def METHOD_NAME(cls, fp):
    """Import dataset.
    Arguments
    ---------
    fp: str, pathlib.Path
        File path to the RIS file.
    note_list: list
        A list of notes, coming from the Dataframe's "notes" column.
    Returns
    -------
    pandas.DataFrame:
        Dataframe with entries.
    Raises
    ------
    ValueError
        File with unrecognized encoding is used as input.
    """
    encodings = ["utf-8", "utf-8-sig", "ISO-8859-1"]
    entries = None
    if entries is None:
        if is_url(fp):
            url_input = urlopen(fp)
        for encoding in encodings:
            if is_url(fp):
                try:
                    bibliography_file = io.StringIO(
                        url_input.read().decode(encoding)
                    )
                    entries = list(
                        rispy.load(bibliography_file, skip_unknown_tags=True)
                    )
                    bibliography_file.close()
                    break
                except UnicodeDecodeError:
                    pass
            else:
                try:
                    with open(fp, "r", encoding=encoding) as bibliography_file:
                        entries = list(
                            rispy.load(bibliography_file, skip_unknown_tags=True)
                        )
                        break
                except UnicodeDecodeError:
                    pass
                except IOError as e:
                    logging.warning(e)
        if entries is None:
            raise ValueError("Cannot find proper encoding for data file.")
    # Turn the entries dictionary into a Pandas dataframe
    df = pandas.DataFrame(entries)
    # Check if "notes" column is present
    if "notes" in df:
        # Strip Zotero XHTML <p> tags on "notes"
        df["notes"] = df["notes"].apply(cls._strip_zotero_p_tags)
        # Split "included" from "notes"
        df[["included", "notes"]] = pandas.DataFrame(
            df["notes"].apply(cls._label_parser).tolist(),
            columns=["included", "notes"],
        )
        # Return the standardised dataframe with label and notes separated
        return _standardize_dataframe(df)
    else:
        # Return the standardised dataframe
        return _standardize_dataframe(df)