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Classe « DataFrame »

Méthode pandas.DataFrame.to_markdown

Signature de la méthode to_markdown

def to_markdown(self, buf: 'FilePath | WriteBuffer[str] | None' = None, *, mode: 'str' = 'wt', index: 'bool' = True, storage_options: 'StorageOptions | None' = None, **kwargs) -> 'str | None' 

Description

help(DataFrame.to_markdown)

Print DataFrame in Markdown-friendly format.

Parameters
----------
buf : str, Path or StringIO-like, optional, default None
    Buffer to write to. If None, the output is returned as a string.
mode : str, optional
    Mode in which file is opened, "wt" by default.
index : bool, optional, default True
    Add index (row) labels.

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.request.Request`` as header options. For other
    URLs (e.g. starting with "s3://", and "gcs://") the key-value pairs are
    forwarded to ``fsspec.open``. Please see ``fsspec`` and ``urllib`` for more
    details, and for more examples on storage options refer `here
    <https://pandas.pydata.org/docs/user_guide/io.html?
    highlight=storage_options#reading-writing-remote-files>`_.

**kwargs
    These parameters will be passed to `tabulate                 <https://pypi.org/project/tabulate>`_.

Returns
-------
str
    DataFrame in Markdown-friendly format.

Notes
-----
Requires the `tabulate <https://pypi.org/project/tabulate>`_ package.

Examples
        --------
        >>> df = pd.DataFrame(
        ...     data={"animal_1": ["elk", "pig"], "animal_2": ["dog", "quetzal"]}
        ... )
        >>> print(df.to_markdown())
        |    | animal_1   | animal_2   |
        |---:|:-----------|:-----------|
        |  0 | elk        | dog        |
        |  1 | pig        | quetzal    |

        Output markdown with a tabulate option.

        >>> print(df.to_markdown(tablefmt="grid"))
        +----+------------+------------+
        |    | animal_1   | animal_2   |
        +====+============+============+
        |  0 | elk        | dog        |
        +----+------------+------------+
        |  1 | pig        | quetzal    |
        +----+------------+------------+

Vous êtes un professionnel et vous avez besoin d'une formation ? Programmation Python
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