{"uid":"cap_AQkq5RjZm62obfjzkMtiZ","slug":"join-coverage-analytics-category-frequencies-missing-value-fill-e8b17758","name":"Join Coverage Analytics: Category Frequencies + Missing-Value Fill","description":"Join coverage — Category frequencies + Explicit missing-value fill: Category frequencies + 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-09-112?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_Y4ta-73Tz-TCdsTTSxuy1","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 (matched_rows, source_rows) by computing category frequencies and filling missing values using zero, mean, or median imputation — returns 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Analyze my join coverage data — I have up to 50 rows with matched_rows and source_rows fields grouped by dataset category — give me category frequencies and fill any missing matched_rows values using median imputation.","exampleUseCases":[{"title":"Join coverage audit by dataset group","prompt":"I have join coverage records across two dataset groups — group-a and group-b — with matched_rows and source_rows for each date. Can you compute the category frequencies and fill any missing matched_rows values using median so I can see how balanced the coverage is?"},{"title":"Missing source_rows imputation with zero","prompt":"Some of my join coverage records are missing source_rows values. Can you run the analysis on my 120 rows, use zero fill for the missing source_rows, and also give me the category frequency breakdown by dataset_group?"},{"title":"Daily join match rate profiling","prompt":"I want to profile my join coverage data for October — about 30 rows with matched_rows counts per day across multiple dataset groups. Please compute the category frequencies and use mean imputation to fill any nulls in the matched_rows field."}],"resultDescription":"Two analytical reports: (1) a category frequency distribution showing how often each dataset_group value appears across the supplied rows, and (2) a missing-value fill report for the selected field (matched_rows or source_rows) where nulls are replaced using the chosen method (zero, mean, or median). Results are computed locally with no external lookups.","failureModes":["Rows array empty or missing — minItems:1 required","More than 200 rows submitted — maxItems limit exceeded","Invalid date format — must match YYYY-MM-DD pattern","row_id missing or empty — minLength:1 required","Invalid field enum value — must be 'matched_rows' or 'source_rows'","Invalid method enum — must be 'zero', 'mean', or 'median'","Numeric values out of range (±1,000,000,000,000)","Payment failure — 0.01 USDC x402 payment required"],"whenToPreferThis":"Choose this endpoint when you need both category frequency profiling AND missing-value imputation for join coverage data (matched_rows, source_rows) in a single $0.01 call covering up to 200 rows. Prefer it over separate analytics tools when you want two coordinated reports on the same dataset without external data lookups or live API calls. Ideal for lightweight, local, deterministic analysis of dataset join quality metrics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:41.050Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-category-frequencies-missing-value-fill-e8b17758"}