{"uid":"cap_ztrnPn5KNdtlQtRnSHCBv","slug":"river-level-observations-string-normalisation-secondary-measure-90e7e7fc","name":"River Level Observations — String Normalisation + Secondary-Measure Weighted Mean","description":"River level observations — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied river level observations records (level_m, flow_m3s). 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-07-034?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","level_m","flow_m3s"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"level_m":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"flow_m3s":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","level_m":10,"flow_m3s":1,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","level_m":20,"flow_m3s":2,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","level_m":15,"flow_m3s":3,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","level_m":30,"flow_m3s":4,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["level_m","flow_m3s"],"type":"string","default":"level_m"}}},"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_b4ocsmHXHGqVEC7SBrkxk","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 station group strings and computes a flow-weighted mean for supplied river level observation records (level_m, flow_m3s) across up to 200 rows.","exampleAgentPrompt":"I have 150 rows of river monitoring data with station groups like 'Group A', 'group-a', 'GROUP A' and readings for level_m and flow_m3s — can you normalise those station group strings and compute a flow-weighted mean of the level_m values across all rows?","exampleUseCases":[{"title":"Flood monitoring station data cleanup","prompt":"I've got 80 rows of river gauge readings from multiple stations — the station names are inconsistent (e.g. 'north-gauge', 'North Gauge', 'NORTH GAUGE') and I need them normalised, plus a flow-weighted mean of level_m across all stations."},{"title":"Catchment hydrology reporting","prompt":"Run string normalisation on the station_group field and compute a secondary-measure weighted mean for flow_m3s across these 120 river observation records I'm uploading — I need both reports for a catchment summary."},{"title":"Environmental compliance data prep","prompt":"Before I submit this river monitoring dataset to our regulator, can you clean up the station group labels and give me a weighted mean of river levels weighted by flow for these 200 observation rows?"}],"resultDescription":"Two analytical reports: (1) normalised versions of the station_group strings across all supplied rows, and (2) a secondary-measure weighted mean of the selected field (level_m or flow_m3s) using the other measure as the weight, covering up to 200 input rows. No external lookups or live data are performed.","failureModes":["Rows exceeding 200 items will be rejected (maxItems constraint)","Missing required fields (row_id, station_group, date, level_m, flow_m3s) will cause validation errors","Invalid date format (non-YYYY-MM-DD) will fail schema validation","Null values in both level_m and flow_m3s simultaneously may produce undefined weighted mean","Payment not included or insufficient USDC will result in 402 response"],"whenToPreferThis":"Choose this endpoint when you have tabular river observation data (level and flow readings) that needs both string normalisation of categorical station labels and a statistically weighted aggregate in a single call. It is purpose-built for hydrology datasets up to 200 rows and bundles two analytical reports for $0.01 USDC, making it efficient for batch preprocessing before reporting or regulatory submission. Not suitable when you need live river data retrieval, forecasting, or more than 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:39:17.093Z","isFirstParty":false,"canonicalSlug":"river-level-observations-string-normalisation-secondary-measure-90e7e7fc"}