pandas.DataFrame.to_xml#
- DataFrame.to_xml(path_or_buffer=None, index=True, root_name='data', row_name='row', na_rep=None, attr_cols=None, elem_cols=None, namespaces=None, prefix=None, encoding='utf-8', xml_declaration=True, pretty_print=True, parser='lxml', stylesheet=None, compression='infer', storage_options=None)[source]#
Render a DataFrame to an XML document.
New in version 1.3.0.
- Parameters
- path_or_bufferstr, path object, file-like object, or None, default None
String, path object (implementing
os.PathLike[str]
), or file-like object implementing awrite()
function. If None, the result is returned as a string.- indexbool, default True
Whether to include index in XML document.
- root_namestr, default ‘data’
The name of root element in XML document.
- row_namestr, default ‘row’
The name of row element in XML document.
- na_repstr, optional
Missing data representation.
- attr_colslist-like, optional
List of columns to write as attributes in row element. Hierarchical columns will be flattened with underscore delimiting the different levels.
- elem_colslist-like, optional
List of columns to write as children in row element. By default, all columns output as children of row element. Hierarchical columns will be flattened with underscore delimiting the different levels.
- namespacesdict, optional
All namespaces to be defined in root element. Keys of dict should be prefix names and values of dict corresponding URIs. Default namespaces should be given empty string key. For example,
namespaces = {"": "https://example.com"}
- prefixstr, optional
Namespace prefix to be used for every element and/or attribute in document. This should be one of the keys in
namespaces
dict.- encodingstr, default ‘utf-8’
Encoding of the resulting document.
- xml_declarationbool, default True
Whether to include the XML declaration at start of document.
- pretty_printbool, default True
Whether output should be pretty printed with indentation and line breaks.
- parser{‘lxml’,’etree’}, default ‘lxml’
Parser module to use for building of tree. Only ‘lxml’ and ‘etree’ are supported. With ‘lxml’, the ability to use XSLT stylesheet is supported.
- stylesheetstr, path object or file-like object, optional
A URL, file-like object, or a raw string containing an XSLT script used to transform the raw XML output. Script should use layout of elements and attributes from original output. This argument requires
lxml
to be installed. Only XSLT 1.0 scripts and not later versions is currently supported.- compressionstr or dict, default ‘infer’
For on-the-fly compression of the output data. If ‘infer’ and ‘path_or_buffer’ is path-like, then detect compression from the following extensions: ‘.gz’, ‘.bz2’, ‘.zip’, ‘.xz’, ‘.zst’, ‘.tar’, ‘.tar.gz’, ‘.tar.xz’ or ‘.tar.bz2’ (otherwise no compression). Set to
None
for no compression. Can also be a dict with key'method'
set to one of {'zip'
,'gzip'
,'bz2'
,'zstd'
,'tar'
} and other key-value pairs are forwarded tozipfile.ZipFile
,gzip.GzipFile
,bz2.BZ2File
,zstandard.ZstdCompressor
ortarfile.TarFile
, respectively. As an example, the following could be passed for faster compression and to create a reproducible gzip archive:compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1}
.New in version 1.5.0: Added support for .tar files.
Changed in version 1.4.0: Zstandard support.
- storage_optionsdict, 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.request.Request
as header options. For other URLs (e.g. starting with “s3://”, and “gcs://”) the key-value pairs are forwarded tofsspec.open
. Please seefsspec
andurllib
for more details, and for more examples on storage options refer here.
- Returns
- None or str
If
io
is None, returns the resulting XML format as a string. Otherwise returns None.
Examples
>>> df = pd.DataFrame({'shape': ['square', 'circle', 'triangle'], ... 'degrees': [360, 360, 180], ... 'sides': [4, np.nan, 3]})
>>> df.to_xml() <?xml version='1.0' encoding='utf-8'?> <data> <row> <index>0</index> <shape>square</shape> <degrees>360</degrees> <sides>4.0</sides> </row> <row> <index>1</index> <shape>circle</shape> <degrees>360</degrees> <sides/> </row> <row> <index>2</index> <shape>triangle</shape> <degrees>180</degrees> <sides>3.0</sides> </row> </data>
>>> df.to_xml(attr_cols=[ ... 'index', 'shape', 'degrees', 'sides' ... ]) <?xml version='1.0' encoding='utf-8'?> <data> <row index="0" shape="square" degrees="360" sides="4.0"/> <row index="1" shape="circle" degrees="360"/> <row index="2" shape="triangle" degrees="180" sides="3.0"/> </data>
>>> df.to_xml(namespaces={"doc": "https://example.com"}, ... prefix="doc") <?xml version='1.0' encoding='utf-8'?> <doc:data xmlns:doc="https://example.com"> <doc:row> <doc:index>0</doc:index> <doc:shape>square</doc:shape> <doc:degrees>360</doc:degrees> <doc:sides>4.0</doc:sides> </doc:row> <doc:row> <doc:index>1</doc:index> <doc:shape>circle</doc:shape> <doc:degrees>360</doc:degrees> <doc:sides/> </doc:row> <doc:row> <doc:index>2</doc:index> <doc:shape>triangle</doc:shape> <doc:degrees>180</doc:degrees> <doc:sides>3.0</doc:sides> </doc:row> </doc:data>