{"uid":"cap_W8tnA4x6415iGHlizEORT","slug":"pressure-observations-numeric-distribution-trailing-mean-series-1a7e85fd","name":"Pressure Observations — Numeric Distribution + Trailing Mean Series","description":"Pressure observations — Numeric distribution + Trailing mean series: Numeric distribution + Trailing mean series for supplied pressure observations records (pressure_hpa, elevation_m). 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-05-076?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","pressure_hpa","elevation_m"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"elevation_m":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"pressure_hpa":{"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","elevation_m":1,"pressure_hpa":10,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","elevation_m":2,"pressure_hpa":20,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","elevation_m":3,"pressure_hpa":15,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","elevation_m":4,"pressure_hpa":30,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["pressure_hpa","elevation_m"],"type":"string","default":"pressure_hpa"},"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_d-k633eXhP1b9oQNe5IZW","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 a numeric distribution and trailing mean time series for user-supplied atmospheric pressure and elevation observation records.","exampleAgentPrompt":"I have pressure readings from my weather stations — can you run a numeric distribution and a trailing mean series on the pressure_hpa field using a rolling window of 5, across these 12 rows of station data including dates and elevation_m values?","exampleUseCases":[{"title":"Weather station pressure trend analysis","prompt":"I collected barometric pressure readings from three station groups over the past month — can you compute a numeric distribution and trailing mean (window of 7) on the pressure_hpa field for these 90 rows of data?"},{"title":"Elevation-pressure correlation summary","prompt":"Can you run a numeric distribution and trailing mean series on the elevation_m field for these 50 weather observation records so I can see how elevation values are spread and trending over time? Use a window of 4."},{"title":"Quality check on sensor pressure logs","prompt":"I have 150 rows of pressure sensor data with station groups, dates, and pressure_hpa readings — please generate a numeric distribution and a rolling mean series with window size 10 so I can spot any anomalies."}],"resultDescription":"Returns two analytical reports for the supplied dataset: (1) a numeric distribution showing the spread and frequency of values for the chosen field (pressure_hpa or elevation_m), and (2) a trailing mean series showing the rolling average over the specified window size. Both reports are computed locally on the submitted data (up to 200 rows) with no external data lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, station_group, date, pressure_hpa, elevation_m) causes a schema rejection","Invalid date format (not YYYY-MM-DD) triggers a pattern validation error","Window size outside range 2–200 is rejected","Null numeric values may affect distribution and trailing mean accuracy","Empty rows array is rejected (minItems: 1)"],"whenToPreferThis":"Choose this endpoint when you have your own pressure or elevation observation records (up to 200 rows) and need fast, self-contained statistical analysis — specifically a numeric distribution and a trailing mean time series — without any live data fetching, external API lookups, or forecasting. Ideal for post-hoc analysis of weather station logs, sensor exports, or manually collected barometric data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T06:41:43.706Z","isFirstParty":false,"canonicalSlug":"pressure-observations-numeric-distribution-trailing-mean-series-1a7e85fd"}