{"uid":"cap_P1kC16ro5RCLrKgDyh5GM","slug":"data-ingestion-batches-trailing-mean-series-explicit-missing-value-fill-7a125fcc","name":"Data Ingestion Batches — Trailing Mean Series + Explicit Missing-Value Fill","description":"Data ingestion batches — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied data ingestion batches records (received_rows, accepted_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-01-154?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","received_rows","accepted_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"accepted_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"received_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","accepted_rows":1,"dataset_group":"group-a","received_rows":10},{"date":"2026-10-02","row_id":"row-2","accepted_rows":2,"dataset_group":"group-b","received_rows":20},{"date":"2026-10-03","row_id":"row-3","accepted_rows":3,"dataset_group":"group-a","received_rows":15},{"date":"2026-10-04","row_id":"row-4","accepted_rows":4,"dataset_group":"group-b","received_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["received_rows","accepted_rows"],"type":"string","default":"received_rows"},"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_aj9SbsdHBYbeu-PN4-Xl0","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 time series and fills missing values in data ingestion batch records (received_rows, accepted_rows) for up to 200 rows, returning 2 analytical reports.","exampleAgentPrompt":"Can you run a trailing mean series with a window of 3 on the received_rows field for my ingestion batch records, filling any missing values using the mean method? Here's my data: row-1 on 2024-01-01 group-a got 100 received and 90 accepted, row-2 on 2024-01-02 group-a got null received and 85 accepted, row-3 on 2024-01-03 group-a got 110 received and 95 accepted.","exampleUseCases":[{"title":"Smoothing noisy ETL pipeline metrics","prompt":"I have daily ingestion batch records for three dataset groups over the past month and some days have null received_rows counts — can you fill those nulls using the median and then compute a trailing mean with a window of 7 so I can see the smoothed trend?"},{"title":"Monitoring accepted row rates over time","prompt":"Run a trailing mean series with window size 5 on the accepted_rows field for my ingestion batches and use zero-fill for any missing values — I want to see how my acceptance rate trends week over week across groups."},{"title":"Auditing data quality gaps in ingestion logs","prompt":"I've got up to 150 rows of ingestion batch logs with some missing accepted_rows values — fill the gaps using mean imputation and give me the trailing mean report with a window of 4 so I can spot which dataset groups are underperforming."}],"resultDescription":"Returns 2 analytical reports: (1) a trailing mean time series computed over the specified window for the chosen field (received_rows or accepted_rows), and (2) an explicit missing-value fill report showing imputed values using the chosen method (zero, mean, or median). All computed locally against the supplied rows, no external lookups.","failureModes":["Fewer than 1 or more than 200 rows supplied — request rejected","Invalid date format (must be YYYY-MM-DD) — validation error","Window size outside 2–200 range — rejected","Field value not 'received_rows' or 'accepted_rows' — enum validation error","Missing required row fields (row_id, dataset_group, date) — schema error","Numeric values outside ±1,000,000,000,000 range — rejected","Payment of 0.01 USDC not supplied — 402 payment required"],"whenToPreferThis":"Choose this endpoint when you need both a trailing/rolling mean time series AND missing-value imputation for data ingestion batch metrics (received_rows or accepted_rows) in a single paid call. It is purpose-built for ETL and pipeline monitoring use cases with structured daily batch records and delivers two reports at once. Prefer it over generic analytics tools when your data fits the ingestion batch schema and you want local analytical computation without external data lookups or prediction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T00:52:29.515Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-trailing-mean-series-explicit-missing-value-fill-7a125fcc"}