{"uid":"cap_Q5V2V5F1GlNl3RPPp6waP","slug":"transcript-preparation-iqr-outlier-flags-explicit-missing-value-fill-74eeec6c","name":"Transcript Preparation — IQR Outlier Flags + Explicit Missing-Value Fill","description":"Transcript preparation — IQR outlier flags + Explicit missing-value fill: IQR outlier flags + Explicit missing-value fill for supplied transcript preparation records (transcribed_minutes, source_minutes). 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-writing-12-180?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","document_group","date","transcribed_minutes","source_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"document_group":{"type":"string","default":"","maxLength":80},"source_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"transcribed_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","document_group":"group-a","source_minutes":1,"transcribed_minutes":10},{"date":"2026-10-02","row_id":"row-2","document_group":"group-b","source_minutes":2,"transcribed_minutes":20},{"date":"2026-10-03","row_id":"row-3","document_group":"group-a","source_minutes":3,"transcribed_minutes":15},{"date":"2026-10-04","row_id":"row-4","document_group":"group-b","source_minutes":4,"transcribed_minutes":30}],"maxItems":200,"minItems":1},"field":{"enum":["transcribed_minutes","source_minutes"],"type":"string","default":"transcribed_minutes"},"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_KVXOtHNtKUt0ufFXygdk4","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":"Analyzes transcript preparation records (transcribed_minutes, source_minutes) to flag IQR-based outliers and fill missing values using a chosen method, producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you check my transcript preparation records for IQR outliers and fill any missing transcribed_minutes values using the median? Here are my rows: row-1 group-a 2026-10-01 transcribed=10 source=1, row-2 group-b 2026-10-02 transcribed=null source=2, row-3 group-a 2026-10-03 transcribed=15 source=3.","exampleUseCases":[{"title":"Outlier detection in transcription logs","prompt":"I have about 80 rows of transcription job records with transcribed_minutes and source_minutes — can you run IQR outlier flagging on the transcribed_minutes field and also fill any missing values using the mean? I want both reports back."},{"title":"Missing-value imputation for transcript dataset","prompt":"My transcript preparation dataset has some null source_minutes entries. Can you fill those missing values using zero imputation and also flag any IQR outliers in source_minutes across all 150 rows I'm sending?"},{"title":"Data quality audit before transcription pipeline","prompt":"Before I process these 200 transcript records, can you run IQR outlier detection and median fill for any missing transcribed_minutes values? I need to catch bad data in document group 'batch-nov' before it flows downstream."}],"resultDescription":"Returns two analytical reports per call: (1) an IQR outlier flags report identifying which rows contain statistical outliers in the specified field, and (2) an explicit missing-value fill report showing which null entries were filled and with what imputed value (zero, mean, or median). Both reports are computed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected","Missing required fields (row_id, date, transcribed_minutes, source_minutes) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Invalid method enum value (not zero/mean/median) — rejected","Invalid field enum value (not transcribed_minutes/source_minutes) — rejected","Empty rows array — rejected","Non-numeric values in numeric fields — schema error"],"whenToPreferThis":"Choose this endpoint when you need both IQR-based outlier detection and missing-value imputation on transcript preparation data (transcribed_minutes, source_minutes) in a single low-cost call. It is ideal for data cleaning pipelines processing up to 200 rows of transcription records where no external data, predictions, or live lookups are needed. Prefer it over general-purpose analytics when you specifically want two co-generated reports (outlier flags + fill) on transcription minute fields within a flat-rate $0.01 USDC charge.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:54:54.051Z","isFirstParty":false,"canonicalSlug":"transcript-preparation-iqr-outlier-flags-explicit-missing-value-fill-74eeec6c"}