{"uid":"cap_fRYry7GWkwfQgv7V6000v","slug":"time-series-completeness-analyzer-numeric-distribution-keyed-dataset-c03115f2","name":"Time Series Completeness Analyzer — Numeric Distribution + Keyed Dataset Comparison","description":"Time series completeness — Numeric distribution + Keyed dataset comparison: Numeric distribution + Keyed dataset comparison for supplied time series completeness records (observed_points, expected_points). 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-16-084?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}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"expected_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_points":1,"observed_points":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_points":2,"observed_points":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_points":3,"observed_points":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_points":4,"observed_points":30}],"maxItems":200,"minItems":1},"field":{"enum":["observed_points","expected_points"],"type":"string","default":"observed_points"},"other":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","observed_points","expected_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","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":21},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_points":3,"observed_points":17},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_points":4,"observed_points":33}],"maxItems":200,"minItems":0}}},"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_grcrmdZZUOmIn7BO1JfYq","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 time series completeness records (observed_points vs expected_points) by running two independent analytical reports: a numeric distribution analysis and a keyed dataset comparison, for up to 200 rows.","exampleAgentPrompt":"Analyze the completeness of my time series data — I have up to 50 rows with date, dataset_group, observed_points, and expected_points fields. Run the numeric distribution on observed_points and also compare my primary dataset against a second dataset to spot differences in completeness.","exampleUseCases":[{"title":"Data pipeline completeness audit","prompt":"I have daily records for my ETL pipeline showing how many data points we observed vs how many we expected across two groups, 'feeds-a' and 'feeds-b', for the last 30 days. Can you run the numeric distribution on observed_points and compare those rows against last month's baseline dataset to see where completeness dropped?"},{"title":"Sensor data gap detection","prompt":"We collect sensor readings hourly and I want to check how complete our data is — I have 120 rows with dates, sensor group names, and observed vs expected point counts. Please run both the numeric distribution and the keyed dataset comparison against our reference dataset so I can see where gaps are."},{"title":"API coverage monitoring report","prompt":"I'm tracking API endpoint coverage over time — each row has a date, a service group, the number of calls observed, and the number expected. Can you analyze the distribution of observed_points across my 80 rows and compare this week's dataset against last week's to flag any completeness regressions?"}],"resultDescription":"Returns two independent analytical reports derived from the supplied rows: (1) a numeric distribution report showing statistical spread of the selected field (observed_points or expected_points), and (2) a keyed dataset comparison report that matches rows between the primary and secondary (other) dataset by key to surface differences in completeness values. All analysis is performed locally on the supplied data — no external lookups or live data fetching.","failureModes":["Fewer than 1 row or more than 200 rows supplied — request rejected","Missing required fields (row_id, dataset_group, date, observed_points, expected_points) on any row — validation error","Date field not matching YYYY-MM-DD pattern — schema validation failure","numeric values outside allowed range (±1,000,000,000,000) — rejected","Mismatched keys between primary and secondary dataset resulting in no comparable rows — empty comparison report","Payment of 0.01 USDC not completed via x402 — request not processed"],"whenToPreferThis":"Choose this endpoint when you need to audit time series data completeness by comparing observed vs expected data point counts across dates and groups, and want both a statistical distribution view and a direct row-by-row keyed comparison against a reference dataset — all in a single $0.01 call covering up to 200 rows. Prefer this over generic stats tools when your data is already structured as completeness records with group identifiers and you want the two-report combo without setting up your own analytical environment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:39:13.428Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-analyzer-numeric-distribution-keyed-dataset-c03115f2"}