{"uid":"cap_xlYddjqHEfnBWF-SAQc89","slug":"time-series-completeness-analytics-record-quality-audit-string-1749ae43","name":"Time Series Completeness Analytics — Record Quality Audit, String Normalisation & Weighted Mean","description":"Time series completeness — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied time series completeness records (observed_points, expected_points). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-205?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","observed_points","expected_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"expected_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_points":1,"observed_points":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_points":2,"observed_points":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_points":3,"observed_points":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_points":4,"observed_points":30}],"maxItems":200,"minItems":1},"field":{"enum":["observed_points","expected_points"],"type":"string","default":"observed_points"}}},"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_Qj7vV0aGdULFSt3Ku5XQB","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":"Runs three local analytical reports on time series completeness data (observed vs expected points): record quality audit, string normalisation, and secondary-measure weighted mean — up to 200 rows per call.","exampleAgentPrompt":"Can you run all three analytics reports — record quality audit, string normalisation, and weighted mean — on my time series completeness data? I have up to 50 rows with dataset groups like 'sensor-a' and 'sensor-b', dates from 2025-01-01 to 2025-01-50, observed_points and expected_points values, and I want to weight on observed_points.","exampleUseCases":[{"title":"Data pipeline completeness health check","prompt":"I need to audit the quality of my data pipeline completeness logs — I have 120 rows with date, dataset_group, observed_points and expected_points columns. Can you run the record quality audit, string normalisation, and weighted mean reports on them, using observed_points as the field?"},{"title":"Sensor feed gap detection audit","prompt":"My IoT sensor feeds have been inconsistent lately. Can you analyse these 80 completeness records — each has a row_id, a sensor group name, a date, and observed vs expected data point counts — and give me the quality audit, normalised strings, and a weighted mean summary?"},{"title":"Monthly reporting data quality review","prompt":"Before I send out our monthly data completeness report, can you run the three analytics — quality audit, string normalisation, and secondary-measure weighted mean — on these 200 rows of completeness records with observed_points and expected_points for each dataset group and date?"}],"resultDescription":"Returns three independent analytical reports computed locally: (1) a record quality audit identifying issues in the completeness records, (2) a string normalisation report for text fields such as dataset_group, and (3) a secondary-measure weighted mean computed over the selected field (observed_points or expected_points) across up to 200 input rows. No external data is fetched or predictions made.","failureModes":["More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, dataset_group, date, observed_points, expected_points) — validation error","Date field not matching YYYY-MM-DD pattern — schema validation failure","Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejected","Invalid field enum value (must be 'observed_points' or 'expected_points') — schema error","Payment not included or insufficient — x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical operations (quality audit, string normalisation, weighted mean) on time series completeness data in a single low-cost call ($0.01 USDC for all three reports). Ideal when you already have observed vs expected point counts per date and dataset group and want offline/local analysis without any live lookups, predictions, or external integrations.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:43.840Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-analytics-record-quality-audit-string-1749ae43"}