{"uid":"cap_kiEtHfWF4lE_y_1JAzWoO","slug":"sampling-observations-trailing-mean-series-missing-value-fill-653c6c0b","name":"Sampling Observations Trailing Mean Series + Missing Value Fill","description":"Sampling observations — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied sampling observations records (sample_value, 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-analytics-15-154?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","sample_value","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},"sample_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"sample_weight":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","sample_value":10,"dataset_group":"group-a","sample_weight":1},{"date":"2026-10-02","row_id":"row-2","sample_value":20,"dataset_group":"group-b","sample_weight":2},{"date":"2026-10-03","row_id":"row-3","sample_value":15,"dataset_group":"group-a","sample_weight":3},{"date":"2026-10-04","row_id":"row-4","sample_value":30,"dataset_group":"group-b","sample_weight":4}],"maxItems":200,"minItems":1},"field":{"enum":["sample_value","sample_weight"],"type":"string","default":"sample_value"},"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_ZqO2bLOBhUJ7g7iB91pkF","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 mean series and fills missing values in sampling observation records (sample_value or sample_weight) for up to 200 rows.","exampleAgentPrompt":"I have 50 daily sampling observations with some missing sample_value entries — can you compute a trailing mean series with a window of 7 and fill the missing values using median imputation?","exampleUseCases":[{"title":"Smooth noisy sensor sampling data","prompt":"I have 120 rows of daily sensor sample readings with some nulls in the sample_value column — please compute a trailing mean series with a window of 5 and fill in the missing values using median."},{"title":"Impute missing survey weights before analysis","prompt":"My survey dataset has 80 rows and some sample_weight values are missing — run a trailing mean with window size 3 and fill the gaps using the mean method so I can proceed with weighted analysis."},{"title":"Zero-fill missing observations for reporting","prompt":"I need to prepare a clean time series from 60 sampling observation records for a report — can you apply a trailing mean window of 2 and zero-fill any missing sample_value entries?"}],"resultDescription":"Returns two analytical reports for the supplied rows: (1) a trailing mean series showing the rolling average over the specified window for the chosen field, and (2) a dataset with missing values explicitly filled using the selected method (zero, mean, or median). Results are computed locally with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Window size outside 2–200 range — rejected by schema","sample_value or sample_weight outside ±1,000,000,000,000 — rejected","Payment not received or insufficient USDC — 402 response","Missing required fields (row_id, dataset_group, date) — error returned"],"whenToPreferThis":"Choose this endpoint when you need both a trailing/rolling mean computation and explicit missing-value imputation on sampling observation data in a single paid call. It is best for small-to-medium datasets (up to 200 rows) with numeric sample_value or sample_weight fields and date-indexed records. Prefer this over general-purpose analytics when you need a combined smoothing + fill report without standing up your own infrastructure.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:03.564Z","isFirstParty":false,"canonicalSlug":"sampling-observations-trailing-mean-series-missing-value-fill-653c6c0b"}