How to Use the Batch Data Converter

1.

Use the top textarea to paste or type your data.
You can enter raw text, table data, or structured content.

Supported formats include CSV, TSV, JSON, Excel-style rows/columns, HTML, Markdown, SQL, XML, YAML, and more (see examples below).
The converter will try to automatically detect and parse your data format.

Upload Files or Folders

Drag and drop a file or folder into the upload area, or click it to browse your files. The contents will be automatically parsed and loaded into the input area. Note: Only one file’s content will be shown in the textarea at a time, but when you click ‘Download,’ all your files will be saved together in a single .zip archive.

You can upload multiple files or an entire folder.
Click the “X” button in the upload area to clear all uploaded files.

2. Choose Input Format

Select the format of your input data from the first dropdown menu. This helps the converter parse your data correctly.

3. Choose Output Format

From the second dropdown, select the format you want to convert your data into (e.g., JSON, HTML, CSV). The output area will update automatically.

4. Convert the Data

Click the “Convert” button to transform your input into the selected output format.

5. Download Converted File

Click the “Download” button to save your converted data in the chosen format.

Notes

The converter tries to preserve table structure and formatting when switching between formats.
For the best results, make sure your data is well-structured and matches the selected input format.

Input / Output Examples

Simple data example contains flat structures with only key-value pairs and no nested objects or arrays. It is compatible with all data formats.

Complex data example includes nested structures such as objects within objects and arrays, representing hierarchical relationships. This format requires data formats that support nesting, like JSON or XML, and is not compatible with flat formats such as CSV.

CSV

Simple data:

Name,Age,Country
James,30,France
Claude,25,Japan
Nana,7,Canada

Excel-style (Column tab-separated)

Simple data:

Name	Age	Country
James	30	France
Claude	25	Japan
Nana	7	Canada

Excel-style (Row tab-separated)

Simple data:

Name	James	Claude	Nana
Age	30	25	7
Country	France	Japan	Canada

HTML Table

Simple data:

<table>
  <thead>
    <tr><th>Name</th><th>Age</th><th>Country</th></tr>
  </thead>
  <tbody>
    <tr><td>James</td><td>30</td><td>France</td></tr>
    <tr><td>Claude</td><td>25</td><td>Japan</td></tr>
    <tr><td>Nana</td><td>7</td><td>Canada</td></tr>
  </tbody>
</table>

JSON

Simple data:

[
  { "Name": "James", "Age": 30, "Country": "France" },
  { "Name": "Claude", "Age": 25, "Country": "Japan" },
  { "Name": "Nana", "Age": 7, "Country": "Canada" }
]

Complex data:

{
  "people": [
    {
      "Name": "James",
      "Age": 30,
      "Country": "France",
      "Hobbies": ["reading", "cycling", "cooking"],
      "Education": {
        "highest_degree": "Master's",
        "fields": ["Literature", "Philosophy"]
      },
      "Work": {
        "occupation": "Engineer",
        "skills": ["JavaScript", "Python", "Project Management"]
      }
    },
    {
      "Name": "Claude",
      "Age": 25,
      "Country": "Japan",
      "Hobbies": ["gaming", "traveling"],
      "Education": {
        "highest_degree": "Bachelor's",
        "fields": ["Computer Science"]
      },
      "Work": {
        "occupation": "Designer",
        "skills": ["Photoshop", "Illustrator", "UX/UI"]
      }
    },
    {
      "Name": "Nana",
      "Age": 7,
      "Country": "Canada",
      "Hobbies": ["drawing", "swimming"],
      "Education": {
        "school": "Elementary School",
        "grades": {
          "math": "A",
          "science": "B+"
        }
      }
    }
  ]
}

LaTeX Table

Simple data:

\begin{tabular}{|l|c|l|}
\hline
Name & Age & Country \\
\hline
James & 30 & France \\
Claude & 25 & Japan \\
Nana & 7 & Canada \\
\hline
\end{tabular}

Markdown Table

Simple data:

| Name   | Age | Country |
|--------|-----|---------|
| James  | 30  | France  |
| Claude | 25  | Japan   |
| Nana    | 7  | Canada  |

Pdf

Upload your file.

