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Dataset Storage — String Normalisation + Explicit Missing-Value Fill
x402
Dataset Storage — String Normalisation + 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 2026-10-15).
Normalises string fields and fills missing numeric values (used_mb, row_count) in dataset storage records using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset storage — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied dataset storage records (used_mb, row_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
Two analytical reports covering the supplied dataset storage records (up to 200 rows), with string fields normalised and missing numeric values (used_mb or row_count) explicitly filled using the chosen method (zero, mean, or median). No external lookups or predictions are made; all processing uses local analytical engines.
Example use cases
Impute missing storage metrics before reporting
“I have 80 dataset storage records where some used_mb values are null — fill them using median imputation and normalise the dataset_group strings so I can generate a clean storage report.”
Clean row_count gaps in pipeline data
“My dataset storage table has about 60 rows and several row_count fields are missing — can you fill those nulls with the mean and also normalise any messy string fields? I need two summary reports back.”
Standardise storage records for data warehouse ingestion
“Before I load these 120 dataset storage rows into our warehouse, I need the dataset_group strings normalised and any null used_mb values filled with zero — run that and return the two analytical reports.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-18-037?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local string normalisation combined with explicit missing-value imputation specifically for dataset storage records (used_mb, row_count fields) and want two analytical reports back in a single low-cost call. Prefer it over general-purpose data cleaning tools when your data fits the dataset storage schema and you need a fast, deterministic, offline result with no external dependencies.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, dataset_group, date) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Invalid field enum value (must be 'used_mb' or 'row_count') — rejected
- Invalid method enum value (must be 'zero', 'mean', or 'median') — rejected
- Numeric values outside allowed range (±1,000,000,000,000) — validation error
- Empty rows array — rejected (minItems: 1)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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