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Time Series Completeness — Exact Row Deduplication + Explicit Missing-Value Fill
x402
Time Series Completeness — Exact Row Deduplication + Explicit Missing-Value Fill 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).
Deduplicates exact rows and fills missing values (zero, mean, or median) in time series completeness records containing observed and expected point counts, returning 2 analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Exact row deduplication + Explicit missing-value fill: Exact row deduplication + Explicit missing-value fill 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 2 local analytical reports: (1) a deduplicated version of the input rows with exact duplicate records removed, and (2) a version of the data where null values in the specified field (observed_points or expected_points) have been filled using the chosen method (zero, mean, or median). No external lookups or live data retrieval is performed.
Example use cases
Pipeline completeness gap imputation
“I have a time series dataset tracking observed vs expected data points per day for two groups — some rows have null observed_points. Can you fill those missing values using the mean and also remove any exact duplicate rows? I have about 150 rows spanning last quarter.”
Multi-group deduplication audit
“My completeness tracking data for dataset groups 'sales' and 'inventory' has some duplicate entries that crept in from a pipeline bug. Can you deduplicate the exact duplicate rows and fill any missing expected_points using zero, then give me the two reports?”
Data quality cleanup before reporting
“Before I send my monthly completeness report, can you clean up this time series data — remove exact duplicates and fill any nulls in the observed_points column using median — for all 80 daily records across my dataset groups?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-054?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both exact row deduplication AND missing-value imputation on time series completeness data (observed vs expected point counts) in a single call, for up to 200 rows, with no need for live data lookups or external integrations. It is ideal for data pipeline cleanup steps, pre-reporting data quality passes, or batch analytical preparation where local computation suffices and cost must be minimal ($0.01 USDC for 2 reports).
Side effects
- Exceeding 200 rows triggers a validation error
- Missing required fields (row_id, date, observed_points, expected_points) cause row rejection
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Numeric values outside ±1,000,000,000,000 are rejected
- Invalid fill method or field enum value causes request failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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