SQL Insert

Simple data:

INSERT INTO people (Name, Age, Country) VALUES
('James', 30, 'France'),
('Claude', 25, 'Japan'),
('Nana', 7, 'Canada');

TSV

Simple data:

Name	Age	Country
James	30	France
Claude	25	Japan
Nana	7	Canada

Excel (XLS)

Simple data:

<table>
  <thead>
    <tr><th>Name</th><th>Age</th><th>Country</th></tr>
  </thead>
  <tbody>
    <tr><td>James</td><td>30</td><td>France</td></tr>
    <tr><td>Claude</td><td>25</td><td>Japan</td></tr>
    <tr><td>Nana</td><td>7</td><td>Canada</td></tr>
  </tbody>
</table>

Excel (XLSX)

Upload your file.

XML

Simple data:

<?xml version="1.0" encoding="UTF-8"?>
<people>
  <person><Name>James</Name><Age>30</Age><Country>France</Country></person>
  <person><Name>Claude</Name><Age>25</Age><Country>Japan</Country></person>
  <person><Name>Nana</Name><Age>7</Age><Country>Canada</Country></person>
</people>

Complex data:

<?xml version="1.0" encoding="UTF-8"?>
<root>
  <people>
    <Name>James</Name>
    <Age>30</Age>
    <Country>France</Country>
    <Hobbies>reading</Hobbies>
    <Hobbies>cycling</Hobbies>
    <Hobbies>cooking</Hobbies>
    <Education>
      <highest_degree>Master&apos;s</highest_degree>
      <fields>Literature</fields>
      <fields>Philosophy</fields>
    </Education>
    <Work>
      <occupation>Engineer</occupation>
      <skills>JavaScript</skills>
      <skills>Python</skills>
      <skills>Project Management</skills>
    </Work>
  </people>
  <people>
    <Name>Claude</Name>
    <Age>25</Age>
    <Country>Japan</Country>
    <Hobbies>gaming</Hobbies>
    <Hobbies>traveling</Hobbies>
    <Education>
      <highest_degree>Bachelor&apos;s</highest_degree>
      <fields>Computer Science</fields>
    </Education>
    <Work>
      <occupation>Designer</occupation>
      <skills>Photoshop</skills>
      <skills>Illustrator</skills>
      <skills>UX/UI</skills>
    </Work>
  </people>
  <people>
    <Name>Nana</Name>
    <Age>7</Age>
    <Country>Canada</Country>
    <Hobbies>drawing</Hobbies>
    <Hobbies>swimming</Hobbies>
    <Education>
      <school>Elementary School</school>
      <grades>
        <math>A</math>
        <science>B+</science>
      </grades>
    </Education>
  </people>
</root>

YAML

Simple data:

- Name: James
  Age: 30
  Country: France
- Name: Claude
  Age: 25
  Country: Japan
- Name: Nana
  Age: 7
  Country: Canada

Complex data:

people:
  - Name: James
    Age: 30
    Country: France
    Hobbies:
      - reading
      - cycling
      - cooking
    Education:
      highest_degree: "Master's"
      fields:
        - Literature
        - Philosophy
    Work:
      occupation: Engineer
      skills:
        - JavaScript
        - Python
        - Project Management
  - Name: Claude
    Age: 25
    Country: Japan
    Hobbies:
      - gaming
      - traveling
    Education:
      highest_degree: "Bachelor's"
      fields:
        - Computer Science
    Work:
      occupation: Designer
      skills:
        - Photoshop
        - Illustrator
        - UX/UI
  - Name: Nana
    Age: 7
    Country: Canada
    Hobbies:
      - drawing
      - swimming
    Education:
      school: Elementary School
      grades:
        math: A
        science: B+