XML to MATLAB Converter

About XML to MATLAB Converter

Convert XML data to MATLAB code with support for multiple data structures: cell arrays, matrices, struct arrays, and tables. Perfect for data analysis, scientific computing, and importing XML data into MATLAB.

Key Features

• Automatic Parsing: Intelligently extracts tabular data from XML structure
• Multiple Formats: Cell array, matrix, struct array, and table formats
• Type Detection: Automatically detects numeric vs. string data
• Header Support: Optional header row handling
• String Escaping: Properly escapes single quotes in strings
• Attribute Support: Includes XML attributes as columns (prefixed with @)

How to Use

1. Input XML Data: Paste your XML data or upload an .xml file
2. Select Format: Choose the desired MATLAB data structure
3. Configure Options: Toggle header inclusion
4. Copy or Download: Copy the code or download as .m file
5. Run in MATLAB: Execute the code in MATLAB or Octave

Output Formats

1. Cell Array

Flexible format that can hold mixed data types:

data = {
  'id', 'name', 'age'
  '1', 'John Doe', '28'
  '2', 'Jane Smith', '34'
};

2. Matrix (Numeric)

Efficient format for numeric data only:

data = [
  1, 28, 75000
  2, 34, 82000
  3, 45, 95000
];

3. Struct Array

Named fields for structured data access:

data(1) = struct(...
  'id', 1, ...
  'name', 'John Doe', ...
  'age', 28);
data(2) = struct(...
  'id', 2, ...
  'name', 'Jane Smith', ...
  'age', 34);

4. Table (R2013b+)

Modern table format with named columns:

id = [1; 2; 3];
name = {'John Doe'; 'Jane Smith'; 'Bob Johnson'};
age = [28; 34; 45];

data = table(id, name, age);

Example Conversion

XML Input:

<?xml version="1.0"?>
<employees>
  <employee>
    <id>1</id>
    <name>John Doe</name>
    <age>28</age>
  </employee>
  <employee>
    <id>2</id>
    <name>Jane Smith</name>
    <age>34</age>
  </employee>
</employees>

MATLAB Output (Cell Array):

% Cell array with headers
data = {
  'id', 'name', 'age'
  '1', 'John Doe', '28'
  '2', 'Jane Smith', '34'
};

% Access headers: data(1,:)
% Access data: data(2:end,:)

Format Comparison

• Cell Array: Most flexible, handles mixed types, easy to use
• Matrix: Fastest for numeric operations, requires all numeric data
• Struct Array: Named field access, good for complex data
• Table: Modern, supports mixed types, best for data analysis

Supported XML Structures

• Repeating Elements: Automatically detects common record names (row, record, item, entry, employee, product, user)
• Nested Elements: Extracts child element values as columns
• Attributes: Includes XML attributes as columns (prefixed with @)
• Mixed Content: Handles various XML structures intelligently

Common Use Cases

• Data Analysis: Import XML data for statistical analysis
• Scientific Computing: Process experimental data from XML
• Simulation: Load configuration and parameters from XML
• Visualization: Import data for plotting and graphing
• Machine Learning: Prepare datasets from XML sources
• Signal Processing: Import time-series data

MATLAB Tips

• Cell Array Access: Use data{row,col} for cell contents
• Matrix Operations: Use standard matrix operations (+, *, etc.)
• Struct Access: Use data(idx).fieldname or {data.fieldname}
• Table Operations: Use data.VariableName or data{:,col}
• Type Conversion: Use cell2mat(), str2double(), etc. as needed

Compatibility

• MATLAB: All versions (Table format requires R2013b+)
• GNU Octave: Compatible with cell, matrix, and struct formats
• Scilab: Cell and matrix formats with minor syntax adjustments

Privacy & Security

All conversions happen locally in your browser. Your XML data is never uploaded to any server, ensuring complete privacy and security.