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Sampling Observations String Normalisation and Missing Value Fill
x402
Sampling Observations String Normalisation and 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 strings and fills missing values for up to 200 sampling observation records (sample_value or sample_weight) using zero, mean, or median imputation, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied sampling observations records (sample_value, sample_weight). 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 string-normalised and missing-value-filled versions of the supplied sampling observation rows, with imputed values for the chosen field (sample_value or sample_weight) using the selected method (zero, mean, or median). No external lookups or predictions are performed; results are based entirely on the supplied data.
Example use cases
Survey data missing value imputation
“I have 80 rows of survey sampling data with some null sample_value entries. Can you normalise the strings and fill those missing values using the median so I get two clean analytical reports back?”
Weighted sample zero-fill for batch processing
“I need to prep my sampling observations for analysis — about 120 rows with dataset_group and date fields. Please normalise the strings and fill any missing sample_weight values with zero.”
Group sample mean imputation for reporting
“I've got sampling records across two groups, group-a and group-b, for October 2026 — around 60 rows. Can you normalise the strings and impute any missing sample_value fields using the mean, and give me the two reports?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-037?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local string normalisation combined with explicit missing-value imputation (zero, mean, or median) for small-to-medium sampling datasets of up to 200 rows with sample_value and sample_weight fields, and you want two bundled analytical reports for a flat $0.01 USDC fee with no external network dependencies.
Side effects
- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, dataset_group, date) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Values outside allowed numeric range (-1e12 to 1e12) are rejected
- Invalid method or field enum values cause schema validation failure
- Empty rows array (minItems: 1 not met) returns error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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