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CSV Dataset Profiler
x402
CSV Dataset Profiler is a paid API for AI agents from api.vextorium.com, paid per call via x402, $0.004/call, status unknown (last checked 2026-10-12).
Auto-detects delimiter and profiles a CSV file: row/column counts, per-column types, nulls, unique values, min, max, mean, median, std, sum, top values, duplicate rows, and a sample.
Price / call$0.004
Success—
StatusUnknown
How this service works
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.
Output
A JSON object with: total row count, column count, detected delimiter, count of duplicate rows, a sample of rows, and a per-column profile array where each entry includes column name, inferred type, null count, unique count, top frequent values (with counts), and for numeric columns: min, max, sum, mean, median, standard deviation, and average string length for text columns.
Example use cases
Data quality check before ETL pipeline
“Before I load this CSV into the database, can you profile it and tell me which columns have nulls, what types were detected, and whether there are any duplicate rows? Here's the raw CSV text.”
Exploratory analysis of sales data
“I've got a sales CSV and I want to understand it — can you give me the row and column count, the type of each column, and the min, max, mean, and top 5 most frequent values per column? Here's the CSV content.”
Validating a client-supplied dataset
“A client sent me this CSV file and I need to quickly sanity-check it — auto-detect the delimiter, profile each column for data type and unique values, and flag any duplicate rows. Here's the full CSV text.”
Technical details
Endpoint
POSThttps://api.vextorium.com/estadisticas-csv-pago?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a fast, comprehensive statistical profile of a CSV dataset before processing, cleaning, or loading it — especially when you don't know the delimiter or column types in advance. It covers type inference, nulls, duplicates, distributions, and top values in a single call, making it ideal for automated data quality checks and exploratory data analysis in agent workflows.
Side effects
- CSV text exceeds 5 MB limit — request rejected
- Malformed or empty CSV body returns an error
- Ambiguous delimiter that cannot be auto-detected may produce incorrect column splits
- Non-UTF-8 encoded files may cause parsing errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"filas": 3,
"perfil": [
{
"tipo": "str",
"unicos": 2,
"vacios": 0,
"columna": "city",
"longitud_media": 7,
"mas_frecuentes": [
{
"valor": "Madrid",
"veces": 2
},
{
"valor": "Barcelona",
"veces": 1
}
]
},
{
"max": 120,
"min": 80,
"suma": 300,
"tipo": "int64",
"media": 100,
"unicos": 3,
"vacios": 0,
"columna": "sales",
"mediana": 100,
"desviacion": 20,
"mas_frecuentes": [
{
"valor": 100,
"veces": 1
},
{
"valor": 80,
"veces": 1
},
{
"valor": 120,
"veces": 1
}
]
},
{
"max": 2,
"min": 1,
"suma": 4,
"tipo": "int64",
"media": 1.333333,
"unicos": 2,
"vacios": 0,
"columna": "month",
"mediana": 1,
"desviacion": 0.57735,
"mas_frecuentes": [
{
"valor": 1,
"veces": 2
},
{
"valor": 2,
"veces": 1
}
]
}
],
"muestra": [
{
"city": "Madrid",
"month": 1,
"sales": 100
},
{
"city": "Barcelona",
"month": 1,
"sales": 80
},
{
"city": "Madrid",
"month": 2,
"sales": 120
}
],
"columnas": 3,
"delimitador": ",",
"filas_duplicadas": 0
}
}Tags
x402
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