{"uid":"cap_aCFuLR77OUB6YqJPw9a7G","slug":"join-coverage-analytics-numeric-interval-filter-missing-value-fill-a2bff954","name":"Join Coverage Analytics — Numeric Interval Filter + Missing-Value Fill","description":"Join coverage — Numeric interval filter + Explicit missing-value fill: Numeric interval filter + 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-09-135?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_zKemxvHPtkdiKFzT210k-","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":"Filters join coverage records (matched_rows, source_rows) to a numeric interval and fills missing values, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 150 join coverage records with matched_rows and source_rows values — can you filter matched_rows to the range 0–100, fill any missing values using median, and give me two analytical reports on the result?","exampleUseCases":[{"title":"ETL pipeline join quality check","prompt":"Here are 80 join coverage records from our nightly ETL run with matched_rows and source_rows per dataset_group — filter matched_rows between 0 and 500, fill any nulls with the mean, and give me two reports so I can spot where joins are degrading."},{"title":"Missing-value imputation for source rows","prompt":"I've got 120 rows of join coverage data and source_rows has a bunch of nulls — fill those missing source_rows values using zero, keep only rows where source_rows falls between 1 and 1000, and return the two analytical reports."},{"title":"Dataset group coverage audit","prompt":"Can you analyze these 60 join coverage records across our group-a and group-b datasets? Filter matched_rows to between 5 and 200, replace any missing matched_rows with the median, and give me both reports so I can audit coverage quality."}],"resultDescription":"Two independent analytical reports on the submitted join coverage records, after applying the specified numeric interval filter to the chosen field (matched_rows or source_rows) and filling any missing values using the selected method (zero, mean, or median). Reports are generated locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row submitted — validation error","More than 200 rows submitted — request rejected","date field not matching YYYY-MM-DD pattern — validation error","numeric values outside ±1,000,000,000,000 — validation error","invalid fill method or field enum value — rejected","all rows filtered out by interval — empty or degenerate report"],"whenToPreferThis":"Choose this endpoint when you need to both clean join coverage data (fill nulls, apply numeric bounds) and receive two analytical reports in a single call, at low cost ($0.01 USDC). Ideal for data engineering pipelines auditing join quality across dataset groups, especially when you need imputation and interval filtering combined. Not suitable for live data lookups, predictions, or datasets larger than 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:03.564Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-numeric-interval-filter-missing-value-fill-a2bff954"}