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Seguimiento Fácil CSV Profiler
x402
Seguimiento Fácil CSV Profiler is a paid API for AI agents from seguimiento-facil.gregjosegf1.chatgpt.site, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-15).
Analyzes a CSV dataset to produce a statistical summary including column types, row count, duplicate detection, empty cell counts, and numeric column statistics.
Price / call$0.003
Success—
StatusUnknown
How this service works
Un kit local y práctico para revisar reportes CSV, encontrar duplicados y entender tus datos.
Output
Returns a JSON object with ok:true and a summary containing: list of column names, total row count, column count, number of duplicate rows, number of empty cells, number of rows with empty cells, and per-numeric-column statistics (min, max, sum, count, average).
Example use cases
Sales report data quality check
“I just exported a sales report as CSV with columns like customer_name, amount, and date — can you analyze it and tell me if there are any duplicate entries, empty cells, or suspicious numeric values in the amount column?”
HR dataset duplicate detection
“I have an employee CSV with columns name, department, and salary — please profile it so I can see if any duplicate rows snuck in and get a quick summary of the salary range across all records.”
Survey results structure audit
“I've got survey response data in CSV format and I need to know how complete it is — can you check for empty cells, count the total responses, and give me stats on any numeric rating columns?”
Technical details
Endpoint
POSThttps://seguimiento-facil.gregjosegf1.chatgpt.site/api/csv-profile?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, lightweight statistical profile of a CSV dataset — especially when you want duplicate detection, empty cell counts, and numeric summaries in a single call without setting up a full data pipeline or ETL tool. Best suited for small-to-medium CSV files where quick data quality validation is the goal.
Side effects
- Malformed or non-CSV input may cause parsing errors
- Very large CSV payloads may time out or exceed size limits
- CSV with no headers may produce unexpected column naming
- All-string columns will have no numericColumns output
- Network or payment authorization failures return non-200 responses
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| outputrequired | object |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"summary": {
"columns": [
"name",
"age"
],
"rowCount": 1,
"emptyCells": 0,
"columnCount": 2,
"duplicateRows": 0,
"numericColumns": {
"age": {
"max": 42,
"min": 42,
"sum": 42,
"count": 1,
"average": 42
}
},
"rowsWithEmptyCells": 0
}
}
}Tags
x402
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