# Relaystation FillNA – Missing Value Imputation

> 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

## Facts

- Endpoint: POST https://api.relaystation.ai/v1/data/fillna
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/relaystation-fillna-missing-value-imputation-0c3b0bba
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5V5e-GRcy1S_XlVOCz36F

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability relaystation-fillna-missing-value-imputation-0c3b0bba -d '<json body>'
```

Example prompt: I have a CSV with a bunch of empty cells in the 'age' and 'salary' columns — can you fill them using the mean of each column so the dataset is complete for modeling?

## When to prefer this

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.

## Known failure modes

- 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)

## 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.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method",
    "bodyType",
    "body"
   ],
   "properties": {
    "body": {
     "properties": {}
    },
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "POST",
      "PUT",
      "PATCH"
     ],
     "type": "string"
    },
    "bodyType": {
     "enum": [
      "json",
      "form-data",
      "text"
     ],
     "type": "string"
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object"
    }
   }
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/relaystation-fillna-missing-value-imputation-0c3b0bba/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from api.relaystation.ai](https://www.zero.xyz/host/api.relaystation.ai/llms.txt)