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Data Ingestion Batches — Base-100 Series + Explicit Missing-Value Fill
x402
Data Ingestion Batches — Base-100 Series + Explicit Missing-Value Fill 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 Base-100 index series and fills missing values (zero/mean/median) for up to 200 rows of data ingestion batch records (received_rows, accepted_rows).
Price / call$0.01
Success—
StatusUnknown
How this service works
Data ingestion batches — Base-100 series + Explicit missing-value fill: Base-100 series + Explicit missing-value fill for supplied data ingestion batches records (received_rows, accepted_rows). 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 for the submitted rows: (1) a Base-100 index series rebasing the selected field (received_rows or accepted_rows) to 100 at the specified base index row, and (2) an explicit missing-value fill series using the chosen method (zero, mean, or median). Results cover all submitted rows (up to 200) using local analytical engines with no external data access.
Example use cases
ETL pipeline acceptance rate indexing
“I have a week of ETL batch records across two pipeline groups. Can you normalize the accepted_rows to a base-100 index starting at day 0 and fill any null values with the mean so I can compare acceptance trends across groups?”
Data quality gap filling for ingestion metrics
“My ingestion log has some missing received_rows entries. Fill those gaps using the median of the available values, then compute a base-100 series so I can see how throughput has changed over time — I have about 50 rows spanning the last month.”
Multi-group ingestion throughput comparison
“I want to compare received_rows across three dataset groups over the past quarter — can you fill any missing values with zero and generate a base-100 index starting from index 0 for all 120 rows so I can benchmark each group against its own starting point?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-01-169?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to normalize time-series ingestion metrics (received_rows or accepted_rows) to a common base-100 scale for trend comparison, and/or need to impute missing numeric values before analysis — all in a single cheap call ($0.01 USDC) against your own supplied data with no external lookups. Prefer it over general-purpose analytics tools when you want two pre-packaged reports (indexing + gap-fill) for pipeline batch data specifically, without setting up your own compute environment.
Side effects
- More than 200 rows submitted — request rejected, reduce batch size
- Missing required fields (row_id, date, dataset_group) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- base_index out of range (must be 0–199 and within submitted row count) — error
- All values null for chosen field — mean/median fill may return zero or undefined
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string | |
| base_index | integer |
Tags
x402
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