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Formateadores y código

CSV → Conjunto de Datos JSON

CSV + inferred column metadata for ML pipelines.

Runs in your browser
JSON dataset with metadata
{
  "metadata": {
    "rowCount": 5,
    "columnCount": 6,
    "columns": [
      {
        "name": "id",
        "type": "integer",
        "nullCount": 0,
        "uniqueCount": 5
      },
      {
        "name": "name",
        "type": "string",
        "nullCount": 0,
        "uniqueCount": 5
      },
      {
        "name": "email",
        "type": "string",
        "nullCount": 0,
        "uniqueCount": 1
      },
      {
        "name": "age",
        "type": "integer",
        "nullCount": 0,
        "uniqueCount": 5
      },
      {
        "name": "active",
        "type": "boolean",
        "nullCount": 0,
        "uniqueCount": 2
      },
      {
        "name": "city",
        "type": "string",
        "nullCount": 0,
        "uniqueCount": 5
      }
    ]
  },
  "data": [
    {
      "id": 1,
      "name": "Ada",
      "email": "[email protected]",
      "age": 36,
      "active": true,
      "city": "London"
    },
    {
      "id": 2,
      "name": "Grace",
      "email": "[email protected]",
      "age": 85,
      "active": true,
      "city": "New York"
    },
    {
      "id": 3,
      "name": "Alan",
      "email": "[email protected]",
      "age": 41,
      "active": false,
      "city": "Cambridge"
    },
    {
      "id": 4,
      "name": "Linus",
      "email": "[email protected]",
      "age": 55,
      "active": true,
      "city": "Helsinki"
    },
    {
      "id": 5,
      "name": "Margaret",
      "email": "[email protected]",
      "age": 87,
      "active": true,
      "city": "Boston"
    }
  ]
}

Nota del editor

Understanding · Tabular rows into nested objects — for ML training and API responses.

Este capítulo en profundidad está disponible solo en inglés por el momento. La herramienta de conversión de arriba funciona en tu idioma; el artículo explicativo extenso aún no se ha traducido.

Preguntas frecuentes

Quick answers.

›How does the tool handle data types?

The converter checks each value to see if it represents a number or a boolean. If a column consistently contains numeric patterns, it is output as a `number` type in the JSON rather than a string.

›Does my data leave my computer?

No. The parsing and transformation logic is executed locally within your browser session. No data is sent to our servers or stored in any database.

›What happens if my CSV has no header row?

The tool assumes the first row contains labels for the JSON keys. If headers are missing, the resulting objects will use the first row of data as keys, so it is best to provide a header-first file.

›Is there a limit on file size?

The limit depends on your browser's available memory. For datasets exceeding several hundred megabytes, we recommend using a dedicated local script to avoid browser tab crashes.

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