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Time Series Completeness — Category Frequencies + Base-100 Series
x402
Time Series Completeness — Category Frequencies + Base-100 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 to produce category frequency distributions and a base-100 indexed series report for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Category frequencies + Base-100 series: Category frequencies + Base-100 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
Returns two analytical reports: (1) a category frequency table showing how often each dataset_group appears in the submitted rows, and (2) a base-100 indexed series for the selected field (observed_points or expected_points) anchored at the specified base_index row, enabling relative trend comparison across time.
Example use cases
IoT sensor coverage audit
“I have daily IoT sensor readings for two device groups over the past month — each row has observed_points and expected_points. Can you give me a category frequency breakdown by group and a base-100 series starting from day 0 using observed_points so I can see how data completeness changed over time?”
ETL pipeline data gap report
“My ETL pipeline logs expected vs observed data points per dataset group each day. Can you analyze these completeness records — up to 150 rows — and produce both a category frequency report and a base-100 indexed series for expected_points starting from index 0, so I can spot where the pipeline fell short?”
Multi-group experiment completeness review
“I ran an experiment across three groups over 60 days and tracked observed and expected data points per day. Please generate a frequency distribution of how often each group appears and a base-100 trend series on observed_points from index 0, so I can compare completeness across groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-105?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a categorical frequency summary and a relative base-100 trend index on time series completeness data in a single paid call. It is ideal for data quality audits comparing observed vs expected coverage across multiple groups over time, without requiring any external data lookups or live connections. Prefer it over generic stats tools when your data fits the row schema (date + group + observed/expected points) and you want two distinct analytical views from one API call at low cost.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, observed_points, expected_points) cause row-level rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- base_index out of range (>= number of submitted rows) causes an indexing error
- Null values in observed_points or expected_points may affect series calculation
- Payment failure (insufficient USDC balance) blocks the request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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