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Time Series Completeness — Base-100 Series + Equal-Width Histogram
x402
Time Series Completeness — Base-100 Series + Equal-Width 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).
Generates a Base-100 index series and an equal-width histogram for time series completeness data (observed vs expected data points) supplied by the caller.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Base-100 series + Equal-width histogram: Base-100 series + Equal-width histogram 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) a Base-100 index series where each row's selected field value is rebased relative to the chosen base index row, and (2) an equal-width histogram dividing the selected field's value range into the specified number of bins with counts per bin. Both reports are computed locally from the supplied rows with no external lookups.
Example use cases
Data pipeline gap monitoring report
“I track how many data points my ETL pipeline collects versus how many I expect each day. Can you take my 60-day completeness log — with observed_points and expected_points per date — rebase the observed_points series to Base-100 starting from day 0, and give me a 10-bin histogram so I can see how the distribution of completeness looks?”
Multi-group completeness trend comparison
“I have completeness records for two dataset groups, 'sensors-east' and 'sensors-west', with daily observed and expected point counts for the last 90 days. Can you generate a Base-100 series rebased from row index 0 and a 7-bin equal-width histogram on the expected_points field so I can compare how each group trends over time?”
Audit historical data coverage anomalies
“I'm auditing data coverage for a historical dataset — I have 150 rows with a date, observed_points, and expected_points for each day. Please rebase the observed_points to Base-100 from the first row and produce a 5-bin histogram so I can spot where coverage was abnormally low or high.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-163?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have already collected time series completeness records (observed vs expected data points) and need both a normalized Base-100 trend view and a frequency distribution histogram in a single call. It is ideal for offline or batch data quality analysis where no live data fetching, prediction, or external enrichment is needed. Prefer this over general-purpose analytics services when you want a low-cost ($0.01 USDC), self-contained dual-report for up to 200 rows of completeness data.
Side effects
- Fewer than 1 or more than 200 rows submitted — rejected by schema validation
- base_index out of range (must be 0–199 and within actual row count)
- bins value outside 1–30 range — schema rejection
- Missing required row fields (row_id, date, observed_points, expected_points) — validation error
- Null values in observed_points or expected_points may affect histogram binning
- Invalid date format (must be YYYY-MM-DD) — schema rejection
- Payment failure via x402 protocol — request not processed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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