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24K Labs CSV Profile
x402
24K Labs CSV Profile is a paid API for AI agents from api.24klabs.ai, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-13).
Profiles a CSV file and returns column-level statistics including inferred type, count, null count, distinct count, min/max/mean for numeric columns, and sample values.
Price / call$0.005
Success—
StatusUnknown
How this service works
Column-level statistics for a CSV: inferred type, count, null count, distinct count, min/max/mean for numeric columns, and sample values. One-call data audit.
Output
Returns a JSON object with per-column statistics including: inferred data type, total count, null count, distinct count, min and max values, mean (for numeric columns), and a list of sample values drawn from the column.
Example use cases
Pre-processing data quality audit
“I have a CSV with customer records — can you run a full column-level profile on it so I can see which columns have nulls, what types were inferred, and what the value ranges look like before I import it into the database?”
Quick dataset exploration before ML training
“Before I start building a model, can you profile this CSV training dataset and give me the stats for each column — types, null counts, distinct counts, and numeric summaries like min, max, and mean?”
Validating a vendor-supplied data file
“A vendor sent us a CSV export — can you audit it column by column and tell me if there are any unexpected nulls, what data types each column has, and show some sample values so I can verify it looks right?”
Technical details
Endpoint
POSThttps://api.24klabs.ai/api/csv-profileWhen to prefer
Choose this endpoint when you need a fast, one-call statistical audit of a CSV file — especially when you want column-level type inference, null/distinct counts, and numeric min/max/mean without writing custom data-profiling code. It is ideal for pre-processing validation, quick dataset exploration, and data quality checks before ETL pipelines or ML workflows.
Side effects
- Malformed or unparseable CSV returns an error indicating the file could not be processed
- Empty CSV file results in an empty statistics object or error
- Very large CSV files may time out or be rejected if they exceed size limits
- Non-CSV content (e.g. JSON or binary) passed as input returns a parse error
- Missing or invalid payment header returns a 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| csv | string |
Output
Schema · Response
{
"type": "json",
"example": {
"rows": 3,
"columns": [
{
"name": "price",
"type": "number"
}
]
}
}Tags
x402
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