{"uid":"cap_MYB9ffMUnvd348e2YotdS","slug":"label-review-analytics-numeric-row-ordering-explicit-missing-value-fill-7534feb9","name":"Label Review Analytics — Numeric Row Ordering + Explicit Missing-Value Fill","description":"Label review — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill 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-12-124?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_o6Juao4Iy1D3sbPuHi_zn","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":"Sorts label review records by numeric row order and fills missing values in a chosen field using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Sort my label review records by numeric row order and fill any missing reviewed_records values using median imputation — I have 4 rows: row-1 group-a 2026-10-01 reviewed=10 changed=1, row-2 group-b 2026-10-02 reviewed=null changed=2, row-3 group-a 2026-10-03 reviewed=15 changed=3, row-4 group-b 2026-10-04 reviewed=30 changed=4. Give me both analytical reports.","exampleUseCases":[{"title":"Clean ML annotation batch before training","prompt":"I have a batch of label review records from last week and some reviewed_records values are missing — can you sort them by row number and fill those nulls using the mean so I can feed clean data into my training pipeline? Here are my rows: row-1 group-a 2026-11-01 reviewed=50 changed=3, row-2 group-b 2026-11-02 reviewed=null changed=5, row-3 group-a 2026-11-03 reviewed=40 changed=2."},{"title":"Audit changed_labels gaps across dataset groups","prompt":"Can you run numeric row ordering and zero-fill any missing changed_labels values across these label review records so I can audit which dataset groups had incomplete change tracking? Rows: row-1 group-x 2026-09-10 reviewed=100 changed=null, row-2 group-y 2026-09-11 reviewed=80 changed=7, row-3 group-x 2026-09-12 reviewed=null changed=null."},{"title":"Prepare labeling QA report with imputed data","prompt":"I need a QA report on our labeling session — please sort these rows numerically and use median to fill in any missing reviewed_records values: row-1 group-alpha 2026-12-01 reviewed=200 changed=10, row-2 group-beta 2026-12-02 reviewed=null changed=8, row-3 group-alpha 2026-12-03 reviewed=180 changed=null, row-4 group-beta 2026-12-04 reviewed=210 changed=12."}],"resultDescription":"Two analytical reports based on the supplied label review rows: the first covering numeric row ordering (rows sorted by their numeric row index), and the second covering explicit missing-value fill (nulls in the chosen field replaced using zero, mean, or median). No external data is fetched; all analysis is performed locally on the submitted rows.","failureModes":["More than 200 rows submitted — request rejected","Missing required fields (row_id, date, dataset_group) in any row — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Numeric field values outside allowed range (±1,000,000,000,000) — rejection","Invalid enum value for field or method parameters — schema error","Empty rows array — rejected due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you need both numeric row ordering and missing-value imputation applied together to label review data (reviewed_records or changed_labels) in a single $0.01 call that returns two reports. Prefer it over single-report endpoints when you specifically need to clean and sort annotation review records offline without any live lookups or external predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-03T06:41:14.828Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-numeric-row-ordering-explicit-missing-value-fill-7534feb9"}