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Module « pandas »

Fonction read_fwf - module pandas

Signature de la fonction read_fwf

def read_fwf(filepath_or_buffer: 'FilePath | ReadCsvBuffer[bytes] | ReadCsvBuffer[str]', *, colspecs: 'Sequence[tuple[int, int]] | str | None' = 'infer', widths: 'Sequence[int] | None' = None, infer_nrows: 'int' = 100, dtype_backend: 'DtypeBackend | lib.NoDefault' = <no_default>, iterator: 'bool' = False, chunksize: 'int | None' = None, **kwds) -> 'DataFrame | TextFileReader' 

Description

help(pandas.read_fwf)

Read a table of fixed-width formatted lines into DataFrame.

Also supports optionally iterating or breaking of the file
into chunks.

Additional help can be found in the `online docs for IO Tools
<https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html>`_.

Parameters
----------
filepath_or_buffer : str, path object, or file-like object
    String, path object (implementing ``os.PathLike[str]``), or file-like
    object implementing a text ``read()`` function.The string could be a URL.
    Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is
    expected. A local file could be:
    ``file://localhost/path/to/table.csv``.
colspecs : list of tuple (int, int) or 'infer'. optional
    A list of tuples giving the extents of the fixed-width
    fields of each line as half-open intervals (i.e.,  [from, to[ ).
    String value 'infer' can be used to instruct the parser to try
    detecting the column specifications from the first 100 rows of
    the data which are not being skipped via skiprows (default='infer').
widths : list of int, optional
    A list of field widths which can be used instead of 'colspecs' if
    the intervals are contiguous.
infer_nrows : int, default 100
    The number of rows to consider when letting the parser determine the
    `colspecs`.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
    Back-end data type applied to the resultant :class:`DataFrame`
    (still experimental). Behaviour is as follows:

    * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
      (default).
    * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
      DataFrame.

    .. versionadded:: 2.0

**kwds : optional
    Optional keyword arguments can be passed to ``TextFileReader``.

Returns
-------
DataFrame or TextFileReader
    A comma-separated values (csv) file is returned as two-dimensional
    data structure with labeled axes.

See Also
--------
DataFrame.to_csv : Write DataFrame to a comma-separated values (csv) file.
read_csv : Read a comma-separated values (csv) file into DataFrame.

Examples
--------
>>> pd.read_fwf('data.csv')  # doctest: +SKIP

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