{"uid":"cap_gKt2I5kd1kplcNakEGeCt","slug":"label-review-analytics-numeric-interval-filter-date-by-category-pivot-0889c2b1","name":"Label Review Analytics: Numeric Interval Filter + Date-by-Category Pivot","description":"Label review — Numeric interval filter + Date by category pivot: Numeric interval filter + Date by category pivot for supplied label review records (reviewed_records, changed_labels). 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-12-133?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","reviewed_records","changed_labels"],"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},"changed_labels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"reviewed_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","changed_labels":1,"reviewed_records":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","changed_labels":2,"reviewed_records":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","changed_labels":3,"reviewed_records":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","changed_labels":4,"reviewed_records":30}],"maxItems":200,"minItems":1},"field":{"enum":["reviewed_records","changed_labels"],"type":"string","default":"reviewed_records"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_tt8O3DmqIsAuMAOaRukW6","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 analytical reports on label review data: filters rows by a numeric interval on a chosen field, and pivots dates by dataset category for reviewed_records or changed_labels.","exampleAgentPrompt":"I have label review records with reviewed_records and changed_labels — can you filter the rows where reviewed_records is between 5 and 50, and also give me a pivot of dates broken down by dataset_group? Here are my rows: row-1 on 2026-10-01 in group-a with 10 reviewed and 1 changed, row-2 on 2026-10-02 in group-b with 20 reviewed and 2 changed.","exampleUseCases":[{"title":"QA audit of annotation batch volumes","prompt":"I want to audit our annotation batches — filter all label review rows where reviewed_records is between 10 and 100, and also pivot the dates by dataset_group so I can see when each group was active. Here's my data: row-1, 2026-10-01, group-a, 15 reviewed, 2 changed; row-2, 2026-10-02, group-b, 80 reviewed, 5 changed; row-3, 2026-10-03, group-a, 5 reviewed, 0 changed."},{"title":"Detecting high label change rate sessions","prompt":"Can you run two reports on my label review data? First, filter rows where changed_labels is between 3 and 20, and second, give me a date-by-category pivot using the changed_labels field. My rows: row-1 on 2026-11-01 in group-alpha with 8 changed and 50 reviewed, row-2 on 2026-11-02 in group-beta with 1 changed and 30 reviewed, row-3 on 2026-11-03 in group-alpha with 15 changed and 45 reviewed."},{"title":"Monthly label review summary by team","prompt":"I have up to 200 label review entries across two teams and I need a numeric interval filter on reviewed_records between 0 and 25, plus a date pivot grouped by dataset_group. Teams are 'team-nlp' and 'team-cv', dates range from 2026-09-01 to 2026-09-30 — can you process all these rows and give me both reports?"}],"resultDescription":"Returns two independent analytical reports: (1) a numeric interval filter listing rows where the chosen field (reviewed_records or changed_labels) falls within the specified minimum and maximum bounds, and (2) a date-by-category pivot table aggregating the chosen metric across dates broken down by dataset_group. Both reports are derived purely from the supplied input rows with no external data lookup.","failureModes":["More than 200 rows submitted — exceeds the per-call row limit","Missing required fields (row_id, date, dataset_group) in one or more rows","Date format not matching YYYY-MM-DD pattern causing validation failure","Numeric values outside the allowed range (-1e12 to 1e12) causing schema rejection","Invalid field enum value (must be 'reviewed_records' or 'changed_labels')","Payment not processed or insufficient USDC balance causing 402 rejection"],"whenToPreferThis":"Choose this endpoint when you have label review or data annotation records (with reviewed_records and changed_labels metrics) and need both a numeric range filter and a date-by-category pivot in a single low-cost call. It is ideal for ML data quality audits, annotation pipeline monitoring, and batch QA reporting where up to 200 rows are available locally and no live data lookup or prediction is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:20.409Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-numeric-interval-filter-date-by-category-pivot-0889c2b1"}