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Duplicate Observations Analytics: Category Frequencies + Two-Measure Correlation
x402
Duplicate Observations Analytics: Category Frequencies + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Analyzes duplicate observation records to produce category frequency distributions and a two-measure correlation report for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Category frequencies + Two-measure correlation: Category frequencies + Two-measure correlation 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
Returns two analytical reports based on the supplied rows: (1) a category frequency breakdown showing how often each dataset_group value appears in the records, and (2) a two-measure correlation report quantifying the statistical relationship between the duplicate_rows and total_rows fields across all supplied observations. No external data is fetched; all computation is local.
Example use cases
Data pipeline duplicate rate audit
“I have 80 records from our ETL pipeline tracking duplicate_rows and total_rows across two dataset groups over the past month — can you give me a category frequency breakdown by group and show me how duplicate_rows correlates with total_rows?”
Multi-team dataset quality comparison
“We have observations from three team dataset groups and I want to know how frequently each group appears in the duplicate records plus the correlation between duplicate count and total row count — I'll send you up to 150 rows of data.”
Weekly duplicate observation reporting
“Run two analytics reports on these 60 duplicate observation rows from our weekly data quality check: first a frequency breakdown by dataset_group category, then a correlation between duplicate_rows and total_rows so I can see if bigger datasets tend to have more duplicates.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-108?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 pre-collected duplicate observation records keyed by dataset group and date, and you need both a categorical frequency breakdown and a two-measure correlation between duplicate_rows and total_rows in a single low-cost call. It is ideal for lightweight data quality analytics workflows where you already hold the data locally and do not need external enrichment, predictions, or live lookups.
Side effects
- Fewer than 1 row or more than 200 rows submitted — request rejected
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Null values in both numeric measures may degrade or prevent correlation computation
- Payment of 0.01 USDC not satisfied — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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