{"uid":"cap_N2L55P48td7ZOCx-FWyYQ","slug":"label-review-analytics-category-frequencies-date-by-category-pivot-8d1d7cf4","name":"Label Review Analytics: Category Frequencies + Date by Category Pivot","description":"Label review — Category frequencies + Date by category pivot: Category frequencies + 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-12-110?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_Pego-onBImq7ObmDAa2gb","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":"Computes category frequency counts and a date-by-category pivot table for label review records (reviewed_records, changed_labels) on up to 200 supplied rows — two independent analytical reports in one call.","exampleAgentPrompt":"Can you run a category frequency analysis and date-by-category pivot on my label review data? I have rows with dataset_group, date, reviewed_records, and changed_labels — up to 50 rows — and I want to analyze the reviewed_records field.","exampleUseCases":[{"title":"ML annotation QA category breakdown","prompt":"I have label review records from our annotation pipeline — each row has a date, a dataset group like 'group-a' or 'group-b', and counts of reviewed_records and changed_labels. Can you give me a frequency table of how often each category appears and a pivot of reviewed_records by date and category?"},{"title":"Daily label change tracking per team","prompt":"Our QA team reviews datasets daily. I have about 80 rows of review logs with dates, group names, and changed_labels counts. Run the category frequency and date-by-category pivot reports on changed_labels so I can see which groups are changing the most labels each day."},{"title":"Audit of multi-group review coverage","prompt":"I need to audit our label review coverage across dataset groups. Here are 120 rows with row IDs, dates, dataset groups, and reviewed_records counts — can you generate the category frequency breakdown and the date-by-category pivot for reviewed_records?"}],"resultDescription":"Two separate analytical reports: (1) a category frequency table showing how often each dataset_group appears in the supplied rows, and (2) a date-by-category pivot table cross-tabulating the selected metric (reviewed_records or changed_labels) by date and dataset_group — both computed locally on the supplied data, no external lookups.","failureModes":["Submitting more than 200 rows returns an error or truncated results","Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) cause validation failure","Malformed date strings not matching YYYY-MM-DD pattern are rejected","Null values in numeric fields may affect aggregation accuracy","Invalid field selector (not 'reviewed_records' or 'changed_labels') causes an error","Empty rows array (minItems:1 not met) returns a validation error"],"whenToPreferThis":"Choose this endpoint when you have label review or annotation QA data with category/group labels and want both a frequency distribution of categories and a date-by-category pivot in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where you want local, deterministic computation without any live data fetch or external model inference. Prefer this over general BI tools when you need a quick, structured two-report summary of reviewed_records or changed_labels across dataset groups.","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-category-frequencies-date-by-category-pivot-8d1d7cf4"}