{"uid":"cap_S-6c2DXTJ3gzBl-tGpCtr","slug":"duplicate-observations-analytics-numeric-row-ordering-date-by-5043dd14","name":"Duplicate Observations Analytics: Numeric Row Ordering + Date-by-Category Pivot","description":"Duplicate observations — Numeric row ordering + Date by category pivot: Numeric row ordering + Date by category pivot for supplied duplicate observations records (duplicate_rows, total_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-04-122?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","duplicate_rows","total_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"duplicate_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_rows":1,"dataset_group":"group-a","duplicate_rows":10},{"date":"2026-10-02","row_id":"row-2","total_rows":2,"dataset_group":"group-b","duplicate_rows":20},{"date":"2026-10-03","row_id":"row-3","total_rows":3,"dataset_group":"group-a","duplicate_rows":15},{"date":"2026-10-04","row_id":"row-4","total_rows":4,"dataset_group":"group-b","duplicate_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["duplicate_rows","total_rows"],"type":"string","default":"duplicate_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_OWVYcr6Sh1Ft1hGhWLEdv","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 two local analytical reports on duplicate-observation data: numeric row ordering and a date-by-category pivot, for up to 200 supplied rows.","exampleAgentPrompt":"Run two analytics reports on my duplicate observation data — numeric row ordering and a date-by-category pivot — for these 4 records: row-1 in group-a on 2026-10-01 with 10 duplicate_rows out of 1 total, row-2 in group-b on 2026-10-02 with 20 duplicates out of 2 total, row-3 in group-a on 2026-10-03 with 15 duplicates out of 3 total, and row-4 in group-b on 2026-10-04 with 30 duplicates out of 4 total; analyze the duplicate_rows field.","exampleUseCases":[{"title":"Data quality audit across dataset groups","prompt":"I have records from two dataset groups collected over several dates with duplicate and total row counts. Can you run numeric row ordering and a date-by-category pivot on them so I can see which groups accumulate the most duplicates over time? Here are the rows: row-1, group-a, 2025-01-01, 5 duplicate_rows, 100 total; row-2, group-b, 2025-01-01, 12 duplicates, 200 total; row-3, group-a, 2025-01-02, 8 duplicates, 110 total — analyze duplicate_rows."},{"title":"ETL pipeline duplication trend review","prompt":"After our nightly ETL runs I want to see a date-by-category pivot and numeric ordering for duplicate counts across pipeline stages. Rows are: etl-1, stage-ingest, 2025-03-10, 50 duplicate_rows, 500 total; etl-2, stage-transform, 2025-03-10, 20 duplicates, 480 total; etl-3, stage-ingest, 2025-03-11, 65 duplicates, 510 total; analyze the duplicate_rows field."},{"title":"Monthly deduplication effort summary","prompt":"Can you generate the numeric row ordering and date-by-category pivot for my monthly deduplication tracking data? Here are the entries: jan-1, region-north, 2025-01-15, 30 duplicate_rows, 300 total; jan-2, region-south, 2025-01-15, 45 duplicates, 400 total; jan-3, region-north, 2025-02-15, 20 duplicates, 310 total; jan-4, region-south, 2025-02-15, 55 duplicates, 420 total — use duplicate_rows as the analysis field."}],"resultDescription":"Returns two analytical reports computed locally from the submitted rows: (1) a numeric row ordering report ranking rows by the selected metric (duplicate_rows or total_rows), and (2) a date-by-category pivot table showing values broken down by date and dataset_group. No external data is fetched; all analysis is performed on the supplied records.","failureModes":["Fewer than 1 row submitted — minimum 1 row required","More than 200 rows submitted — exceeds maxItems limit","Invalid date format (must match YYYY-MM-DD pattern)","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows)","Invalid field selector (must be 'duplicate_rows' or 'total_rows')","Null numeric values may affect ordering and pivot calculations"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of duplicate-observation data with dataset group and date fields, and you need both a ranked numeric ordering and a date-by-category pivot in a single low-cost call. It is ideal for data quality audits, ETL monitoring, and deduplication summaries where no live data lookup or prediction is needed — just fast, local computation on your supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:39.885Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-analytics-numeric-row-ordering-date-by-5043dd14"}