フォーマッター＆コード
CSV → JSONデータセット
CSV + inferred column metadata for ML pipelines.
{
"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"
}
]
}編集者注
Understanding · Tabular rows into nested objects — for ML training and API responses.
この詳細な解説章は現在、英語版のみで提供されています。上の変換ツールはあなたの言語で動作しますが、長文の解説記事はまだ翻訳されていません。
よくある質問
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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