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Source Diversity — Exact Row Deduplication + Trailing Mean Series
x402
Source Diversity — Exact Row Deduplication + 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 2026-10-23).
Deduplicates rows and computes a trailing mean series for source diversity metrics (source_count, outlet_count) over up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Source diversity — Exact row deduplication + Trailing mean series: Exact row deduplication + Trailing mean series for supplied source diversity records (source_count, outlet_count). 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 reports: (1) a deduplicated set of rows with exact duplicates removed, and (2) a trailing mean series for the specified field (source_count or outlet_count) computed over the given window size, applied to the supplied rows grouped by channel_group and date.
Example use cases
News source diversity smoothing
“I have 50 rows of daily news source diversity records with source_count and outlet_count per channel group. Can you deduplicate them and compute a trailing mean series for source_count with a window of 7 days?”
Outlet count deduplication for media audit
“I need to clean up my outlet_count data across 3 channel groups — can you remove any exact duplicate rows and give me a trailing mean series for outlet_count with a window of 5?”
Channel group time series cleanup
“Here are 100 rows of source diversity records by date and channel_group. Please deduplicate them exactly and then calculate a rolling trailing mean for source_count using a window of 10.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-17-045?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 source diversity records (with source_count and outlet_count) and need both exact row deduplication and a trailing mean time series in a single low-cost call. Ideal for media analytics pipelines where data quality and smoothing are needed together before downstream analysis. Not suitable for live data fetching, prediction, or large-scale batch processing beyond 200 rows.
Side effects
- Fewer than 1 row supplied — request rejected
- Window size exceeds number of rows — trailing mean may be undefined or partial
- Rows missing required fields (row_id, date, channel_group) — validation error
- More than 200 rows submitted — request rejected at limit
- Malformed date strings not matching YYYY-MM-DD — schema validation failure
- Null values in source_count or outlet_count may produce null entries in trailing mean
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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