Python 如何将熊猫/数据帧转换为 XML？
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How do convert a pandas/dataframe to XML?
提问by user7289
is there a simple way to take a pandas/df table:
有没有一种简单的方法来获取 pandas/df 表：
field_1 field_2 field_3 field_4
cat 15,263 2.52 00:03:00
dog 1,652 3.71 00:03:47
test 312 3.27 00:03:41
book 300 3.46 00:02:40
And convert it to XML along the lines of:
并按照以下方式将其转换为 XML：
<item>
<field name="field_1">cat</field>
<field name="field_2">15263</field>
<field name="filed_3">2.52</field>
...
<item>
<field name="field_1">dog</field>
and so on...
Thanks in advance for any help.
在此先感谢您的帮助。
采纳答案by Viktor Kerkez
You can create a function that creates the itemnode from a row in your DataFrame:
您可以创建一个item从 DataFrame 中的一行创建节点的函数：
def func(row):
xml = ['<item>']
for field in row.index:
xml.append(' <field name="{0}">{1}</field>'.format(field, row[field]))
xml.append('</item>')
return '\n'.join(xml)
And then apply the function along the axis=1.
然后沿axis=1.
>>> print '\n'.join(df.apply(func, axis=1))
<item>
<field name="field_1">cat</field>
<field name="field_2">15,263</field>
<field name="field_3">2.52</field>
<field name="field_4">00:03:00</field>
</item>
<item>
<field name="field_1">dog</field>
<field name="field_2">1,652</field>
<field name="field_3">3.71</field>
<field name="field_4">00:03:47</field>
</item>
...
回答by Andy Hayden
To expand on Viktor's excellent answer (and tweaking it slightly to work with duplicate columns), you could set this up as a to_xmlDataFrame method:
为了扩展 Viktor 的优秀答案（并稍微调整它以处理重复的列），您可以将其设置为to_xmlDataFrame 方法：
def to_xml(df, filename=None, mode='w'):
def row_to_xml(row):
xml = ['<item>']
for i, col_name in enumerate(row.index):
xml.append(' <field name="{0}">{1}</field>'.format(col_name, row.iloc[i]))
xml.append('</item>')
return '\n'.join(xml)
res = '\n'.join(df.apply(row_to_xml, axis=1))
if filename is None:
return res
with open(filename, mode) as f:
f.write(res)
pd.DataFrame.to_xml = to_xml
Then you can print the xml:
然后你可以打印xml：
In [21]: print df.to_xml()
<item>
<field name="field_1">cat</field>
<field name="field_2">15,263</field>
<field name="field_3">2.52</field>
<field name="field_4">00:03:00</field>
</item>
<item>
...
or save it to a file:
或将其保存到文件：
In [22]: df.to_xml('foo.xml')
Obviously this example should be tweaked to fit your xml standard.
显然，这个例子应该进行调整以适合您的 xml 标准。
回答by sparkonhdfs
You can use the xml.etree.ElementTreepackage to generate a read-friendly format in a very few lines of code.
您可以使用xml.etree.ElementTree包以极少的代码行生成易于阅读的格式。
root = etree.Element('data');
for i,row in dframe.iterrows():
item = etree.SubElement(root, 'item', attrib=row.to_dict());
etree.dump(root);
This will create a XML Tree (under root), where each row will will be of type item, and have attributes for all columns. You can create a more nested tree with columns as well by creating a subelement for each field.
这将创建一个 XML 树（在根目录下），其中每一行的类型都是item，并且具有所有列的属性。您还可以通过为每个字段创建一个子元素来创建更多嵌套的列树。
Then you can also read the xml file back in Python using the ElementTree package:
然后，您还可以使用 ElementTree 包在 Python 中读取 xml 文件：
xml.etree.ElementTree.parse('xml_file.xml');
