{"uid":"cap_e0RXHdi9H7Pjc1jgNkCDt","slug":"elevation-samples-trailing-mean-series-explicit-missing-value-fill-2c936566","name":"Elevation Samples — Trailing Mean Series + Explicit Missing-Value Fill","description":"Elevation samples — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied elevation samples records (elevation_m, sample_weight). 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-13-154?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","elevation_m","sample_weight"],"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},"sample_weight":{"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":10,"sample_weight":1,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","elevation_m":20,"sample_weight":2,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","elevation_m":15,"sample_weight":3,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","elevation_m":30,"sample_weight":4,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["elevation_m","sample_weight"],"type":"string","default":"elevation_m"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"},"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_l7W9Vpv0-haMRceXBuYH5","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 trailing moving average series and fills missing values in elevation sample data (elevation_m, sample_weight) for up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"I have 50 elevation sample records with elevation_m and sample_weight fields grouped by station; can you compute a trailing mean series using a window of 5 and fill any missing elevation_m values using the median method?","exampleUseCases":[{"title":"Smoothing sensor elevation readings","prompt":"I've got a batch of 120 elevation readings from different station groups with some nulls in elevation_m — can you run a trailing mean with a window of 10 and fill the missing values using the mean method?"},{"title":"Quality-checking weighted elevation samples","prompt":"Can you process my 80 elevation sample rows and compute a rolling average over sample_weight with window size 3, filling any missing sample_weight values with zero?"},{"title":"Trend analysis on daily elevation data","prompt":"I have daily elevation observations across two station groups for the past quarter — about 90 rows — please compute a trailing mean series with window 7 on elevation_m and use median fill for any gaps."}],"resultDescription":"Returns two analytical reports: (1) a trailing mean series showing the rolling average of the selected field (elevation_m or sample_weight) over the specified window, and (2) an explicit missing-value fill report showing imputed values using the chosen method (zero, mean, or median). Both reports are derived entirely from the supplied input rows with no external data lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Invalid date format (non-YYYY-MM-DD strings) cause validation errors","Window size outside 2–200 range causes schema validation failure","Missing required fields (row_id, station_group, date) cause row-level errors","All values null in a column may cause mean/median fill to return null","Invalid method or field enum values cause bad request errors"],"whenToPreferThis":"Choose this endpoint when you have tabular elevation sample data (up to 200 rows) and need both a trailing moving average series and missing-value imputation in a single call. It is ideal for offline/batch analytical work on pre-collected elevation or sensor data where no live geospatial lookup, prediction, or external data enrichment is required. Prefer it over general-purpose data APIs when you specifically need two bundled reports — smoothed trend series plus null-fill — on elevation_m or sample_weight fields.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:50:01.607Z","isFirstParty":false,"canonicalSlug":"elevation-samples-trailing-mean-series-explicit-missing-value-fill-2c936566"}