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Time Series Completeness: Category Frequencies + Daily Sum Series
x402
Time Series Completeness: Category Frequencies + Daily Sum Series 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).
Analyzes time series completeness records by computing category frequencies and a daily sum series for observed vs expected data points across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Category frequencies + Daily sum series: Category frequencies + Daily sum series 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.
Output
Two independent analytical reports: (1) a category frequency breakdown showing how often each dataset_group appears in the submitted rows, and (2) a daily sum series aggregating the chosen field (observed_points or expected_points) by date across all rows. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Auditing sensor data coverage by device group
“I have 150 rows of sensor readings from three device groups across the past month, each with observed_points and expected_points per day. Can you compute the category frequencies by group and the daily sum series for observed_points to see where coverage is dropping?”
Monitoring ETL pipeline completeness by source
“My ETL pipeline logs daily record counts — I'll give you up to 200 rows with dataset_group, date, observed_points, and expected_points. Run the category frequencies and daily sum series on expected_points so I can spot which sources are consistently under-delivering.”
Reporting on data feed gaps for a dashboard
“I need a completeness report for my data feeds: here are 80 rows with row_id, dataset_group, date, observed_points, and expected_points. Give me the group frequency breakdown and daily observed_points sums so I can build a gap analysis chart.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-102?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, low-cost dual-report analysis of time series completeness data — specifically category frequency counts and daily aggregated sums — without requiring a live database, external lookup, or prediction engine. It is ideal for batch sizes up to 200 rows where you supply the raw completeness records and want structured analytical summaries returned immediately.
Side effects
- Missing required fields (row_id, date, dataset_group, observed_points, expected_points) cause validation errors
- More than 200 rows submitted exceeds the maxItems limit and will be rejected
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- Null numeric values for both observed_points and expected_points on all rows may produce empty aggregations
- Payment failure via x402 protocol prevents endpoint execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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