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Relaystation FillNA – Missing Value Imputation
x402
Relaystation FillNA – Missing Value Imputation is a paid API for AI agents from api.relaystation.ai, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).
Fills empty/null cells in tabular data using value, forward-fill, backward-fill, mean, median, or mode strategies
Price / call$0.01
Success—
StatusUnknown
How this service works
$0.0002/MB. Fill empty cells by value, forward/backward fill, mean, median, or mode. 1¢ x402 min; remainder auto-credits — relaystation.ai/penny
Output
Returns the input dataset with all specified null/empty cells filled according to the chosen strategy (constant value, forward-fill, backward-fill, mean, median, or mode per column). Output is the cleaned tabular data ready for downstream use.
Example use cases
ML pipeline missing data cleanup
“Before I train my model, fill all null values in my training dataset using column means — here's the CSV with gaps in 'age', 'income', and 'score' columns.”
Time series forward-fill for gaps
“I have sensor readings exported as a table with some missing timestamps — forward-fill the empty cells so there are no gaps in the series.”
Survey data mode imputation
“I've got a survey results table with lots of blank responses in the 'region' and 'category' columns — fill those blanks using the most common value (mode) for each column.”
Technical details
Endpoint
POSThttps://api.relaystation.ai/v1/data/fillnaWhen to prefer
Choose this endpoint when you need a lightweight, pay-per-use missing value imputation step in a data pipeline without spinning up a full data science environment. Ideal for preprocessing CSVs before ML training, cleaning exported spreadsheets, or handling gaps in time series data. Best when you need a simple statistical fill strategy (mean, median, mode, ffill, bfill, or constant) rather than complex model-based imputation.
Side effects
- Invalid or unsupported fill strategy specified
- Malformed or unparseable input data format
- Column referenced for fill does not exist in dataset
- Numeric strategy (mean/median) applied to non-numeric column
- Payload too large or malformed causing processing error
- Insufficient data to compute mean/median/mode (all nulls in column)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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