{"uid":"cap_Ys_VgNaYhqXjqjHWHA2ZZ","slug":"data-ingestion-batches-date-category-pivot-missing-value-fill-ce47edf7","name":"Data Ingestion Batches — Date×Category Pivot + Missing-Value Fill","description":"Data ingestion batches — Date by category pivot + Explicit missing-value fill: Date by category pivot + 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-01-189?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"}}},"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_Zz7PXsKUF0f90hCjHJvuy","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":"Pivots ingestion batch records (received_rows, accepted_rows) by date and dataset_group, then fills missing values using zero, mean, or median imputation — returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have ingestion batch records with received_rows and accepted_rows across dataset groups like 'group-a' and 'group-b' for dates in October 2026 — can you pivot them by date and category, and fill any missing accepted_rows values using median imputation? Here are up to 50 rows of data.","exampleUseCases":[{"title":"ETL pipeline acceptance rate analysis","prompt":"I've got daily ingestion batch stats for three dataset groups across the past month — dates, received_rows, and accepted_rows per group. Can you pivot them into a date-by-group table and fill any missing accepted_rows with the median so I can see acceptance patterns over time?"},{"title":"Data quality gap detection in ingestion logs","prompt":"My ingestion logs have some null values in received_rows for certain dates and groups. Can you reshape these records into a date-by-category pivot and use zero-fill on the missing received_rows so I can identify which pipeline categories had gaps?"},{"title":"Batch monitoring dashboard data prep","prompt":"I need to prep my ingestion batch data for a dashboard — about 120 rows covering different dataset groups and dates. Can you pivot the accepted_rows field by date and dataset_group, filling any blanks with the mean, so the table is complete and ready to visualize?"}],"resultDescription":"Returns two analytical reports: (1) a date-by-category pivot table for the selected field (received_rows or accepted_rows), and (2) the same dataset with missing values explicitly filled using the chosen method (zero, mean, or median). Both reports are computed locally from the supplied rows with no external lookups.","failureModes":["Fewer than 1 row or more than 200 rows submitted — request rejected","Invalid date format (not YYYY-MM-DD) causes schema validation error","Missing required fields (row_id, dataset_group, date) cause per-row rejection","Numeric values outside ±1,000,000,000,000 range are rejected","Invalid enum for field (must be 'received_rows' or 'accepted_rows') or method (must be 'zero', 'mean', 'median') returns validation error","Payment of 0.01 USDC not attached causes 402 response"],"whenToPreferThis":"Choose this endpoint when you have tabular ingestion batch records with received_rows and accepted_rows and need both a date×category pivot and missing-value imputation in a single $0.01 call. It is ideal for data engineers who want quick local reshaping and gap-filling of ETL metrics without sending data to an external analytics platform. Prefer it over general-purpose BI tools when you need a lightweight, pay-per-call operation on up to 200 rows with no infrastructure setup.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T00:47:27.694Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-date-category-pivot-missing-value-fill-ce47edf7"}