xorbits.pandas.read_fwf#

xorbits.pandas.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 = _NoDefault.no_default, **kwds) → DataFrame | TextFileReader[source]#

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.

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 DataFrame (still experimental). Behaviour is as follows:

    • "numpy_nullable": returns nullable-dtype-backed DataFrame (default).

    • "pyarrow": returns pyarrow-backed nullable ArrowDtype DataFrame.

    New in version 2.0(pandas).

  • **kwds (optional) – Optional keyword arguments can be passed to TextFileReader.

Returns

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

Return type

DataFrame or TextFileReader

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')

Warning

This method has not been implemented yet. Xorbits will try to execute it with pandas.

This docstring was copied from pandas.