{"uid":"cap_VCX4iH6Eg_-W2cyCgmaEo","slug":"data-ingestion-batches-string-normalisation-date-by-category-pivot-302674ac","name":"Data Ingestion Batches — String Normalisation + Date-by-Category Pivot","description":"Data ingestion batches — String normalisation + Date by category pivot: String normalisation + Date by category pivot 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-01-035?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"}}},"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_J_BbJwcZZqKmlPvPoAtat","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":"Runs string normalisation and a date-by-category pivot analysis on up to 200 rows of data ingestion batch records (received_rows, accepted_rows), returning two local analytical reports.","exampleAgentPrompt":"Can you run string normalisation and a date-by-category pivot on my ingestion batch data? I have rows with dataset_group, date, received_rows, and accepted_rows — I want the pivot done on the received_rows field.","exampleUseCases":[{"title":"Daily ingestion pipeline quality check","prompt":"I have 50 rows of ingestion batch logs with dataset_group, date, received_rows, and accepted_rows. Can you normalise the string fields and give me a date-by-category pivot on accepted_rows so I can see which groups are underperforming by day?"},{"title":"Multi-group ETL acceptance rate breakdown","prompt":"We run ETL jobs across three dataset groups every day. Can you take these ingestion batch records and pivot the received_rows by date and group, plus normalise the string labels? I want two clean reports to share with the data team."},{"title":"Spot-checking batch ingestion anomalies","prompt":"I want to spot-check our ingestion batches from last month — here are the rows with row_id, date, dataset_group, received_rows, and accepted_rows. Please run string normalisation and a date-by-category pivot on received_rows so I can see where the numbers look off."}],"resultDescription":"Two analytical reports: (1) a string normalisation report showing cleaned/standardised string fields across the submitted rows, and (2) a date-by-category pivot table cross-referencing the selected numeric field (received_rows or accepted_rows) by date and dataset_group. No external lookups or predictions are included — all analysis is local and deterministic.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, date, dataset_group, received_rows, accepted_rows) causes row rejection","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array returns an error","Invalid field enum value (not 'received_rows' or 'accepted_rows') causes rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of data ingestion batch records and need both string normalisation and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal for ETL pipeline QA, ingestion acceptance rate analysis, and batch data audits where no live external lookup or prediction is required — everything runs locally and deterministically.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:45.786Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-string-normalisation-date-by-category-pivot-302674ac"}