如何将XML文件转换为Pandas数据框

时间:2020-01-24 18:41:11

标签: python xml pandas

我要转换以下XML文件:

<data>
  <level_1 name="employment">
    <level_2 name="sub-employment">
      <indicator>ind1</indicator>
      <indicator>ind2</indicator>
    </level_2>
    <level_2 name="sub-employment2">
      <indicator>ind3</indicator>
    </level_2>
  </level_1>
  <level_1 name="health">
    <level_2 name="sub-health">
      <level_3 name="sub-sub-health">
        <indicator>ind4</indicator>
      </level_3>
    </level_2>
  </level_1>
</data>

进入熊猫数据框,结果类似于:

  level_1   level_2         level_3        indicator

0  employment  sub-employment   None             ind1
1  employment  sub-employment   None             ind2    
2  employment  sub-employment2  None             ind3 
3  health      sub-health       sub-sub-health   ind4

在将xml.etree.cElementTree导入为et并将熊猫导入为pd之后,我使用了以下代码:

def getvalueofnode(node):
    """ return node text or None """
    return node.text if node is not None else None          
def main():
    """ main """
    parsed_xml = et.parse("tree.xml")
    dfcols = ['level_1', 'level_2', 'level_3', 'indicator']
    df_xml = pd.DataFrame(columns=dfcols)

    for node in parsed_xml.getroot():
        name = node.attrib.get('name')
        level_2 = node.find('level_2')
        level_3 = node.find('level_3')
        indicator = node.find('indicator')

        df_xml = df_xml.append(
            pd.Series([name, getvalueofnode(level_2), getvalueofnode(level_3),
                       getvalueofnode(indicator)], index=dfcols),
            ignore_index=True)     
    print(df_xml)     
main()

但是我得到了错误的结果:

      level_1   level_2 level_3 indicator
0  employment  \n          None      None
1      health  \n          None      None

我在做什么错了?

1 个答案:

答案 0 :(得分:1)

定义以下功能,创建祖先字典, 从 node 向上:

def parNames(node, root):
    names = {}
    while True:
        node = parentMap[node]
        if node is root:
            return names
        names[node.tag] = node.attrib['name']

稍后将需要它。它使用 parentMap 字典,该字典将 即将创建。

读取您的输入文件:

tree = et.parse('tree.xml')
root = tree.getroot()

实际处理应从创建父级地图开始 -字典,每个节点返回其父节点:

parentMap = {}
for parent in root.iter():
    for child in parent:
        parentMap[child] = parent

要为您的DataFrame创建源数据,请运行:

rows = []
for it in root.iter('indicator'):
    row = parNames(it, root)
    row[it.tag] = it.text
    rows.append(row)

此循环创建词典列表(每行数据)。 每行(一个字典)包含:

  • 迭代器键下-相应节点的文本,
  • “父”键( level _... )下的
  • name 所有属性 父母(由 parNames 函数返回)。

下一步是创建DataFrame:

df2 = pd.DataFrame(rows).fillna('').sort_index(axis=1)

唯一要做的步骤是将 indicator 列移到最后一个位置:

df2 = df2.reindex(df2.columns.drop('indicator')
    .append(pd.Index(['indicator'])),axis=1)