{"uid":"cap_Th67qZvZXDtD6Cc4qO4oi","slug":"join-coverage-duplicate-key-report-and-missing-value-fill-2780ccab","name":"Join Coverage Duplicate Key Report and Missing Value Fill","description":"Join coverage — Duplicate key report + Explicit missing-value fill: Duplicate key report + Explicit missing-value fill for supplied join coverage records (matched_rows, source_rows). 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-09-070?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["matched_rows","source_rows"],"type":"string","default":"matched_rows"},"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_w2O5PCdULWRxppDCg7Sl5","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 join coverage records to identify duplicate keys and fill missing values in matched_rows or source_rows fields using zero, mean, or median imputation.","exampleAgentPrompt":"Check my join coverage data for duplicate row IDs and fill any missing matched_rows values using median — here are my rows: row-1/2026-10-01/group-a with matched_rows=10 and source_rows=1, row-2/2026-10-02/group-b with matched_rows=null and source_rows=2, up to about 50 rows total.","exampleUseCases":[{"title":"ETL pipeline data quality audit","prompt":"I just ran a join between my transactions and customers tables and got back 120 coverage rows — can you check them for duplicate row IDs and fill any missing source_rows values using the median? Here are the rows with row_id, date, dataset_group, matched_rows, and source_rows fields."},{"title":"Missing value imputation for reporting","prompt":"I have about 80 join coverage records across two dataset groups and some of the matched_rows values are null — can you fill those nulls using the mean and also flag any duplicate keys in the same pass?"},{"title":"Data validation before downstream aggregation","prompt":"Before I aggregate my join coverage metrics, can you run a duplicate key check and fill any missing source_rows fields with zero for these 150 rows across group-a and group-b?"}],"resultDescription":"Returns two independent reports: (1) a duplicate key report identifying any row_id values that appear more than once across the submitted records, and (2) a missing value fill report showing the original and imputed values for the target field (matched_rows or source_rows) using the chosen method (zero, mean, or median). Both reports are computed locally against the supplied data with no external lookups.","failureModes":["Exceeds 200 row limit — request rejected or truncated","Invalid date format not matching YYYY-MM-DD pattern — validation error","missing required fields (row_id, dataset_group, date) — schema validation failure","numeric values outside allowed range (-1T to 1T) — rejection","empty rows array — schema minItems violation"],"whenToPreferThis":"Choose this endpoint when you need a combined duplicate-key detection and missing-value imputation pass over join coverage data (matched_rows, source_rows) in a single cheap call. Best suited for small-to-medium datasets up to 200 rows where both data quality reports are needed simultaneously. Prefer this over general-purpose analytics when your data specifically follows the join coverage schema with dataset_group and date dimensions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:37.864Z","isFirstParty":false,"canonicalSlug":"join-coverage-duplicate-key-report-and-missing-value-fill-2780ccab"}