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Dataset Partition Sizes — Daily Sum Series + Base-100 Series
x402
Dataset Partition Sizes — Daily Sum 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 a daily sum time series and a base-100 index series for supplied dataset partition size records (row_count or file_mb), returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset partition sizes — Daily sum series + Base-100 series: Daily sum 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 daily sum series aggregating the chosen metric (row_count or file_mb) by date across all supplied records, and (2) a base-100 index series normalizing the same daily totals relative to the specified base row, enabling trend comparison. Both reports are computed locally on the supplied data with no external lookups.
Example use cases
Daily row count growth trend
“I have daily partition records for two dataset groups over the past month — can you give me a daily sum series and a base-100 index for row_count so I can see how total rows are growing each day relative to the first day?”
Storage size baseline comparison
“Here are 150 partition records with file_mb values across several dataset groups from January to May. Can you compute the daily total file size series and index it to day 0 so I can see how storage has grown relative to the baseline?”
Multi-group partition analytics for a data pipeline
“My data pipeline logs partition sizes daily for three groups. I want to see both the daily sum of row counts and a normalized base-100 view starting from index 5 — here are the records for the last quarter.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-07-138?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw dataset partition size records and need both a temporal daily aggregation and a normalized index series in a single call. It is ideal for data engineering workflows that need to track partition growth over time and compare it against a baseline period without setting up a full analytics stack. It covers two reports in one payment, making it cost-efficient for combined trend + indexing use cases.
Side effects
- Fewer than 1 or more than 200 rows supplied — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- base_index out of range (>=number of rows) — index error
- Null values in row_count or file_mb may affect aggregation results
- Missing required fields (row_id, dataset_group, date) — schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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