{"uid":"cap_ORfRGH7R60TsDlZAt4-Yu","slug":"river-level-observations-string-normalisation-two-measure-correlation-b3db5eb8","name":"River Level Observations — String Normalisation + Two-Measure Correlation","description":"River level observations — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation 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-07-033?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}}},"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_BOshrmAXB7uRjllxSKiom","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 correlation between river level (level_m) and flow (flow_m3s) measurements across up to 200 supplied observation rows.","exampleAgentPrompt":"I have 150 rows of river observation records with station_group labels, dates, river levels in metres, and flow rates in cubic metres per second — can you normalise the station group strings and run a correlation analysis between the level and flow measurements?","exampleUseCases":[{"title":"Flood monitoring data quality check","prompt":"I've collected 80 daily river level and flow readings from our gauging stations over the past three months — the station names are inconsistently formatted. Can you normalise the station group labels and tell me how correlated the water level is with the flow rate across those records?"},{"title":"Catchment hydrology research summary","prompt":"I have a CSV of 200 river observation rows with station group names, dates, level_m, and flow_m3s values for our catchment study. Please clean up the station group strings and compute the correlation between river level and flow for us."},{"title":"Environmental compliance data preparation","prompt":"Before submitting our river monitoring data to the regulator, I need the station group names standardised and a statistical correlation report between the level and flow columns — I have 120 rows covering the last quarter."}],"resultDescription":"Returns two analytical reports: (1) normalised station group strings for each input row, and (2) a correlation analysis between the level_m and flow_m3s measures across the supplied dataset, computed entirely from the provided data with no external lookups or predictions.","failureModes":["Exceeds 200-row limit — request will be rejected; split into smaller batches","Missing required fields (row_id, station_group, date, level_m, flow_m3s) — validation error returned","Malformed date format (must be YYYY-MM-DD) — schema validation failure","All level_m or flow_m3s values are null — correlation cannot be computed","row_id values not unique — may cause ambiguous output rows"],"whenToPreferThis":"Choose this endpoint when you have tabular river observation data (up to 200 rows) and need both string normalisation of station group labels and a statistical correlation between level and flow in a single call. It is a self-contained, offline analytical operation — ideal when you do not need real-time gauge lookups, external data enrichment, or predictive modelling, and want a low-cost ($0.01 USDC) reproducible computation on your own supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T06:42:01.856Z","isFirstParty":false,"canonicalSlug":"river-level-observations-string-normalisation-two-measure-correlation-b3db5eb8"}