{"uid":"cap_FcGFMaDfLzzr0voNBOHb2","slug":"transformation-throughput-analytics-daily-sum-series-missing-value-fill-8c8f7488","name":"Transformation Throughput Analytics — Daily Sum Series & Missing-Value Fill","description":"Transformation throughput — Daily sum series + Explicit missing-value fill: Daily sum series + Explicit missing-value fill for supplied transformation throughput records (processed_rows, duration_seconds). 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-13-145?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","processed_rows","duration_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duration_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","processed_rows":10,"duration_seconds":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","processed_rows":20,"duration_seconds":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","processed_rows":15,"duration_seconds":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","processed_rows":30,"duration_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["processed_rows","duration_seconds"],"type":"string","default":"processed_rows"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_gVf5KQpWobaYBhihARNt-","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 daily sum time series and fills missing values for transformation throughput records (processed_rows, duration_seconds) across up to 200 rows.","exampleAgentPrompt":"Can you run a daily sum series on my transformation throughput records and fill any missing processed_rows values using median imputation? I have about 50 rows with dates and dataset groups ready to send.","exampleUseCases":[{"title":"ETL pipeline daily throughput report","prompt":"I have 120 rows of ETL job records with dates, dataset groups, and processed_rows counts — can you aggregate them into a daily sum series and fill any missing processed_rows values using median so I can see total daily throughput?"},{"title":"Data pipeline duration gap filling","prompt":"My pipeline logs have some missing duration_seconds entries across about 80 records spanning several dates. Can you compute the daily sum of duration_seconds and fill the gaps with zero so I get a clean time series?"},{"title":"Multi-group transformation analytics","prompt":"I've got transformation throughput data across two dataset groups over the past month, around 150 rows. Can you give me a daily sum series for processed_rows and fill any nulls with the mean value?"}],"resultDescription":"Returns two analytical reports: (1) a daily sum series aggregating the selected field (processed_rows or duration_seconds) by date, and (2) an explicit missing-value fill report where nulls in the selected field are imputed using the chosen method (zero, mean, or median). Results are derived entirely from the supplied data with no external lookups.","failureModes":["Input exceeds 200 rows — request rejected","Missing required fields (row_id, date, processed_rows, duration_seconds) — validation error","Invalid date format (must be YYYY-MM-DD) — schema rejection","field enum value not recognized — validation error","method enum value not recognized — validation error","All values null for selected field — fill report may be uninformative"],"whenToPreferThis":"Choose this endpoint when you need both a daily sum aggregation and missing-value imputation on transformation throughput data (processed_rows or duration_seconds) in a single call, for datasets up to 200 rows. It is ideal for lightweight, self-contained ETL analytics where no external data sources or predictions are needed — just local computation on supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:58.541Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-analytics-daily-sum-series-missing-value-fill-8c8f7488"}