{"uid":"cap_y8oH6RtE5-tJEIcFFQmUU","slug":"duplicate-observations-numeric-distribution-trailing-mean-series-76d47089","name":"Duplicate Observations — Numeric Distribution + Trailing Mean Series","description":"Duplicate observations — Numeric distribution + Trailing mean series: Numeric distribution + Trailing mean series for supplied duplicate observations records (duplicate_rows, total_rows). 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-04-076?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","duplicate_rows","total_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"duplicate_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_rows":1,"dataset_group":"group-a","duplicate_rows":10},{"date":"2026-10-02","row_id":"row-2","total_rows":2,"dataset_group":"group-b","duplicate_rows":20},{"date":"2026-10-03","row_id":"row-3","total_rows":3,"dataset_group":"group-a","duplicate_rows":15},{"date":"2026-10-04","row_id":"row-4","total_rows":4,"dataset_group":"group-b","duplicate_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["duplicate_rows","total_rows"],"type":"string","default":"duplicate_rows"},"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_Y-gEIYDsrvQf8HrpaCjtP","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 summary and a trailing mean time series for supplied duplicate_rows and total_rows observation records, locally, with no external lookups.","exampleAgentPrompt":"I have up to 200 records of duplicate observation data — each with a row_id, dataset_group, date, duplicate_rows count, and total_rows count — can you run both a numeric distribution summary and a trailing mean series (window of 7) on the duplicate_rows field for me?","exampleUseCases":[{"title":"Data quality audit across dataset groups","prompt":"I have 150 daily duplicate-row observations from my ETL pipeline across two groups — 'group-a' and 'group-b' — each with a date, duplicate_rows, and total_rows. Can you give me a numeric distribution and a 14-day trailing mean series on the duplicate_rows field so I can see where duplication is spiking?"},{"title":"Monitoring total row growth over time","prompt":"I want to track how total_rows have been trending across my dataset batches. I have 80 records with dates and total_rows counts. Can you compute the numeric distribution and a trailing mean series with a window of 5 for the total_rows field?"},{"title":"Validating deduplication improvement over sprints","prompt":"We ran deduplication sprints over the past quarter and I have 60 daily records showing duplicate_rows and total_rows per sprint cycle. Can you produce the numeric distribution and trailing mean (window of 3) on duplicate_rows so I can show the team whether the duplicate rate is genuinely improving?"}],"resultDescription":"Returns two independent analytical reports: (1) a numeric distribution summary (e.g. min, max, mean, median, percentiles, spread) for the selected field across all supplied rows, and (2) a trailing mean time series for that field using the specified rolling window — all computed locally from the supplied data, with no external data fetched.","failureModes":["Fewer than 1 row supplied — returns validation error","More than 200 rows supplied — exceeds maxItems limit, rejected","Invalid date format (not YYYY-MM-DD) — schema validation failure","Window size outside 2–200 range — rejected by schema","Field value not 'duplicate_rows' or 'total_rows' — enum validation failure","Null values in numeric fields may affect distribution calculations","Missing required properties (row_id, dataset_group, date) — schema rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 records of duplicate-observation data (with duplicate_rows and total_rows per date and dataset group) and need both a numeric distribution summary and a trailing mean time series in a single low-cost call ($0.01 USDC), with no external lookups, predictions, or live data required. Prefer it over general-purpose analytics tools when you want a bundled two-report output computed entirely from your supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T07:19:41.100Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-numeric-distribution-trailing-mean-series-76d47089"}