{"uid":"cap_1SV13Hr37DpYA_dB1OsZP","slug":"sampling-observations-trailing-mean-series-adjacent-row-changes-4ed83820","name":"Sampling Observations — Trailing Mean Series + Adjacent Row Changes","description":"Sampling observations — Trailing mean series + Adjacent row changes: Trailing mean series + Adjacent row changes 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-15-146?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"},"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_f06nlW4hR4DGyipyl1q9l","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 trailing moving-average series and adjacent row-to-row change analysis for up to 200 sampling observation records with sample_value and sample_weight fields.","exampleAgentPrompt":"I have 4 sampling observations — row-1 on 2026-10-01 with value 10 and weight 1 in group-a, row-2 on 2026-10-02 with value 20 and weight 2 in group-b, row-3 on 2026-10-03 with value 15 and weight 3 in group-a, row-4 on 2026-10-04 with value 30 and weight 4 in group-b — can you run both a trailing mean series and adjacent row changes on the sample_value field using a window of 2?","exampleUseCases":[{"title":"Environmental sensor trend smoothing","prompt":"I have daily air quality sensor readings for 60 days across two monitoring stations — can you compute a trailing mean series with a window of 7 and also show me the day-over-day changes in the sample_value field so I can spot anomalies?"},{"title":"Weekly survey response analysis","prompt":"I've got 120 weekly survey response records with scores and response weights — run a trailing mean series with a window size of 4 and adjacent row changes on sample_weight so I can see how engagement is shifting across consecutive weeks."},{"title":"Production batch quality control","prompt":"Here are 50 production batch samples with numeric quality scores and batch weights across two product groups — calculate both a rolling mean using a window of 3 and the row-to-row differences on sample_value so my QC team can track drift between consecutive batches."}],"resultDescription":"Returns two analytical reports for the supplied observation rows: (1) a trailing mean series showing rolling averages of the specified field over the given window, and (2) adjacent row changes showing the difference between consecutive row values — both computed locally without external lookups or predictions.","failureModes":["Fewer than 1 row supplied — minItems validation error","More than 200 rows supplied — maxItems exceeded error","Invalid date format not matching YYYY-MM-DD pattern — schema validation failure","Window size outside 2–200 range — schema validation error","sample_value or sample_weight outside ±1,000,000,000,000 range — validation error","Missing required fields (row_id, dataset_group, date) — required field error","Invalid field enum value (not sample_value or sample_weight) — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need both a trailing moving average AND adjacent row change analysis on sampling observation data in a single $0.01 call covering up to 200 rows. It is ideal for time-series or sequential measurement data with sample weights, and when you want two complementary analytical views (smoothing + delta) without making separate API calls. Prefer alternatives if you need only one of the two reports, require grouped summary statistics, need distribution histograms, or require real-time data fetching.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:46.200Z","isFirstParty":false,"canonicalSlug":"sampling-observations-trailing-mean-series-adjacent-row-changes-4ed83820"}