Convert XML to CSV in Python

XML (Extensible Markup Language) is widely used to store and transport structured data. However, for tasks like data analysis or spreadsheet editing, CSV (Comma-Separated Values) is far more user-friendly and easier to work with.

To make XML data easier to process, we often convert it to a CSV file. In this article, we will explore how to convert XML to CSV step-by-step with the help of the built-in xml.etree.ElementTree module and the powerful pandas library.

Approach

• Import necessary libraries.
• Define the desired column headers.
• Parse the XML file.
• Extract the relevant data.
• Store it into a pandas DataFrame.
• Export the DataFrame to a CSV file.

To download the XML data used in the examples, click here.

Example

Python Program to Convert XML to CSV.

# Importing the required libraries
import xml.etree.ElementTree as Xet
import pandas as pd

cols = ["name", "phone", "email", "date", "country"]
rows = []

# Parsing the XML file
xmlparse = Xet.parse(r'psth_to_sample.xml')
root = xmlparse.getroot()
for i in root:
    name = i.find("name").text
    phone = i.find("phone").text
    email = i.find("email").text
    date = i.find("date").text
    country = i.find("country").text

    rows.append({"name": name,
                 "phone": phone,
                 "email": email,
                 "date": date,
                 "country": country})

df = pd.DataFrame(rows, columns=cols)

# Writing dataframe to csv
df.to_csv('output.csv')

Output:

Code Breakdown:

• We used ElementTree to parse and navigate through the XML structure.
• Data from each record was collected into a list of dictionaries.
• Finally, we used pandas to create a CSV file from that structured data.

To learn about the pandas module in depth, refer to: Python Pandas Tutorial