{"uid":"cap_IIPISfYs5-KbcvTi5HAwo","slug":"join-coverage-string-normalisation-and-secondary-measure-weighted-mean-1910cfa7","name":"Join Coverage String Normalisation and Secondary-Measure Weighted Mean","description":"Join coverage — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean 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-09-034?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"}}},"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_XXz2GPBotx9nxvkBfLQ-T","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":"Computes string normalisation and secondary-measure weighted mean analytics for join coverage records (matched_rows, source_rows) across up to 200 rows, returning 2 independent reports.","exampleAgentPrompt":"Can you run string normalization and a secondary-measure weighted mean on my join coverage data? I have 4 rows — group-a on 2026-10-01 with matched_rows=10 and source_rows=1, group-b on 2026-10-02 with matched_rows=20 and source_rows=2, group-a on 2026-10-03 with matched_rows=15 and source_rows=3, and group-b on 2026-10-04 with matched_rows=30 and source_rows=4 — and I want to analyze the matched_rows field.","exampleUseCases":[{"title":"Join coverage quality check by group","prompt":"I have join coverage records for two dataset groups over the past week — each row has matched_rows and source_rows. Can you normalize the string fields and compute a weighted mean on matched_rows so I can see which groups have the best coverage?"},{"title":"Weighted mean for source row auditing","prompt":"Run a secondary-measure weighted mean on source_rows for my join coverage dataset — I have about 50 rows across groups 'prod' and 'staging' from October 2026. I also want the string normalization report included."},{"title":"Multi-group join coverage summary","prompt":"I need two analytics reports on my join coverage data: string normalisation and a weighted mean using matched_rows as the secondary measure. There are three dataset groups across dates in late 2026, up to 120 rows total."}],"resultDescription":"Returns 2 independent analytical reports: (1) string normalisation results for the join coverage records, and (2) a secondary-measure weighted mean computed over the selected field (matched_rows or source_rows), both derived locally from the supplied rows without external lookups.","failureModes":["More than 200 rows submitted — exceeds maxItems limit, request rejected","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) on any row — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Numeric values outside allowed range (±1,000,000,000,000) — rejected","Empty rows array (minItems=1 not met) — request rejected","Invalid field enum value (not 'matched_rows' or 'source_rows') — rejected"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and a secondary-measure weighted mean computed together on join coverage data (matched_rows, source_rows) in a single low-cost call. It is ideal for ETL pipeline auditing, data quality checks on join operations, or summarising coverage ratios across dataset groups. Prefer this over histogram or ordering endpoints when you specifically need weighted averaging and string normalisation as your two analytical outputs.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T12:48:38.785Z","isFirstParty":false,"canonicalSlug":"join-coverage-string-normalisation-and-secondary-measure-weighted-mean-1910cfa7"}