如何将XML文件转换为漂亮的pandas数据帧？
如何将XML文件转换为漂亮的pandas数据帧？
提问于 2015-02-01 11:58:54
让我们假设我有一个这样的XML：
<author type="XXX" language="EN" gender="xx" feature="xx" web="foobar.com">
<documents count="N">
<document KEY="e95a9a6c790ecb95e46cf15bee517651" web="www.foo_bar_exmaple.com"><![CDATA[A large text with lots of strings and punctuations symbols [...]
]]>
</document>
<document KEY="bc360cfbafc39970587547215162f0db" web="www.foo_bar_exmaple.com"><![CDATA[A large text with lots of strings and punctuations symbols [...]
]]>
</document>
<document KEY="19e71144c50a8b9160b3f0955e906fce" web="www.foo_bar_exmaple.com"><![CDATA[A large text with lots of strings and punctuations symbols [...]
]]>
</document>
<document KEY="21d4af9021a174f61b884606c74d9e42" web="www.foo_bar_exmaple.com"><![CDATA[A large text with lots of strings and punctuations symbols [...]
]]>
</document>
<document KEY="28a45eb2460899763d709ca00ddbb665" web="www.foo_bar_exmaple.com"><![CDATA[A large text with lots of strings and punctuations symbols [...]
]]>
</document>
</documents>
</author>我想读取这个XML文件，并将其转换为pandas DataFrame：
key type language feature web data
e95324a9a6c790ecb95e46cf15bE232ee517651 XXX EN xx www.foo_bar_exmaple.com A large text with lots of strings and punctuations symbols [...]
bc360cfbafc39970587547215162f0db XXX EN xx www.foo_bar_exmaple.com A large text with lots of strings and punctuations symbols [...]
19e71144c50a8b9160b3cvdf2324f0955e906fce XXX EN xx www.foo_bar_exmaple.com A large text with lots of strings and punctuations symbols [...]
21d4af9021a174f61b8erf284606c74d9e42 XXX EN xx www.foo_bar_exmaple.com A large text with lots of strings and punctuations symbols [...]
28a45eb2460823499763d70vdf9ca00ddbb665 XXX EN xx www.foo_bar_exmaple.com A large text with lots of strings and punctuations symbols [...]这是我已经尝试过的，但我得到了一些错误，可能有一种更有效的方法来完成这项任务：
from lxml import objectify
import pandas as pd
path = 'file_path'
xml = objectify.parse(open(path))
root = xml.getroot()
root.getchildren()[0].getchildren()
df = pd.DataFrame(columns=('key','type', 'language', 'feature', 'web', 'data'))
for i in range(0,len(xml)):
obj = root.getchildren()[i].getchildren()
row = dict(zip(['key','type', 'language', 'feature', 'web', 'data'], [obj[0].text, obj[1].text]))
row_s = pd.Series(row)
row_s.name = i
df = df.append(row_s)有没有人能为我提供一个更好的解决这个问题的方法？
回答 5
Stack Overflow用户
回答已采纳
发布于 2015-02-02 04:08:37
您可以很容易地使用xml (来自Python标准库)来转换为pandas.DataFrame。下面是我要做的(从文件读取时，将xml_data替换为您的文件或文件对象的名称)：
import pandas as pd
import xml.etree.ElementTree as ET
import io
def iter_docs(author):
author_attr = author.attrib
for doc in author.iter('document'):
doc_dict = author_attr.copy()
doc_dict.update(doc.attrib)
doc_dict['data'] = doc.text
yield doc_dict
xml_data = io.StringIO(u'''YOUR XML STRING HERE''')
etree = ET.parse(xml_data) #create an ElementTree object
doc_df = pd.DataFrame(list(iter_docs(etree.getroot())))如果您的原始文档中有多个作者，或者您的XML的根不是author，那么我将添加以下生成器：
def iter_author(etree):
for author in etree.iter('author'):
for row in iter_docs(author):
yield row并将doc_df = pd.DataFrame(list(iter_docs(etree.getroot())))更改为doc_df = pd.DataFrame(list(iter_author(etree)))
看看ElementTree库documentation中提供的xml tutorial。
Stack Overflow用户
发布于 2021-03-25 16:24:25
从v1.3开始，您可以简单地使用：
pandas.read_xml(path_or_file)Stack Overflow用户
发布于 2018-05-29 14:57:05
这是将xml转换为pandas数据帧的另一种方法。例如，我需要从一个字符串解析xml，但是这个逻辑也适用于读取文件。
import pandas as pd
import xml.etree.ElementTree as ET
xml_str = '<?xml version="1.0" encoding="utf-8"?>\n<response>\n <head>\n <code>\n 200\n </code>\n </head>\n <body>\n <data id="0" name="All Categories" t="2018052600" tg="1" type="category"/>\n <data id="13" name="RealEstate.com.au [H]" t="2018052600" tg="1" type="publication"/>\n </body>\n</response>'
etree = ET.fromstring(xml_str)
dfcols = ['id', 'name']
df = pd.DataFrame(columns=dfcols)
for i in etree.iter(tag='data'):
df = df.append(
pd.Series([i.get('id'), i.get('name')], index=dfcols),
ignore_index=True)
df.head()页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/28259301
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