数据与电子表格
模拟数据生成器
生成逼真的伪造数据 — 姓名、邮箱、地址、UUID、日期和自定义字段 — 并导出为 JSON、CSV 或 SQL INSERT 语句
Fields (6)
Add field:
Preview (first 5 rows)
| id | first_name | last_name | city | age | |
|---|---|---|---|---|---|
| 1 | Amy | Campbell | sharon.hernandez16@test.io | Madison | 79 |
| 2 | Amy | Rodriguez | lisa.hernandez67@placeholder.co | Kingston | 19 |
| 3 | Barbara | Clark | mary.green54@dummy.email | Milford | 39 |
| 4 | Elizabeth | Campbell | brandon.davis44@test.io | Springfield | 62 |
| 5 | Stephanie | Martin | maria.nguyen12@fakeapi.com | Salem | 48 |
Output (JSON · 25 rows)
[
{
"id": 1,
"first_name": "Amy",
"last_name": "Campbell",
"email": "sharon.hernandez16@test.io",
"city": "Madison",
"age": 79
},
{
"id": 2,
"first_name": "Amy",
"last_name": "Rodriguez",
"email": "lisa.hernandez67@placeholder.co",
"city": "Kingston",
"age": 19
},
{
"id": 3,
"first_name": "Barbara",
"last_name": "Clark",
"email": "mary.green54@dummy.email",
"city": "Milford",
"age": 39
},
{
"id": 4,
"first_name": "Elizabeth",
"last_name": "Campbell",
"email": "brandon.davis44@test.io",
"city": "Springfield",
"age": 62
},
{
"id": 5,
"first_name": "Stephanie",
"last_name": "Martin",
"email": "maria.nguyen12@fakeapi.com",
"city": "Salem",
"age": 48
},
{
"id": 6,
"first_name": "Katherine",
"last_name": "Wright",
"email": "michelle.roberts86@sample.org",
"city": "Milton",
"age": 76
},
{
"id": 7,
"first_name": "Ruth",
"last_name": "Anderson",
"email": "gregory.flores36@fakeapi.com",
"city": "Kingston",
"age": 34
},
{
"id": 8,
"first_name": "Brian",
"last_name": "Jones",
"email": "betty.lee26@demo.net",
"city": "Arlington",
"age": 69
},
{
"id": 9,
"first_name": "Nicole",
"last_name": "Hernandez",
"email": "elizabeth.lewis79@mock.dev",
"city": "Milford",
"age": 20
},
{
"id": 10,
"first_name": "Carol",
"last_name": "Scott",
"email": "dorothy.martinez6@test.io",
"city": "Madison",
"age": 65
},
{
"id": 11,
"first_name": "Scott",
"last_name": "Roberts",
"email": "ruth.rodriguez88@test.io",
"city": "Madison",
"age": 58
},
{
"id": 12,
"first_name": "Lisa",
"last_name": "Lee",
"email": "ashley.gonzalez56@demo.net",
"city": "Riverside",
"age": 30
},
{
"id": 13,
"first_name": "Samuel",
"last_name": "Lee",
"email": "jacob.martinez42@test.io",
"city": "Georgetown",
"age": 31
},
{
"id": 14,
"first_name": "Margaret",
"last_name": "Nguyen",
"email": "helen.scott54@test.io",
"city": "Hudson",
"age": 19
},
{
"id": 15,
"first_name": "Maria",
"last_name": "Walker",
"email": "michelle.clark44@fakeapi.com",
"city": "Newport",
"age": 70
},
{
"id": 16,
"first_name": "Brian",
"last_name": "White",
"email": "samantha.thomas48@sample.org",
"city": "Riverside",
"age": 59
},
{
"id": 17,
"first_name": "Brandon",
"last_name": "Wright",
"email": "daniel.jackson91@mock.dev",
"city": "Richmond",
"age": 59
},
{
"id": 18,
"first_name": "Michelle",
"last_name": "Campbell",
"email": "brandon.martinez65@example.com",
"city": "Lexington",
"age": 65
},
{
"id": 19,
"first_name": "Richard",
"last_name": "Young",
"email": "james.clark20@sample.org",
"city": "Kingston",
"age": 43
},
{
"id": 20,
"first_name": "Laura",
"last_name": "Miller",
"email": "laura.jackson30@demo.net",
"city": "Arlington",
"age": 71
},
{
"id": 21,
"first_name": "Barbara",
"last_name": "Jones",
"email": "maria.torres17@sample.org",
"city": "Marion",
"age": 65
},
{
"id": 22,
"first_name": "Rachel",
"last_name": "Martin",
"email": "daniel.nguyen13@fakeapi.com",
"city": "Bristol",
"age": 64
},
{
"id": 23,
"first_name": "Timothy",
"last_name": "Hernandez",
"email": "larry.gonzalez72@dummy.email",
"city": "Clinton",
"age": 62
},
{
"id": 24,
"first_name": "Michelle",
"last_name": "Anderson",
"email": "brian.johnson35@placeholder.co",
"city": "Lexington",
"age": 44
},
{
"id": 25,
"first_name": "Patricia",
"last_name": "Davis",
"email": "christine.king3@placeholder.co",
"city": "Springfield",
"age": 71
}
]继续探索
您可能喜欢的其他 数据与电子表格…
CSV 查看与编辑器
以交互式表格查看、排序、筛选和检查 CSV 文件——全部在浏览器中完成
立即试用
JSON 表格查看器
将 JSON 对象数组渲染为可排序、可搜索的 HTML 表格,支持列筛选
立即试用
Excel 转 CSV
将 XLSX 和 XLS Excel 文件转换为 CSV 格式——无需上传,通过 SheetJS 在浏览器中运行
立即试用
CSV 列提取器
从 CSV 文件中选取特定列并下载结果——非常适合清理大型数据集
立即试用
SQL 查询 CSV
直接在上传的 CSV 文件上运行 SQL SELECT 查询——无需服务器
立即试用
CSV 合并工具
将多个 CSV 文件合并为一个——重新排序、去重并自动处理表头
立即试用
CSV Splitter
Split a large CSV file into smaller files by row count or by unique values in a column
立即试用
JSON 转 Excel
将 JSON 对象数组转换为 Excel (.xlsx) 或 CSV——由 SheetJS 驱动,在浏览器中运行
立即试用