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Duplicate Observations Analytics: Category Frequencies + Trailing Mean Series
x402
Duplicate Observations Analytics: Category Frequencies + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Analyzes duplicate observation records to produce two reports: category frequency distributions by dataset_group and a trailing mean time series for a chosen numeric field.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Category frequencies + Trailing mean series: Category frequencies + Trailing mean series for supplied duplicate observations records (duplicate_rows, total_rows). 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
Two independent analytical reports: (1) a category frequency table showing how often each dataset_group appears in the supplied records, and (2) a trailing mean time series computed over the chosen field (duplicate_rows or total_rows) using the specified rolling window size, covering up to 200 input rows.
Example use cases
Data quality audit by dataset group
“I have 150 rows of duplicate tracking records across groups 'transactions', 'users', and 'events' with dates and duplicate_rows counts — can you generate the category frequency breakdown by group and also compute the trailing mean of duplicate_rows with a window of 5?”
Rolling average trend for duplicate rates
“Here are my daily duplicate observation records for the past quarter, with dataset_group and total_rows filled in — please compute the trailing mean series for total_rows over a window of 7 and also show me the frequency distribution across the groups.”
Sanity check on pipeline duplicate counts
“My ETL pipeline logs 80 rows of duplicate_rows and total_rows per dataset group per day — can you run both the category frequencies report and the rolling mean for duplicate_rows with a window of 2 to help me spot anomalies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-103?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected duplicate observation records (with duplicate_rows and total_rows) and need both a categorical frequency breakdown and a rolling mean trend in a single call for under $0.01 USDC — especially when no external data lookup or prediction is needed, just local statistical computation on supplied data.
Side effects
- Input array is empty or missing — returns validation error
- More than 200 rows supplied — exceeds max item limit
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- duplicate_rows or total_rows values outside allowed numeric range
- window value less than 2 or greater than 200 — schema rejection
- Null values in numeric fields may affect trailing mean calculation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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