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Time Series Completeness Analyzer — Record Quality Audit + Deduplication + Histogram
x402
Time Series Completeness Analyzer — Record Quality Audit + Deduplication + Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
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.
Price / call$0.01
Success—
StatusUnknown
How this service works
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.
Output
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.
Example use cases
Daily sensor coverage quality check
“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?”
ETL pipeline completeness validation
“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.”
Multi-group time series profiling
“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.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-219?utm_source=zero.xyzWhen to prefer
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).
Side effects
- 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
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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