + Two-measure correlation: Numeric interval filter + Two-measure correlation 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-06-131?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"},"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_PVXtiFEp0BJ4yEsFAqN9V","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 market survey observation rows by a numeric interval on a selected field and computes a two-measure correlation between respondent_count and sample_weight, returning two independent analytical reports for up to 200 rows.","exampleAgentPrompt":"I have market survey observations for groups A and B across October 2026 — can you filter rows where respondent_count is between 5 and 25, then run a two-measure correlation between respondent_count and sample_weight across all the rows?","exampleUseCases":[{"title":"Survey panel size vs weighting correlation","prompt":"I've got 80 rows of market survey data with respondent_count and sample_weight per company group. Filter to rows where respondent_count is between 10 and 50, then compute the correlation between respondent_count and sample_weight so I can see if bigger panels are being weighted differently."},{"title":"Outlier exclusion before correlation report","prompt":"Can you take my survey observations — about 150 rows across groups Alpha and Beta — filter out anything where sample_weight falls outside 0.5 to 200, and then run a two-measure correlation between sample_weight and respondent_count? I want to exclude extreme weights before drawing conclusions."},{"title":"Group comparison with filtered interval","prompt":"I have quarterly market survey data for two company groups and want to understand how respondent count relates to sample weight. Please filter to the date range 2026-10-01 through 2026-10-04 using a respondent_count minimum of 0 and maximum of 100, then give me the correlation between respondent_count and sample_weight."}],"resultDescription":"Returns two independent analytical reports: (1) a numeric interval filter report listing which of the up to 200 survey rows fall within the specified minimum–maximum range for the chosen field, and (2) a two-measure correlation report quantifying the statistical relationship between respondent_count and sample_weight across the supplied rows. Both reports are generated locally without external lookups.","failureModes":["Rows array exceeds 200 items — request rejected","Missing required row fields (row_id, date, company_group) — validation error","Invalid date format (must be YYYY-MM-DD) — schema validation failure","Minimum value greater than maximum value — may return empty filtered set","Null values in respondent_count or sample_weight — correlation computation may return NaN or be skipped","Field enum value not recognized — schema rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 market survey observation records with respondent_count and sample_weight fields and need both a numeric range filter and a correlation analysis in a single low-cost call ($0.01 USDC). It is ideal for self-contained, offline analytical tasks on supplied data where no live data lookup, prediction, or external enrichment is needed. Prefer it over general-purpose analytics tools when working specifically with survey panel data combining group labels, dates, and two numeric measures.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:26.315Z","isFirstParty":false,"canonicalSlug":"market-survey-observations-numeric-interval-filter-two-measure-3a1fec8d"}