将 XML 文件读取到 Pandas DataFrame

Question

有人可以帮忙将以下 XML 文件转换为 Pandas 数据帧：

<?xml version="1.0" encoding="UTF-8" ?>
<root>
 <bathrooms type="dict">
  <n35237 type="number">1.0</n35237>
  <n32238 type="number">3.0</n32238>
  <n44699 type="number">nan</n44699>
 </bathrooms>
 <price type="dict">
  <n35237 type="number">7020000.0</n35237>
  <n32238 type="number">10000000.0</n32238>
  <n44699 type="number">4128000.0</n44699>
 </price>
 <property_id type="dict">
  <n35237 type="number">35237.0</n35237>
  <n32238 type="number">32238.0</n32238>
  <n44699 type="number">44699.0</n44699>
 </property_id>
</root>

它应该是这样的 --

OUTPUT

这是我写的代码：-

import pandas as pd
import xml.etree.ElementTree as ET

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

dfcols = ['property_id', 'price', 'bathrooms']
df_xml = pd.DataFrame(columns=dfcols)

for node in root:
    property_id = node.attrib.get('property_id')
    price = node.attrib.get('price')
    bathrooms = node.attrib.get('bathrooms')

    df_xml = df_xml.append(
            pd.Series([property_id, price, bathrooms], index=dfcols),
            ignore_index=True)


print(df_xml)

我到处都得到 None，而不是实际值。有人可以告诉我如何修复它。谢谢！

Answer 1

如果数据很简单，像这样，那么你可以这样做：

from lxml import objectify
xml = objectify.parse('Document1.xml')
root = xml.getroot()

bathrooms = [child.text for child in root['bathrooms'].getchildren()]
price = [child.text for child in root['price'].getchildren()]
property_id = [child.text for child in root['property_id'].getchildren()]

data = [bathrooms, price, property_id]
df = pd.DataFrame(data).T
df.columns = ['bathrooms', 'price', 'property_id']

    bathrooms   price      property_id
0   1.0        7020000.0    35237.0
1   3.0        10000000.0   32238.0
2   nan        4128000.0    44699.0

如果它更复杂，那么循环更好。你可以这样做

from lxml import objectify
xml = objectify.parse('Document1.xml')
root = xml.getroot()

data=[]
for i in range(len(root.getchildren())):
    data.append([child.text for child in root.getchildren()[i].getchildren()])

df = pd.DataFrame(data).T
df.columns = ['bathrooms', 'price', 'property_id']

Answer 2

我已经成功地使用了 xmltodict 包中的这个函数：

import xmltodict

xmlDict = xmltodict.parse(xmlData)
df = pd.DataFrame.from_dict(xmlDict)

我喜欢这个的一点是，我可以在解析 xml 和制作我的 df 之间轻松地进行一些字典操作。此外，如果结构巧妙，它有助于将数据作为字典来探索。

Answer 3

大家好，我找到了另一种非常简单的方法来解决这些问题。参考：https://www.youtube.com/watch?v=WVrg5-cjr5k

import xml.etree.ElementTree as ET
import pandas as pd
import codecs

## open notebook and save your xml file to text.xml 
with codecs.open('text.xml', 'r', encoding='utf8') as f:
    tt = f.read()


def xml2df(xml_data):
    root = ET.XML(xml_data)
    all_records = []
    for i, child in enumerate(root):
        record = {}
        for sub_child in child:
            record[sub_child.tag] = sub_child.text
        all_records.append(record)
    return pd.DataFrame(all_records)


df_xml1 = xml2df(tt)
print(df_xml1)

为了更好地理解 ET，您可以使用下面的代码来查看 xml

的内容

import xml.etree.ElementTree as ET
import pandas as pd
import codecs
with codecs.open('text.xml', 'r', encoding='utf8') as f:
    tt = f.read()

root = ET.XML(tt)

print(type(root))
print(root[0])
for ele in root[0]:
    print(ele.tag + '////' + ele.text)

print(root[0][0].tag)

完成运行程序后，您可以在下面看到输出：

C:\Users\username\Documents\pycode\Scripts\python.exe C:/Users/username/PycharmProjects/DestinationLight/try.py
      n35237      n32238     n44699
0        1.0         3.0        nan
1  7020000.0  10000000.0  4128000.0
2    35237.0     32238.0    44699.0

<class 'xml.etree.ElementTree.Element'>
<Element 'bathrooms' at 0x00000285006B6180>
n35237////1.0
n32238////3.0
n44699////nan
n35237

Process finished with exit code 0

将 XML 文件读取到 Pandas DataFrame

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