{"uid":"cap_eee1uefdb7aRwrwglk6rr","slug":"humidity-observations-iqr-outlier-flags-and-secondary-measure-e2917c91","name":"Humidity Observations IQR Outlier Flags and Secondary-Measure Weighted Mean","description":"Humidity observations — IQR outlier flags + Secondary-measure weighted mean: IQR outlier flags + Secondary-measure weighted mean for supplied humidity observations records (humidity_percent, observation_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-weather-04-177?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","humidity_percent","observation_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"station_group":{"type":"string","default":"","maxLength":80},"humidity_percent":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observation_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","station_group":"group-a","humidity_percent":10,"observation_count":1},{"date":"2026-10-02","row_id":"row-2","station_group":"group-b","humidity_percent":20,"observation_count":2},{"date":"2026-10-03","row_id":"row-3","station_group":"group-a","humidity_percent":15,"observation_count":3},{"date":"2026-10-04","row_id":"row-4","station_group":"group-b","humidity_percent":30,"observation_count":4}],"maxItems":200,"minItems":1},"field":{"enum":["humidity_percent","observation_count"],"type":"string","default":"humidity_percent"}}},"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_nwdmLYs4FdyDtgdFLrWJW","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":"Analyzes up to 200 humidity observation records to produce IQR-based outlier flags and a secondary-measure weighted mean report.","exampleAgentPrompt":"Run IQR outlier detection and an observation-count weighted mean on these humidity records — I have up to 50 rows with fields humidity_percent and observation_count across station groups, and I need both reports in one call.","exampleUseCases":[{"title":"Weather station outlier audit","prompt":"I have daily humidity readings from 3 station groups over the past month — about 90 rows with humidity_percent and observation_count. Flag any IQR outliers and give me a weighted mean using observation_count as the weight."},{"title":"Environmental data quality check","prompt":"Before I publish this humidity dataset, can you run IQR outlier flags on the humidity_percent column and compute a secondary-measure weighted mean? I'll paste the rows — there are around 120 of them with station_group and date fields."},{"title":"Multi-group humidity summary","prompt":"I'm comparing humidity observations across two station groups from October. Can you analyze my 40 rows of data, flag any outliers using the IQR method, and compute an observation-count weighted average of humidity_percent?"}],"resultDescription":"Returns two analytical reports for the submitted humidity observation rows: (1) IQR outlier flags indicating which rows fall outside the interquartile range for the selected field, and (2) a secondary-measure weighted mean computed using the companion numeric field as weights. Both reports are generated locally from the supplied data with no external lookups.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, date, humidity_percent, observation_count) causes rejection","Invalid date format (not YYYY-MM-DD) fails schema validation","Null values in both numeric fields may produce undefined weighted mean","Empty rows array is rejected by minItems constraint"],"whenToPreferThis":"Choose this endpoint when you have a batch of humidity observation records (up to 200 rows) and need both IQR-based outlier detection and an observation-count weighted mean in a single low-cost call. It is best suited for offline/local analysis of already-collected weather station data rather than real-time or live sensor lookups. Prefer this over general-purpose analytics services when you specifically need these two statistical outputs bundled together at minimal cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:41:54.863Z","isFirstParty":false,"canonicalSlug":"humidity-observations-iqr-outlier-flags-and-secondary-measure-e2917c91"}