{"uid":"cap_Y57rTClF0nHMcK_zut6fW","slug":"time-series-completeness-analyzer-record-quality-audit-deduplication-f453ace8","name":"Time Series Completeness Analyzer — Record Quality Audit + Deduplication + Histogram","description":"Time series completeness — Record quality audit + Exact row deduplication + Equal-width histogram: Record quality audit + Exact row deduplication + Equal-width histogram 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-16-219?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"bins":{"type":"integer","default":5,"maximum":30,"minimum":1},"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_jKeQJhKkxvUlhHWXBuygV","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 analytics reports on time series completeness data (observed vs expected points): record quality audit, exact row deduplication, and equal-width histogram — all on supplied rows, up to 200, with no external lookups.","exampleAgentPrompt":"Can you run a record quality audit, deduplicate exact rows, and produce a 10-bin histogram on my time series completeness data for dataset group 'sensor-network'? Here are the rows: 2024-01-01 through 2024-01-05 for row IDs r1–r5, with observed_points ranging from 80 to 100 and expected_points all set to 100 — use observed_points as the histogram field.","exampleUseCases":[{"title":"Daily sensor coverage quality check","prompt":"I have 90 days of sensor completeness logs — each row has a date, a dataset group, and how many data points were observed vs expected. Can you audit the record quality, flag any duplicate rows, and give me a 7-bin histogram on observed_points so I can see the distribution?"},{"title":"ETL pipeline completeness validation","prompt":"Before we publish our monthly ETL report, audit these 150 completeness records for data quality issues, deduplicate any exact repeated rows, and show me an equal-width histogram with 5 bins on the expected_points field — the rows cover dataset groups 'pipeline-a' and 'pipeline-b' from 2024-03-01 to 2024-03-31."},{"title":"Multi-group time series profiling","prompt":"We have completeness records across 3 dataset groups from the past quarter — can you run all three analytics reports on them: quality audit, dedup check, and a 10-bin histogram on observed_points? The data has about 120 rows with dates in YYYY-MM-DD format and both observed and expected point counts filled in."}],"resultDescription":"Returns three independent analytical reports for the supplied rows: (1) a record quality audit flagging issues like nulls or out-of-range values, (2) an exact row deduplication report identifying repeated records, and (3) an equal-width histogram over the selected numeric field (observed_points or expected_points) with the specified number of bins. No external data is fetched — all analysis is performed on the submitted rows.","failureModes":["Rows exceed 200-item limit — request rejected","Missing required fields (row_id, date, observed_points, expected_points) — validation error","Invalid date format (not YYYY-MM-DD) — schema rejection","bins value outside 1–30 range — validation error","Numeric values outside ±1,000,000,000,000 — schema rejection","Empty rows array — request rejected"],"whenToPreferThis":"Choose this endpoint when you need three analytics operations in one call on time series completeness data (observed vs expected points): record quality auditing, exact deduplication, and histogram profiling. It is ideal for lightweight, self-contained data quality checks on batches up to 200 rows without needing external lookups, predictions, or live data connections. Prefer it over general-purpose analytics when you specifically need the combination of quality audit + dedup + histogram on completeness-style records at low cost ($0.01 per call).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:58.705Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-analyzer-record-quality-audit-deduplication-f453ace8"}