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XML data cleaning technology in Python

Aug 07, 2023 pm 03:57 PM
pythonxmlData cleaning

XML data cleaning technology in Python

XML data cleaning technology in Python

Introduction:
With the rapid development of the Internet, the speed of data generation is also getting faster and faster. As a widely used data exchange format, XML (Extensible Markup Language) plays an important role in various fields. However, due to the complexity and diversity of XML data, effective cleaning and processing of large amounts of XML data has become a very challenging task. Fortunately, Python provides some powerful libraries and tools that make it easy to clean and process XML data.

1. Reading XML data
In Python, we can use the xml module to read XML data. XML data can be stored in a file or passed to the program as a string variable.

The following is a sample code for reading an XML file:

import xml.etree.ElementTree as ET

tree = ET.parse('data.xml')
root = tree.getroot()

Through the above code, we successfully read the contents of the XML file into memory and set the root element Saved in the variable root.

2. Traversing and parsing XML data
Once we successfully read the XML data into memory, we can use the methods provided by the ElementTree module to traverse and parse the XML data.

For example, suppose we have an XML file as shown below:

<library>
    <book>
        <title>Python编程入门</title>
        <author>张三</author>
        <price>29.99</price>
    </book>
    <book>
        <title>Java从入门到精通</title>
        <author>李四</author>
        <price>39.99</price>
    </book>
</library>

We can use the following code to traverse and parse the XML data:

for book in root.findall('book'):
    title = book.find('title').text
    author = book.find('author').text
    price = book.find('price').text
    
    print("书名: ", title)
    print("作者: ", author)
    print("价格: ", price)
    print()

With the above code, we can sequentially Get the title, author, and price of each book and print it out.

3. Cleaning and processing of XML data
Let’s take a look at how to use Python to clean and process XML data.

3.1 Delete nodes
Sometimes we may need to delete certain nodes in XML. For example, if we don't want to display the price of a certain book, we can delete the price node.

The following is a sample code for deleting nodes:

for book in root.findall('book'):
    price = book.find('price')
    book.remove(price)

tree.write('cleaned_data.xml')

With the above code, we successfully deleted the price nodes of all books from the XML data and saved the processed data to cleaned_data .xml file.

3.2 Modify nodes
In addition to deleting nodes, we can also modify nodes in XML data.

For example, if we want to change the author of the book "Introduction to Python Programming" to Wang Wu, we can use the following code to achieve it:

for book in root.findall('book'):
    title = book.find('title')
    if title.text == "Python编程入门":
        author = book.find('author')
        author.text = "王五"

tree.write('modified_data.xml')

Through the above code, we successfully put the XML data into The author of the book "Introduction to Python Programming" was modified to Wang Wu and the processed data was saved in the modified_data.xml file.

4. Summary
Python provides a wealth of libraries and tools, allowing us to easily clean and process XML data. This article introduces how to use the xml module and ElementTree module to read, traverse, parse, clean and process XML data, and gives corresponding code examples. It is hoped that these techniques can help readers better handle XML data and play a role in actual data cleaning and processing tasks.

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