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Duplicate Observations Analytics: Base-100 Series + Two-Measure Correlation
x402
Duplicate Observations Analytics: Base-100 Series + 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 2026-10-18).
Computes a Base-100 indexed time series and a two-measure correlation report for supplied duplicate-observation records (duplicate_rows, total_rows) — up to 200 rows, two independent analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Base-100 series + Two-measure correlation: Base-100 series + 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 independent analytical reports: (1) a Base-100 indexed series normalizing the selected field (duplicate_rows or total_rows) relative to the specified base_index row, and (2) a two-measure correlation report between duplicate_rows and total_rows across the supplied records. No external lookups or predictions are made — all computation is performed locally on the supplied data.
Example use cases
Data pipeline duplicate trend indexing
“I have daily duplicate row counts from two dataset groups over the past month — can you index them to a base-100 series starting from the first row and also give me a correlation between duplicate_rows and total_rows? Here's my data: group-a on 2026-11-01 had 5 duplicate_rows out of 100 total, group-a on 2026-11-02 had 8 duplicate_rows out of 120 total, group-b on 2026-11-01 had 12 duplicate_rows out of 200 total, group-b on 2026-11-02 had 18 duplicate_rows out of 210 total.”
Cross-group duplicate correlation audit
“We're auditing data quality across two ingestion pipelines. Can you compute the two-measure correlation between duplicate_rows and total_rows for these records and also produce a base-100 indexed series using total_rows as the field, starting at base_index 0? Groups are pipeline-x and pipeline-y across five dates in October 2026.”
Monitoring duplicate rate normalization
“I want to normalize my weekly duplicate observation counts to a base-100 index so I can compare trends — use duplicate_rows as the field and base it off row index 2. Also run the two-measure correlation report on the same dataset. I have 6 rows across dataset groups alpha and beta from 2026-09-01 to 2026-09-06.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-165?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two simultaneous local analytical outputs — a Base-100 normalized time series AND a correlation between duplicate_rows and total_rows — computed entirely from supplied data without any external API calls or predictions. Ideal for data quality workflows where you want to track duplicate observation trends over time and measure how duplicate counts relate to total row volumes across dataset groups.
Side effects
- Fewer than 1 row supplied — minItems:1 validation error
- More than 200 rows supplied — maxItems:200 exceeded
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- base_index out of range (0–199) — schema validation error
- null values in duplicate_rows or total_rows may affect correlation computation
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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