{"uid":"cap_sRYG4lMJI22np4H6iG5cV","slug":"dataset-partition-sizes-daily-sum-series-explicit-missing-value-fill-1dc9cb16","name":"Dataset Partition Sizes — Daily Sum Series + Explicit Missing-Value Fill","description":"Dataset partition sizes — Daily sum series + Explicit missing-value fill: Daily sum series + Explicit missing-value fill for supplied dataset partition sizes records (row_count, file_mb). 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-07-145?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","row_count","file_mb"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"file_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","file_mb":1,"row_count":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","file_mb":2,"row_count":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","file_mb":3,"row_count":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","file_mb":4,"row_count":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["row_count","file_mb"],"type":"string","default":"row_count"},"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_n1sR1ckFEsF6wPqaKCTgx","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 daily sum time series and fills missing values for dataset partition size metrics (row_count or file_mb) across groups, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you compute the daily sum time series for row_count across these dataset partition records and fill any missing values using the median method? I have up to 50 rows covering October 2026 with groups like 'group-a' and 'group-b'.","exampleUseCases":[{"title":"Daily partition growth monitoring","prompt":"I have daily partition size records for my data lake with row counts and file sizes — can you compute the daily total row_count per day and fill any missing dates using median fill? Here are the records for the past 30 days across groups 'raw' and 'processed'."},{"title":"File size trend analysis with gap filling","prompt":"Can you run a daily sum series on the file_mb field for my dataset partitions and fill any missing values with zero? I'll give you about 120 rows across two dataset groups spanning September and October 2026."},{"title":"Data pipeline audit report generation","prompt":"I need two reports on my partition size data — a daily sum series and explicit missing-value fill — for the row_count metric, using mean imputation for gaps. The dataset has 80 rows across groups 'bronze', 'silver', and 'gold' from Q3 2026."}],"resultDescription":"Two independent analytical reports: (1) a daily sum time series aggregating the chosen metric (row_count or file_mb) by date across dataset groups, and (2) an explicit missing-value-filled version of the series using the specified fill method (zero, mean, or median). No external data fetched; analysis is performed on the supplied rows only.","failureModes":["Input array is empty or exceeds 200 rows — rejected with validation error","Invalid date format (not YYYY-MM-DD) in any row — schema validation failure","Unknown fill method or field enum value — rejected at schema level","All values for selected field are null — fill may produce degenerate or all-zero results","Missing required row fields (row_id, dataset_group, date) — schema validation error"],"whenToPreferThis":"Choose this endpoint when you need both a daily sum aggregation and missing-value imputation for dataset partition size metrics (row_count or file_mb) in a single low-cost call. It is ideal for data engineering and pipeline monitoring use cases where you supply your own records (no external lookup) and need two complementary analytical views — aggregated totals and gap-filled series — on time-series partition data of up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:40.485Z","isFirstParty":false,"canonicalSlug":"dataset-partition-sizes-daily-sum-series-explicit-missing-value-fill-1dc9cb16"}