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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _read_csv_with_offset_pandas_on_ray( fname, num_splits, start, end, kwargs, header ):
 # pragma: no cover """Use a Ray task to read a chunk of a CSV into a Pandas DataFrame. Note: Ray functions are not detected by codecov (thus pragma: no cover) Args: fname: The filename of the file to open. num_splits: The number of splits (partitions) to separate the DataFrame into. start: The start byte offset. end: The end byte offset. kwargs: The kwargs for the Pandas `read_csv` function. header: The header of the file. Returns: A list containing the split Pandas DataFrames and the Index as the last element. If there is not `index_col` set, then we just return the length. This is used to determine the total length of the DataFrame to build a default Index. """

    index_col = kwargs.get("index_col", None)
    bio = file_open(fname, "rb")
    bio.seek(start)
    to_read = header + bio.read(end - start)
    bio.close()
    pandas_df = pandas.read_csv(BytesIO(to_read), **kwargs)
    pandas_df.columns = pandas.RangeIndex(len(pandas_df.columns))
    if index_col is not None:
        index = pandas_df.index
        # Partitions must have RangeIndex
        pandas_df.index = pandas.RangeIndex(0, len(pandas_df))
    else:
        # We will use the lengths to build the index if we are not given an
        # `index_col`.
        index = len(pandas_df)
    return _split_result_for_readers(1, num_splits, pandas_df) + [index]