pandas.read_xml   pandas.read_xml(path_or_buffer, xpath='./*', namespaces=None, elems_only=False, attrs_only=False, names=None, encoding='utf-8', parser='lxml', stylesheet=None, compression='infer', storage_options=None)[source]
 
Read XML document into a DataFrame object.  New in version 1.3.0.   Parameters 
 
path_or_buffer:str, path object, or file-like object


String, path object (implementing os.PathLike[str]), or file-like object implementing a read() function. The string can be any valid XML string or a path. The string can further be a URL. Valid URL schemes include http, ftp, s3, and file.  
xpath:str, optional, default ‘./*’


The XPath to parse required set of nodes for migration to DataFrame. XPath should return a collection of elements and not a single element. Note: The etree parser supports limited XPath expressions. For more complex XPath, use lxml which requires installation.  
namespaces:dict, optional


The namespaces defined in XML document as dicts with key being namespace prefix and value the URI. There is no need to include all namespaces in XML, only the ones used in xpath expression. Note: if XML document uses default namespace denoted as xmlns=’<URI>’ without a prefix, you must assign any temporary namespace prefix such as ‘doc’ to the URI in order to parse underlying nodes and/or attributes. For example, 
namespaces = {"doc": "https://example.com"}
   
elems_only:bool, optional, default False


Parse only the child elements at the specified xpath. By default, all child elements and non-empty text nodes are returned.  
attrs_only:bool, optional, default False


Parse only the attributes at the specified xpath. By default, all attributes are returned.  
names:list-like, optional


Column names for DataFrame of parsed XML data. Use this parameter to rename original element names and distinguish same named elements.  
encoding:str, optional, default ‘utf-8’


Encoding of XML document.  
parser:{‘lxml’,’etree’}, default ‘lxml’


Parser module to use for retrieval of data. Only ‘lxml’ and ‘etree’ are supported. With ‘lxml’ more complex XPath searches and ability to use XSLT stylesheet are supported.  
stylesheet:str, path object or file-like object


A URL, file-like object, or a raw string containing an XSLT script. This stylesheet should flatten complex, deeply nested XML documents for easier parsing. To use this feature you must have lxml module installed and specify ‘lxml’ as parser. The xpath must reference nodes of transformed XML document generated after XSLT transformation and not the original XML document. Only XSLT 1.0 scripts and not later versions is currently supported.  
compression:str or dict, default ‘infer’


For on-the-fly decompression of on-disk data. If ‘infer’ and ‘path_or_buffer’ is path-like, then detect compression from the following extensions: ‘.gz’, ‘.bz2’, ‘.zip’, ‘.xz’, or ‘.zst’ (otherwise no compression). If using ‘zip’, the ZIP file must contain only one data file to be read in. Set to None for no decompression. Can also be a dict with key 'method' set to one of {'zip', 'gzip', 'bz2', 'zstd'} and other key-value pairs are forwarded to zipfile.ZipFile, gzip.GzipFile, bz2.BZ2File, or zstandard.ZstdDecompressor, respectively. As an example, the following could be passed for Zstandard decompression using a custom compression dictionary: compression={'method': 'zstd', 'dict_data': my_compression_dict}.  Changed in version 1.4.0: Zstandard support.   
storage_options:dict, optional


Extra options that make sense for a particular storage connection, e.g. host, port, username, password, etc. For HTTP(S) URLs the key-value pairs are forwarded to urllib as header options. For other URLs (e.g. starting with “s3://”, and “gcs://”) the key-value pairs are forwarded to fsspec. Please see fsspec and urllib for more details.    Returns 
 df

A DataFrame.      See also  read_json

Convert a JSON string to pandas object.  read_html

Read HTML tables into a list of DataFrame objects.    Notes This method is best designed to import shallow XML documents in following format which is the ideal fit for the two-dimensions of a DataFrame (row by column). 
<root>
    <row>
      <column1>data</column1>
      <column2>data</column2>
      <column3>data</column3>
      ...
   </row>
   <row>
      ...
   </row>
   ...
</root>
  As a file format, XML documents can be designed any way including layout of elements and attributes as long as it conforms to W3C specifications. Therefore, this method is a convenience handler for a specific flatter design and not all possible XML structures. However, for more complex XML documents, stylesheet allows you to temporarily redesign original document with XSLT (a special purpose language) for a flatter version for migration to a DataFrame. This function will always return a single DataFrame or raise exceptions due to issues with XML document, xpath, or other parameters. Examples 
>>> xml = '''<?xml version='1.0' encoding='utf-8'?>
... <data xmlns="http://example.com">
...  <row>
...    <shape>square</shape>
...    <degrees>360</degrees>
...    <sides>4.0</sides>
...  </row>
...  <row>
...    <shape>circle</shape>
...    <degrees>360</degrees>
...    <sides/>
...  </row>
...  <row>
...    <shape>triangle</shape>
...    <degrees>180</degrees>
...    <sides>3.0</sides>
...  </row>
... </data>'''
  
>>> df = pd.read_xml(xml)
>>> df
      shape  degrees  sides
0    square      360    4.0
1    circle      360    NaN
2  triangle      180    3.0
  
>>> xml = '''<?xml version='1.0' encoding='utf-8'?>
... <data>
...   <row shape="square" degrees="360" sides="4.0"/>
...   <row shape="circle" degrees="360"/>
...   <row shape="triangle" degrees="180" sides="3.0"/>
... </data>'''
  
>>> df = pd.read_xml(xml, xpath=".//row")
>>> df
      shape  degrees  sides
0    square      360    4.0
1    circle      360    NaN
2  triangle      180    3.0
  
>>> xml = '''<?xml version='1.0' encoding='utf-8'?>
... <doc:data xmlns:doc="https://example.com">
...   <doc:row>
...     <doc:shape>square</doc:shape>
...     <doc:degrees>360</doc:degrees>
...     <doc:sides>4.0</doc:sides>
...   </doc:row>
...   <doc:row>
...     <doc:shape>circle</doc:shape>
...     <doc:degrees>360</doc:degrees>
...     <doc:sides/>
...   </doc:row>
...   <doc:row>
...     <doc:shape>triangle</doc:shape>
...     <doc:degrees>180</doc:degrees>
...     <doc:sides>3.0</doc:sides>
...   </doc:row>
... </doc:data>'''
  
>>> df = pd.read_xml(xml,
...                  xpath="//doc:row",
...                  namespaces={"doc": "https://example.com"})
>>> df
      shape  degrees  sides
0    square      360    4.0
1    circle      360    NaN
2  triangle      180    3.0