CODEWITHSUNDEEP
pythonxmlpandasdataframe
jabba
jabba

Reputation: 513

Parsing XML document into a pandas DataFrame

I have an XML file that looks like this:

<?xml version="1.0" encoding="utf-8"?>
<comments>
<row Id="1" PostId="2" Score="0" Text="(...)" CreationDate="2011-08-30T21:15:28.063" UserId="16" />
<row Id="2" PostId="17" Score="1" Text="(...)" CreationDate="2011-08-30T21:24:56.573" UserId="27" />
<row Id="3" PostId="26" Score="0" Text="(...)" UserId="9" />
</comments>

What I'm trying to do is to extract ID, Text and CreationDate colums into pandas DF and I've tried following:

import xml.etree.cElementTree as et
import pandas as pd
path = '/.../...'
dfcols = ['ID', 'Text', 'CreationDate']
df_xml = pd.DataFrame(columns=dfcols)

root = et.parse(path)
rows = root.findall('.//row')
for row in rows:
    ID = row.find('Id')
    text = row.find('Text')
    date = row.find('CreationDate')
    print(ID, text, date)
    df_xml = df_xml.append(pd.Series([ID, text, date], index=dfcols), ignore_index=True)

print(df_xml)

But the output is:

None None None

How do I fix this?

Upvotes: 7

Views: 18138

Answers (4)

cottontail
cottontail

Reputation: 23381

Since pandas 1.3.0, there's a built-in pandas function pd.read_xml that reads XML documents into a pandas DataFrame.

path = """<?xml version="1.0" encoding="utf-8"?>
<comments>
<row Id="1" PostId="2" Score="0" Text="(...)" CreationDate="2011-08-30T21:15:28.063" UserId="16" />
<row Id="2" PostId="17" Score="1" Text="(...)" CreationDate="2011-08-30T21:24:56.573" UserId="27" />
<row Id="3" PostId="26" Score="0" Text="(...)" UserId="9" />
</comments>"""

# or a path to an XML doc
path = 'test.xml'
pd.read_xml(path)

The XML doc in the OP becomes the following by simply calling read_xml:

res

Upvotes: 0

bcosta12
bcosta12

Reputation: 2452

Based on @Parfait solution, I wrote my version that gets the columns as a parameter and returns the Pandas DataFrame.

test.xml:

<?xml version="1.0" encoding="utf-8"?>
<comments>
<row Id="1" PostId="2" Score="0" Text="(.1.)" CreationDate="2011-08-30T21:15:28.063" UserId="16" />
<row Id="2" PostId="17" Score="1" Text="(.2.)" CreationDate="2011-08-30T21:24:56.573" UserId="27" />
<row Id="3" PostId="26" Score="0" Text="(.3.)" UserId="9" />
</comments>

xml_to_pandas.py:

'''Xml to Pandas DataFrame Convertor.'''

import xml.etree.cElementTree as et
import pandas as pd


def xml_to_pandas(root, columns, row_name):
  '''get xml.etree root, the columns and return Pandas DataFrame'''
  df = None
  try:

    rows = root.findall('.//{}'.format(row_name))

    xml_data = [[row.get(c) for c in columns] for row in rows]  # NESTED LIST

    df = pd.DataFrame(xml_data, columns=columns)
  except Exception as e:
    print('[xml_to_pandas] Exception: {}.'.format(e))

  return df


path = 'test.xml'
row_name = 'row'
columns = ['ID', 'Text', 'CreationDate']

root = et.parse(path)
df = xml_to_pandas(root, columns, row_name)
print(df)

output:

enter image description here

Upvotes: 3

Parfait
Parfait

Reputation: 107747

As advised in this solution by gold member Python/pandas/numpy guru, @unutbu:

Never call DataFrame.append or pd.concat inside a for-loop. It leads to quadratic copying.

Therefore, consider parsing your XML data into a separate list then pass list into the DataFrame constructor in one call outside of any loop. In fact, you can pass nested lists with list comprehension directly into the constructor:

path = 'AttributesXMLPandas.xml'
dfcols = ['ID', 'Text', 'CreationDate']

root = et.parse(path)
rows = root.findall('.//row')

# NESTED LIST
xml_data = [[row.get('Id'), row.get('Text'), row.get('CreationDate')] 
            for row in rows]

df_xml = pd.DataFrame(xml_data, columns=dfcols)

print(df_xml)

#   ID   Text             CreationDate
# 0  1  (...)  2011-08-30T21:15:28.063
# 1  2  (...)  2011-08-30T21:24:56.573
# 2  3  (...)                     None

Upvotes: 4

Prany
Prany

Reputation: 2143

Just a minor change in your code

ID = row.get('Id')
text = row.get('Text')
date = row.get('CreationDate')

Upvotes: 3

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