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Podcast Observations — String Normalisation + Trailing Mean Series
x402
Podcast Observations — String Normalisation + 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 2026-11-02).
Runs string normalisation and trailing mean series analytics on user-supplied podcast observation records (download_count, duration_minutes) for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Podcast observations — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied podcast observations records (download_count, duration_minutes). 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 derived from the supplied podcast observation rows: (1) a string-normalised version of the chosen field across all rows, and (2) a trailing mean series computed over the specified rolling window — both produced locally without external lookups or predictions.
Example use cases
Rolling average of podcast downloads
“I've got 120 rows of weekly podcast observation data with row IDs, channel groups, dates, and download counts. Can you compute a trailing mean series on download_count using a window of 4 so I can see the smoothed download trend?”
Normalise episode duration labels
“I have podcast records including episode duration in minutes across multiple channel groups. Please run string normalisation on the duration_minutes field across all 80 rows so the values are consistently formatted.”
Dual report for podcast performance review
“Here are 200 rows of podcast observations with row_id, channel_group, date, download_count, and duration_minutes. Run both string normalisation and a trailing mean series on download_count with a window of 10 for our monthly performance review.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-09-028?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of podcast observation records and need both string normalisation and a rolling/trailing mean series computed together in a single cost-efficient call ($0.01 USDC for both reports). Ideal for offline batch analytics on podcast download or duration data without requiring live data feeds, predictions, or external enrichment.
Side effects
- Fewer than 1 or more than 200 rows supplied — request rejected
- Window size smaller than 2 or larger than 200 — validation error
- Invalid date format (not YYYY-MM-DD) in any row — schema rejection
- Field value not one of the allowed enum values (download_count, duration_minutes) — error
- Missing required row fields (row_id, channel_group, date) — schema validation failure
- All numeric values null — trailing mean may return empty or null results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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