{"uid":"cap_weA5zIWiC7-02Bv82Y2mG","slug":"road-segment-observations-string-normalisation-trailing-mean-series-03ad0410","name":"Road Segment Observations — String Normalisation + Trailing Mean Series","description":"Road segment observations — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied road segment observations records (length_m, travel_seconds). 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-15-028?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","length_m","travel_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"length_m":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80},"travel_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","length_m":10,"station_group":"group-a","travel_seconds":1},{"date":"2026-10-02","row_id":"row-2","length_m":20,"station_group":"group-b","travel_seconds":2},{"date":"2026-10-03","row_id":"row-3","length_m":15,"station_group":"group-a","travel_seconds":3},{"date":"2026-10-04","row_id":"row-4","length_m":30,"station_group":"group-b","travel_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["length_m","travel_seconds"],"type":"string","default":"length_m"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_OR860FVN7fWCB3I3GBUF7","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":"Applies string normalisation and computes a trailing mean series on supplied road segment observation records (length_m, travel_seconds), returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have a list of road segment observations with length_m and travel_seconds across several station groups — can you normalise the station group strings and compute a trailing mean over a window of 3 for the travel_seconds field? Here are my rows: [{\"row_id\":\"r1\",\"station_group\":\"Group A\",\"date\":\"2024-03-01\",\"length_m\":500,\"travel_seconds\":45},{\"row_id\":\"r2\",\"station_group\":\"group-a\",\"date\":\"2024-03-02\",\"length_m\":500,\"travel_seconds\":50},{\"row_id\":\"r3\",\"station_group\":\"Group B\",\"date\":\"2024-03-03\",\"length_m\":800,\"travel_seconds\":60}].","exampleUseCases":[{"title":"Traffic monitoring data cleanup","prompt":"I've got 80 rows of daily road segment readings from different stations — the station group names are messy (mixed case, hyphens vs spaces) and I want them normalised, plus a trailing mean with window size 5 over length_m to smooth out noise. Can you run both reports at once?"},{"title":"Travel time smoothing for commute analysis","prompt":"Here are 150 road segment observations from our city sensors — I need you to normalise the station_group strings and calculate a trailing mean series with a window of 4 for travel_seconds so I can see smoothed commute trends over time."},{"title":"Quality check before dashboard ingestion","prompt":"Before I load this road segment dataset into our dashboard, can you clean up the station group labels with string normalisation and also give me a trailing mean for length_m with a window of 2? I have about 60 rows."}],"resultDescription":"Returns two analytical reports: (1) a string normalisation report on the station_group field across all supplied rows, and (2) a trailing mean series computed over the specified numeric field (length_m or travel_seconds) using the given window size. Results are derived purely from the supplied data with no external lookups or predictions.","failureModes":["Fewer than 1 row supplied — validation error","More than 200 rows supplied — rejected with row limit error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Window size larger than number of rows — may produce sparse or empty trailing mean results","Null numeric values in the target field — may reduce trailing mean coverage","Invalid field enum value (not 'length_m' or 'travel_seconds') — schema rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 road segment observation records and need both string normalisation of categorical string fields and a trailing (rolling) mean series on a numeric measurement in a single call. It is cost-effective at $0.01 USDC for both reports simultaneously and operates entirely on supplied data with no external dependencies, making it suitable for offline analytics pipelines, data preparation workflows, or pre-ingestion quality checks on road monitoring datasets.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:11:23.740Z","isFirstParty":false,"canonicalSlug":"road-segment-observations-string-normalisation-trailing-mean-series-03ad0410"}