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Time Series Completeness — Exact Row Deduplication + Grouped Numeric Summary
x402
Time Series Completeness — Exact Row Deduplication + Grouped Numeric Summary is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Deduplicates exact rows and produces grouped numeric summary statistics for time series completeness records (observed_points, expected_points) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Exact row deduplication + Grouped numeric summary: Exact row deduplication + Grouped numeric summary 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 analytical reports: (1) an exact row deduplication report identifying and removing duplicate entries from the submitted rows, and (2) a grouped numeric summary of the chosen field (observed_points or expected_points) aggregated by dataset_group, including descriptive statistics such as counts, totals, and averages per group.
Example use cases
Daily completeness audit by pipeline group
“I've got completeness records for my data pipelines — each row has a date, a dataset_group like 'sales' or 'inventory', and the observed vs expected point counts. Can you deduplicate any exact duplicate rows and then give me a grouped numeric summary of observed_points broken down by dataset_group?”
Identifying data gaps in sensor feeds
“Here are 150 rows of completeness logs for our sensor feeds, each with a date, group name, observed_points, and expected_points. Run exact deduplication on them and summarize the expected_points field by group so I can see where we have coverage gaps.”
QA check on ingestion completeness reports
“Before we archive these completeness reports, I want to make sure there are no exact duplicate entries and get a quick grouped numeric summary of observed_points by dataset_group — can you process these rows for me?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-040?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both exact duplicate row removal and grouped numeric summaries for time series completeness data in a single call at minimal cost ($0.01 USDC for both reports). It is ideal for data quality pipelines that track observed vs expected data point counts across groups and dates, and need lightweight local analytics without any external lookups or predictions.
Side effects
- Exceeding 200 rows results in rejection or truncation
- Missing required fields (row_id, dataset_group, date, observed_points, expected_points) causes validation errors
- Invalid date format (non-YYYY-MM-DD) triggers schema validation failure
- Numeric values outside the allowed range (-1e12 to 1e12) are rejected
- Submitting fewer than 1 row causes a minItems validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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