Vextorium CSV Stats Profiler is a paid API for AI agents from api.vextorium.com, paid per call via x402, $0.004/call, status unknown (last checked 2026-10-11).
Accepts CSV text and returns statistical profiling of each column: row/column counts, data types, min/max/avg/median/sum/stddev, unique values, most frequent values, empty counts, and duplicate row detection.
Profile a CSV (delimiter auto-detected): rows, columns, type of each column, nulls, unique values, min, max, mean, median, std, sum, top values, duplicate rows and a sample. Understand a dataset before using it.
A JSON object containing: total row count, column count, detected delimiter, a sample of the first rows, a duplicate row count, and a per-column profile array. Each column profile includes: column name, inferred data type (str, int64, etc.), count of empty values, count of unique values, average string length (for text), and for numeric columns: min, max, sum, average, median, and standard deviation. Most frequent values with occurrence counts are also included for each column.
POSThttps://api.vextorium.com/v1/csv-stats?utm_source=zero.xyzChoose this endpoint when you need rapid, per-column statistical profiling of CSV data without setting up a local data processing environment. It is ideal for data quality checks before ETL pipelines, exploratory data analysis on unknown datasets, or when you need a quick summary of numeric distributions and categorical frequencies in tabular data. It handles delimiter auto-detection and type inference, saving preprocessing steps. Prefer this over general-purpose code execution endpoints when you want a structured JSON profile without writing custom analysis code.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"type": "json",
"example": {
"rows": 3,
"sample": [
{
"city": "Madrid",
"month": 1,
"sales": 100
},
{
"city": "Barcelona",
"month": 1,
"sales": 80
}
],
"columns": 3,
"profile": [
{
"type": "str",
"empty": 0,
"column": "city",
"unique": 2,
"avg_length": 7,
"most_frequent": [
{
"times": 2,
"value": "Madrid"
},
{
"times": 1,
"value": "Barcelona"
}
]
},
{
"avg": 100,
"max": 120,
"min": 80,
"sum": 300,
"type": "int64",
"empty": 0,
"column": "sales",
"median": 100,
"unique": 3,
"deviation": 20,
"most_frequent": [
{
"times": 1,
"value": 100
},
{
"times": 1,
"value": 80
}
]
}
],
"delimiter": ",",
"duplicate_rows": 0
}
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