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Time Series Completeness — Category Frequencies + Keyed Dataset Comparison
x402
Time Series Completeness — Category Frequencies + Keyed Dataset Comparison 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 two local analytical reports on time series completeness data: category frequency distribution by group and keyed row-by-row comparison between two datasets (up to 200 rows each).
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Category frequencies + Keyed dataset comparison: Category frequencies + 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.
Output
Returns two independent analytical reports: (1) a category frequency table showing how often each dataset_group appears across the supplied rows, and (2) a keyed row-by-row comparison between the primary and secondary datasets, highlighting differences in observed_points and expected_points for matching row IDs. Both reports are computed locally with no external lookups.
Example use cases
Audit data pipeline coverage gaps by group
“I have two snapshots of my daily time series completeness records — each row has a row_id, dataset_group, date, observed_points, and expected_points. Can you run the category frequency report so I can see how often each group appears, and do a keyed comparison between the two snapshots to spot where observed counts shifted?”
Monitor sensor data completeness trends
“My IoT pipeline produces daily completeness records with observed vs expected data points for each sensor group. I've got two datasets — a baseline and this week's export, each up to 200 rows — can you compare them row by row and also give me the frequency breakdown by sensor group?”
Validate ETL output between staging and production
“I need to compare our staging and production time series completeness exports — both have row_id, dataset_group, date, observed_points, and expected_points fields. Can you run a keyed dataset comparison to flag mismatches and also show me the category frequencies so I know which groups dominate each dataset?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-111?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need simultaneous category frequency analysis AND a keyed row-level comparison for time series completeness data in a single $0.01 call. It is purpose-built for observed vs expected point count data with dataset_group and date dimensions, and processes up to 200 rows per dataset without any external data fetching or prediction — ideal for data quality audits, pipeline validation, and completeness monitoring workflows.
Side effects
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) cause validation errors
- Date values not matching YYYY-MM-DD pattern are rejected
- Submitting more than 200 rows returns an error
- Row IDs present in one dataset but not the other may produce unmatched rows in the keyed comparison
- Null numeric values are accepted but may affect completeness calculations
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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