{"uid":"cap_pmC9_OTje0D7vCxbSY0kj","slug":"brand-mention-inventories-grouped-numeric-summary-iqr-outlier-flags-4b0e260b","name":"Brand Mention Inventories — Grouped Numeric Summary + IQR Outlier Flags","description":"Brand mention inventories — Grouped numeric summary + IQR outlier flags: Grouped numeric summary + IQR outlier flags for supplied brand mention inventories records (mention_count, source_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-18-094?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","mention_count","source_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"mention_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_count":1,"company_group":"group-a","mention_count":10},{"date":"2026-10-02","row_id":"row-2","source_count":2,"company_group":"group-b","mention_count":20},{"date":"2026-10-03","row_id":"row-3","source_count":3,"company_group":"group-a","mention_count":15},{"date":"2026-10-04","row_id":"row-4","source_count":4,"company_group":"group-b","mention_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["mention_count","source_count"],"type":"string","default":"mention_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_qCSbZHr2gA54U317VApj6","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 grouped numeric summary statistics and IQR-based outlier flags for brand mention inventory records (mention_count or source_count), producing two analytical reports from supplied data.","exampleAgentPrompt":"I have a dataset of brand mention records with mention counts and source counts across different company groups — can you group them by company, compute a numeric summary (mean, median, quartiles, etc.), and flag any IQR outliers in the mention_count field? Here are up to 200 rows.","exampleUseCases":[{"title":"Outlier detection in brand mention tracking","prompt":"I've got 150 rows of brand mention data across four company groups — can you compute a grouped numeric summary and flag any mention_count values that are IQR outliers so I can spot unusual spikes or drops?"},{"title":"Source count analysis across competitors","prompt":"Here's my brand inventory dataset with daily source counts for three competitor groups. Can you group it by company and give me the numeric summary stats plus IQR outlier flags on the source_count field?"},{"title":"Monthly brand mention audit by group","prompt":"I'm doing a monthly audit of brand mentions. Can you take these 200 rows of mention inventory records grouped by company and run the grouped numeric summary plus IQR outlier detection on mention_count so I know which entries are statistically unusual?"}],"resultDescription":"Returns two analytical reports: (1) a grouped numeric summary (e.g. mean, median, min, max, quartiles, standard deviation) broken down by company_group for the selected field (mention_count or source_count), and (2) IQR-based outlier flags identifying which individual rows fall outside the interquartile range. No external data is fetched; all analysis is performed on the supplied rows.","failureModes":["Fewer than 1 row supplied returns an error","Rows missing required fields (row_id, company_group, date, mention_count, source_count) cause validation failure","More than 200 rows supplied exceeds the limit and may be rejected","Invalid date format (not YYYY-MM-DD) triggers schema validation error","Null values in the selected field may reduce statistical reliability","Invalid field enum value (not mention_count or source_count) causes rejection"],"whenToPreferThis":"Choose this endpoint when you have pre-collected brand mention inventory data (up to 200 rows) and need both grouped summary statistics and IQR outlier detection in a single call for $0.01 USDC. It is ideal for offline or batch analytical workflows where no live data lookup is needed and you want two reports — grouped aggregates and outlier flags — from a shared local analytical engine.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T12:48:29.943Z","isFirstParty":false,"canonicalSlug":"brand-mention-inventories-grouped-numeric-summary-iqr-outlier-flags-4b0e260b"}