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Brand Mention Inventories — Trailing Mean Series + Equal-Width Histogram
x402
Brand Mention Inventories — Trailing Mean Series + Equal-Width Histogram 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).
Computes a trailing mean time series and an equal-width histogram for brand mention inventory data (mention_count, source_count) supplied by the caller, up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Trailing mean series + Equal-width histogram: Trailing mean series + Equal-width histogram for supplied brand mention inventories records (mention_count, source_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
Returns two analytical reports: (1) a trailing mean series showing rolling averages of the selected field over the specified window across the time-ordered rows, and (2) an equal-width histogram bucketing the selected field's values into the specified number of bins — both computed locally on the supplied data without any external lookup.
Example use cases
Weekly brand mention trend smoothing
“Here are 50 rows of daily brand mention counts for our three product lines from Q3. Can you calculate a 7-day trailing mean series and a 10-bin histogram on mention_count so I can see the smoothed trend and how the values are distributed?”
Source count distribution for PR audit
“I've got a list of 120 brand mention records with source_count per day across two company groups. Run an equal-width histogram with 8 bins and a trailing mean with window 3 on source_count — I want to see where most of our media coverage is concentrated.”
Competitive brand mention comparison
“I have 80 rows covering two competing brands, each with daily mention_count and source_count. Can you generate a trailing mean series with window 5 and a 6-bin histogram on mention_count so I can compare their mention velocity and distribution?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-148?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you already have brand mention inventory data in hand and need both a rolling average time series and a histogram distribution report in a single low-cost call. It is ideal for offline or batch analytical workflows where no live data fetch, external enrichment, or prediction is needed — just fast local statistical computation on up to 200 supplied rows.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds maximum limit
- window parameter larger than number of rows — trailing mean cannot be computed meaningfully
- Invalid date format (not YYYY-MM-DD) in any row
- Missing required fields (row_id, company_group, date, mention_count, source_count) in any row
- bins value outside 1–30 range — rejected
- field value not one of 'mention_count' or 'source_count' — rejected
- Payment not provided or insufficient — x402 payment required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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