A有一个如下所示的XML文件:
<?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>
我正在尝试做的是将ID、文本和CreationDate列提取到pandas DF中,我尝试了以下几种方法:
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)
但是输出是: None None None
你能告诉我怎么解决这个问题吗?谢谢
发布于 2018-06-09 20:41:43
只需对代码稍作修改即可
ID = row.get('Id')
text = row.get('Text')
date = row.get('CreationDate')
发布于 2019-11-28 00:28:24
基于@Parfait解决方案,我编写了我的版本,将列作为参数获取并返回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)
输出:
https://stackoverflow.com/questions/50774222
复制相似问题