{"uid":"cap_8h3BDtMSCnIrNZU65JF1T","slug":"ticket-escalations-explicit-missing-value-fill-349e33e7","name":"Ticket Escalations — Explicit Missing-Value Fill","description":"Ticket escalations - Explicit missing-value fill: Explicit missing-value fill for Ticket escalations. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded explicit missing-value fill report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-ticket-escalations-fill-missing?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team","date","tickets","escalations"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"team":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"tickets":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"escalations":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","team":"group-a","row_id":"row-1","tickets":10,"escalations":1},{"date":"2026-10-02","team":"group-b","row_id":"row-2","tickets":20,"escalations":2},{"date":"2026-10-03","team":"group-a","row_id":"row-3","tickets":15,"escalations":3},{"date":"2026-10-04","team":"group-b","row_id":"row-4","tickets":30,"escalations":4}],"maxItems":200,"minItems":1},"field":{"enum":["tickets","escalations"],"type":"string","default":"tickets"},"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_j9vXg4lky83suBZkQvq8h","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":"Fills missing numeric values (tickets or escalations) in up to 200 ticket-escalation records using zero, mean, or median imputation, returning a bounded local analytics report.","exampleAgentPrompt":"I have a dataset of 50 ticket escalation records by team and date, some rows have null escalation counts — can you fill those missing escalation values using median imputation?","exampleUseCases":[{"title":"Clean support team escalation dataset","prompt":"I've got about 80 rows of daily ticket and escalation data for our support teams, but some of the escalation counts are missing — fill them in using median so I can run my report."},{"title":"Zero-fill missing ticket counts","prompt":"My ticket escalation records have some null ticket values — can you replace all those missing tickets with zero so the dataset is complete?"},{"title":"Mean imputation before escalation rate analysis","prompt":"Before I calculate escalation rates, I need to fill in the missing escalation numbers across my 120-row dataset using mean — can you do that for the escalations field?"}],"resultDescription":"Returns a bounded report of up to 200 ticket-escalation records with the specified null field (tickets or escalations) replaced using the chosen method (zero, mean, or median), along with local descriptive analytics summarizing the fill operation.","failureModes":["Fewer than 1 row submitted — returns validation error","More than 200 rows submitted — rejected with maxItems error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Unknown method value outside zero/mean/median enum — rejected","Unknown field value outside tickets/escalations enum — rejected","All values already non-null — fill operation is a no-op but still succeeds","row_id missing or empty string — validation error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local missing-value imputation on ticket-escalation data (up to 200 rows) without sending data to an external enrichment or forecasting service. It is purpose-built for support analytics datasets with team and date dimensions and offers three standard statistical fill methods in a single bounded call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T00:46:47.950Z","isFirstParty":false,"canonicalSlug":"ticket-escalations-explicit-missing-value-fill-349e33e7"}