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Dataset Partition Sizes — Trailing Mean Series + Base-100 Series
x402
Dataset Partition Sizes — Trailing Mean Series + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Computes trailing moving-average series and base-100 index series for dataset partition size metrics (row_count or file_mb) supplied by the user.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset partition sizes — Trailing mean series + Base-100 series: Trailing mean series + Base-100 series for supplied dataset partition sizes records (row_count, file_mb). 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 independent analytical reports: (1) a trailing moving-average series computed over the specified window for the chosen metric field (row_count or file_mb), and (2) a base-100 index series anchored at the specified base_index row — both computed locally from the supplied records, covering up to 200 rows across any dataset groups and dates provided.
Example use cases
Smoothed row growth trend for ETL pipeline
“I have 60 days of row_count readings for my ETL pipeline partitions across two groups. Can you calculate a trailing mean with a window of 7 and also show me a base-100 index starting from day 0 so I can see the smoothed growth trend?”
File size baseline comparison for data lake
“I want to see how my data lake partition file sizes have grown relative to the first snapshot. Please compute a base-100 index series and a trailing mean with window 5 for my file_mb records across the 'raw' and 'processed' dataset groups.”
Detecting storage expansion in partition data
“Here are my dataset partition records with dates, row counts, and file sizes for the last 90 days across three groups. Give me the trailing mean series using a window of 4 and the base-100 index series for file_mb so I can spot which group is expanding fastest.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-07-147?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have dataset partition size records (row_count or file_mb) and need both a smoothed trailing mean trend and a base-100 growth index in a single call. It is ideal for data engineers monitoring how partition sizes evolve over time without needing an external data connection — all analytics run locally on supplied data. Prefer this over general statistics endpoints when you specifically need rolling-mean smoothing combined with indexed normalization for storage or row-count metrics.
Side effects
- More than 200 rows submitted — request rejected due to maxItems limit
- Missing required fields (row_id, date, dataset_group, row_count, file_mb) in any row — validation error
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Window size exceeds number of rows — trailing mean series may be empty or incomplete
- base_index out of range for provided rows — index series anchor error
- Null values in the selected metric field — may produce gaps or NaN entries in output series
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer | |
| base_index | integer |
Tags
x402
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