 variable labels as values.
        Each label must be 80 characters or smaller.
    convert_strl : list, default None
        List of columns names to convert to Stata StrL format.  Columns with
        more than 2045 characters are automatically written as StrL.
        Smaller columns can be converted by including the column name.  Using
        StrLs can reduce output file size when strings are longer than 8
        characters, and either frequently repeated or sparse.
    version : int, default None
        The dta version to use. By default, uses the size of data to determine
        the version. 118 is used if data.shape[1] <= 32767, and 119 is used
        for storing larger DataFrames.
    {compression_options}

        .. versionchanged:: 1.4.0 Zstandard support.

    value_labels : dict of dicts
        Dictionary containing columns as keys and dictionaries of column value
        to labels as values. The combined length of all labels for a single
        variable must be 32,000 characters or smaller.

        .. versionadded:: 1.4.0

    Returns
    -------
    StataWriterUTF8
        The instance has a write_file method, which will write the file to the
        given `fname`.

    Raises
    ------
    NotImplementedError
        * If datetimes contain timezone information
    ValueError
        * Columns listed in convert_dates are neither datetime64[ns]
          or datetime
        * Column dtype is not representable in Stata
        * Column listed in convert_dates is not in DataFrame
        * Categorical label contains more than 32,000 characters

    Examples
    --------
    Using Unicode data and column names

    >>> from pandas.io.stata import StataWriterUTF8
    >>> data = pd.DataFrame([[1.0, 1, 'ᴬ']], columns=['a', 'β', 'ĉ'])
    >>> writer = StataWriterUTF8('./data_file.dta', data)
    >>> writer.write_file()

    Directly write a zip file
    >>> compression = {"method": "zip", "archive_name": "data_file.dta"}
    >>> writer = StataWriterUTF8('./data_file.zip', data, compression=compression)
    >>> writer.write_file()

    Or with long strings stored in strl format

    >>> data = pd.DataFrame([['ᴀ relatively long ŝtring'], [''], ['']],
    ...                     columns=['strls'])
    >>> writer = StataWriterUTF8('./data_file_with_long_strings.dta', data,
    ...                          convert_strl=['strls'])
    >>> writer.write_file()
    r