Pandas read_xml(): Import XML Data into a DataFrame

Basic Example

import pandas as pd
df = pd.read_xml('E:\\testing\\data\\student.xml', parser='etree')
print(df.head())

   id        name   class mark  gender
0   1    John Deo   Four    75  female
1   2    Max Ruin  Three    85    male
2   3      Arnold  Three    55    male
3   4  Krish Star   Four    60  female
4   5   John Mike   Four    60  female

Attributes of read_xml()

Using XPath

df = pd.read_xml('student.xml', xpath='.//Row')
print(df)

   id       name    class  mark  gender
0   1    John Deo   Four    75  female
1   2    Max Ruin  Three    85    male
2   3      Arnold  Three    55    male
3   4  Krish Star   Four    60  female
4   5   John Mike   Four    60  female

Including Attributes

from lxml import etree
import pandas as pd

# Parse the XML file
tree = etree.parse('student.xml')

# Extract data from <Row> elements
students = []
for row in tree.xpath('.//Row'):  # Select all <Row> nodes
    students.append({
        'id': row.findtext('id'),         # Extract the text of <id>
        'class': row.findtext('class')   # Extract the text of <class>
    })

# Convert the extracted data to a DataFrame
df = pd.DataFrame(students)

print(df)

   id   class
0   1   Four
1   2  Three
2   3  Three
3   4   Four
4   5   Four

Using attrs_only to Extract Only Attributes

import pandas as pd

# Example XML with attributes and text content
xml_data = '''
<Students>
    <Student id="1" name="John Deo" class="Four">Passed</Student>
    <Student id="2" name="Max Ruin" class="Three">Failed</Student>
    <Student id="3" name="Arnold" class="Three">Passed</Student>
</Students>
'''


# Reading XML with attrs_only=True
df_attrs_only = pd.read_xml(xml_data, parser='etree', attrs_only=True)
print("With attrs_only=True:")
print(df_attrs_only)


# Reading XML without attrs_only (default behavior)
df_default = pd.read_xml(xml_data, parser='etree')
print("\nWithout attrs_only (default):")
print(df_default)

   id       name   class
0   1   John Deo    Four
1   2   Max Ruin   Three
2   3     Arnold   Three

   id       name   class   Student
0   1   John Deo    Four    Passed
1   2   Max Ruin   Three    Failed
2   3     Arnold   Three    Passed

Explanation:

• XML Structure: Each <Student> element contains attributes (id, name, class) and text content (Passed or Failed).
• With attrs_only=True:
  • Only the attributes (id, name, class) are included in the DataFrame.
  • The text content (Passed or Failed) is ignored.
• Without attrs_only:
  • Both the attributes and the text content are included.
  • The text content is added to a new column named after the XML element (Student).
• Use Case: Use attrs_only=True when the text content of XML nodes is not relevant, and only the attributes are needed.

Using namespaces to Handle Namespaced XML

import pandas as pd

# Example XML with namespaces
xml_data = '''
<ns:Students xmlns:ns="http://example.com/ns">
    <ns:Student id="1" name="John Deo" class="Four">Passed</ns:Student>
    <ns:Student id="2" name="Max Ruin" class="Three">Failed</ns:Student>
    <ns:Student id="3" name="Arnold" class="Three">Passed</ns:Student>
</ns:Students>
'''


# Define the namespace
namespaces = {"ns": "http://example.com/ns"}

# Reading XML with the namespace
df = pd.read_xml(xml_data, xpath=".//ns:Student", namespaces=namespaces)
print(df)

   id       name   class Student
0   1   John Deo    Four  Passed
1   2   Max Ruin   Three  Failed
2   3     Arnold   Three  Passed

Explanation:

• XML with Namespace:
  • The XML uses the namespace prefix ns with the URI http://example.com/ns.
  • Elements like <ns:Student> and <ns:Students> are namespaced.
• Defining the Namespace:
  • The namespaces parameter is a dictionary where keys are prefixes (e.g., ns) and values are their respective URIs (e.g., http://example.com/ns).
• Using XPath with Namespace:
  • Use the xpath parameter with the namespace prefix (e.g., .//ns:Student) to target specific elements.
• Output:
  • The resulting DataFrame includes attributes (id, name, class) and text content (Passed or Failed).

Handling Nested XML

` tag, `read_xml()` can parse these nested elements:

import pandas as pd
df = pd.read_xml('nested_student.xml')
print(df)

### Output:

   id         name  marks.score1  marks.score2
0   1    John Deo           75.0           NaN
1   2    Max Ruin           85.0          80.0
2   3      Arnold           55.0          90.0

---

Questions

1. What is the purpose of the read_xml() function in Pandas?
2. How can you use XPath to extract specific nodes from an XML file?
3. What are some common attributes of the read_xml() function?
4. Provide an example of reading XML data with specific attributes.
5. What is the purpose of the attrs_only attribute in read_xml()?
6. In which scenarios would you use attrs_only=True?
7. Provide an example where XML nodes contain both attributes and text. What changes in the DataFrame when attrs_only is used?
8. How does the attrs_only attribute help in simplifying XML data extraction?
9. What is the purpose of the namespaces parameter in read_xml()?
10. Provide an example of reading XML with namespaces using read_xml().
11. How does the xpath parameter work in conjunction with namespaces?
12. Why is defining namespaces important when working with namespaced XML?

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Subhendu Mohapatra

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