Convert XML to JSON in Python

1. Sample XML File

Consider the following sample XML file, data.xml, containing structured records:

<data>
    <record>
        <id>1</id>
        <name>John Doe</name>
        <age>30</age>
        <city>New York</city>
    </record>
    <record>
        <id>2</id>
        <name>Jane Smith</name>
        <age>25</age>
        <city>Los Angeles</city>
    </record>
    <record>
        <id>3</id>
        <name>Emily Davis</name>
        <age>35</age>
        <city>Chicago</city>
    </record>
</data>

2. Using Pandas `read_xml()` to Convert XML to JSON

The Pandas library provides the read_xml() method to parse XML data into a DataFrame effortlessly, which can then be exported as a JSON file using to_json().

Code Example

import pandas as pd

# Input and output file paths
input_file = 'data.xml'
output_file = 'data.json'

# Read the XML file into a Pandas DataFrame
df = pd.read_xml(input_file)

# Export the DataFrame to a JSON file
df.to_json(output_file, orient='records', indent=4)

# Output confirmation
print(f"Data exported to {output_file} successfully.")

Explanation:

• pd.read_xml(): Parses the XML file and loads it into a DataFrame.
• df.to_json(): Exports the DataFrame to a JSON file.
• orient='records': Converts rows of the DataFrame into a list of dictionaries.
• indent=4: Pretty-prints the JSON with an indentation of 4 spaces.

3. Using ElementTree and JSON Modules

The ElementTree module, part of Python’s standard library, allows you to parse XML files iteratively and serialize data using the built-in json module.

Code Example

import xml.etree.ElementTree as ET
import json

# Input and output file paths
input_file = 'data.xml'
output_file = 'data.json'

# Parse the XML file
tree = ET.parse(input_file)
root = tree.getroot()

# Extract data from XML
records = []

# Iterate through records
for record in root.findall('record'):
    data = {}
    for element in record:
        data[element.tag] = element.text
    records.append(data)

# Write data to JSON
with open(output_file, 'w', encoding='utf-8') as json_file:
    json.dump(records, json_file, indent=4)

print(f"Data exported to {output_file} successfully.")

Explanation:

• ET.parse(): Parses the XML file and creates an ElementTree structure.
• root.findall('record'): Locates all <record> elements within the XML document.
• json.dump(): Converts Python objects into a pretty-printed JSON file.

4. Comparison of Methods

5. Which Method Should You Use?

Use Pandas `read_xml()` when working on data science pipelines where Pandas is already imported and the XML structure is relatively flat.

Use ElementTree when building lightweight scripts that avoid heavy third-party dependencies or require custom data transformations during conversion.

Conclusion

Both methods are highly effective for converting XML to JSON in Python. Choose the approach that best fits your project environment and data complexity.

Data Import Export using Tkinter GUI and Pandas DataFrame →

Interactive Notebook & Practice Exercises

Practice converting XML to JSON in our companion Jupyter Notebook:

Interactive Companion Jupyter Notebook

Explore interactive code cells and test converting XML files to JSON using both Pandas and ElementTree.

View on GitHub

Subhendu Mohapatra

Author & Instructor at plus2net

I write and maintain practical tutorials on Python, PHP, SQL, JavaScript, HTML, jQuery, and web development at plus2net. The tutorials focus on clear explanations, working examples, and code that readers can test and adapt while learning.

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