{"uid":"cap_8S4XNcc2bHba9QkKTjSh5","slug":"contact-record-quality-numeric-distribution-missing-value-fill-f959d66d","name":"Contact Record Quality — Numeric Distribution & Missing-Value Fill","description":"Contact record quality — Numeric distribution + Explicit missing-value fill: Numeric distribution + Explicit missing-value fill for supplied contact record quality records (checked_records, duplicate_records). 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-company-03-085?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","checked_records","duplicate_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duplicate_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","checked_records":10,"duplicate_records":1},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","checked_records":20,"duplicate_records":2},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","checked_records":15,"duplicate_records":3},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","checked_records":30,"duplicate_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["checked_records","duplicate_records"],"type":"string","default":"checked_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_umoeW9FBCXd_AQEe_wTuq","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 contact record quality metrics (checked_records, duplicate_records) by computing numeric distributions and filling missing values using a chosen strategy (zero, mean, or median).","exampleAgentPrompt":"I have up to 200 rows of contact record quality data with checked_records and duplicate_records fields — can you run a numeric distribution report and fill any missing checked_records values using median imputation?","exampleUseCases":[{"title":"CRM data quality audit","prompt":"I've got a batch of contact quality records with checked_records and duplicate_records by company group and date — can you compute the numeric distribution for checked_records and fill any missing values using the median so I can see the spread and clean up the nulls?"},{"title":"Duplicate record null imputation","prompt":"My contact dataset has some null entries in the duplicate_records column across a few company groups. Can you fill those missing values using zero imputation and also give me the numeric distribution report for duplicate_records?"},{"title":"Pre-pipeline data cleaning for contact records","prompt":"Before I run my pipeline, I need you to take these 150 rows of contact record quality data and give me a numeric distribution of duplicate_records plus fill all missing checked_records values using mean imputation — I need both reports together."}],"resultDescription":"Returns two analytical reports: (1) a numeric distribution summary for the specified field (checked_records or duplicate_records) covering statistical spread across up to 200 rows, and (2) an explicit missing-value fill report showing which null values were replaced using the chosen strategy (zero, mean, or median). No external lookups or live data are involved — all computation is performed locally on the supplied rows.","failureModes":["Fewer than 1 or more than 200 rows submitted — validation error","Missing required fields (row_id, date, company_group) in any row — schema rejection","Invalid date format (not YYYY-MM-DD) — pattern validation failure","Invalid enum value for field or method — rejected with allowed values","All values null for the target field with mean/median method — may return fill of 0 or NaN","Numeric values outside allowed range (±1 trillion) — schema error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of contact record quality data with checked_records and/or duplicate_records fields and need both a numeric distribution analysis and missing-value imputation in a single low-cost call ($0.01 USDC). It is ideal for offline/batch data cleaning before pipeline ingestion and does not require any external data sources or live lookups. Prefer this over general-purpose analytics tools when you need a paired distribution + fill workflow specifically scoped to contact quality metrics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:48:07.109Z","isFirstParty":false,"canonicalSlug":"contact-record-quality-numeric-distribution-missing-value-fill-f959d66d"}