{"uid":"cap_8fwomeCoiWQYPELz_cQkP","slug":"market-survey-observations-category-frequencies-iqr-outlier-flags-506df1b4","name":"Market Survey Observations — Category Frequencies + IQR Outlier Flags","description":"Market survey observations — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags 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-06-107?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_1EHlI4a6GX6k4E1dYz4lv","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":"Computes category frequencies and IQR-based outlier flags for market survey observation records, covering respondent_count or sample_weight fields across up to 200 rows.","exampleAgentPrompt":"Analyze my market survey data for category frequencies and IQR outlier flags on the respondent_count field — here are the rows: row-1, group-a, 2026-10-01, respondent_count=10, sample_weight=1; row-2, group-b, 2026-10-02, respondent_count=20, sample_weight=2; row-3, group-a, 2026-10-03, respondent_count=15, sample_weight=3.","exampleUseCases":[{"title":"Survey panel quality audit","prompt":"I have 150 rows of market survey responses from our Q3 study across three company groups — can you compute how frequently each group appears and flag any rows where respondent_count looks like an IQR outlier?"},{"title":"Sample weight anomaly detection","prompt":"Run category frequency counts and IQR outlier detection on the sample_weight field for these 80 survey observation records — I need to know which weights are statistically unusual before we weight the final results."},{"title":"Pre-reporting data validation","prompt":"Before I publish these market survey results, check the respondent_count field across all 200 rows: give me a breakdown of how often each company_group shows up and highlight any outlier rows using IQR bounds."}],"resultDescription":"Returns two analytical reports: (1) category frequency counts showing how often each company_group value appears in the dataset, and (2) IQR-based outlier flags identifying which rows have respondent_count or sample_weight values that fall outside the interquartile range bounds. Up to 200 rows processed per call.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, company_group, date, respondent_count, sample_weight) cause rejection","Invalid date format (not YYYY-MM-DD) fails schema validation","Null values in numeric fields may affect IQR calculations","Invalid field selector (not 'respondent_count' or 'sample_weight') returns an error"],"whenToPreferThis":"Choose this endpoint when you need both category frequency analysis and IQR outlier detection simultaneously on market survey observation data with company_group segmentation, and your dataset fits within 200 rows. It delivers two complementary statistical reports in a single $0.01 call using local computation with no external data access, making it ideal for fast, cost-effective pre-analysis or data quality checks on survey exports.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:05.399Z","isFirstParty":false,"canonicalSlug":"market-survey-observations-category-frequencies-iqr-outlier-flags-506df1b4"}