{"uid":"cap_Ht7a6g4pY69yxJ4yGjESW","slug":"label-review-analytics-daily-sum-series-date-by-category-pivot-f127f513","name":"Label Review Analytics — Daily Sum Series & Date-by-Category Pivot","description":"Label review — Daily sum series + Date by category pivot: Daily sum series + 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-12-143?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"}}},"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_iBl0S9NX6INjdsdqRtf_Z","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":"Generates two analytical reports from label review data: a daily sum time series and a date-by-category pivot table, for up to 200 rows of reviewed_records or changed_labels data.","exampleAgentPrompt":"Can you run a daily sum series and date-by-category pivot on my label review data? I have rows with dates, dataset groups like 'group-a' and 'group-b', and I want to analyze the reviewed_records field — here are up to 200 rows to process.","exampleUseCases":[{"title":"Daily label review throughput tracking","prompt":"I have label review logs with dates, dataset groups, and counts of reviewed records. Can you generate a daily sum series and a pivot by date and group so I can see how throughput varied across groups over the past two weeks? Use the reviewed_records field. Here's the data."},{"title":"Changed labels anomaly investigation","prompt":"I want to understand how changed_labels spiked on certain days across my dataset groups. Can you produce a daily sum series and a date-by-category pivot for my label review records so I can spot the anomaly? I'll provide up to 150 rows."},{"title":"ML pipeline labeling audit","prompt":"We're auditing our ML data labeling pipeline and need a summary of label changes over the last sprint. Can you compute daily totals and a category-date pivot for changed_labels across all our dataset groups from these review records?"}],"resultDescription":"Returns two independent analytical reports computed locally from the supplied data: (1) a daily sum time series showing aggregated values of the selected field (reviewed_records or changed_labels) per date, and (2) a date-by-category pivot table breaking down totals by date and dataset_group. No external data is fetched or predicted.","failureModes":["Input array empty or missing — minimum 1 row required","More than 200 rows submitted — maxItems limit exceeded","Invalid date format — must match YYYY-MM-DD pattern","Missing required fields (row_id, date, dataset_group) on any row","Numeric values out of allowed range (±1,000,000,000,000)","Invalid field enum value — must be 'reviewed_records' or 'changed_labels'","Payment failure — 0.01 USDC required per call"],"whenToPreferThis":"Choose this endpoint when you have label review tabular data (up to 200 rows) and need both a daily sum time series and a date-by-category pivot in a single low-cost call ($0.01 USDC). Ideal for ML data labeling pipelines, annotation quality audits, or any scenario where reviewed_records or changed_labels must be aggregated by day and group without external lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:34.008Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-daily-sum-series-date-by-category-pivot-f127f513"}