convert to our native types format, slicing if desired

def to_native_types(self, slicer=None, na_rep='', float_format=None,
                        decimal='.', quoting=None, **kwargs):
        """ convert to our native types format, slicing if desired """

        values = self.values
        if slicer is not None:
            values = values[:, slicer]

        # see gh-13418: no special formatting is desired at the
        # output (important for appropriate 'quoting' behaviour),
        # so do not pass it through the FloatArrayFormatter
        if float_format is None and decimal == '.':
            mask = isna(values)

            if not quoting:
                values = values.astype(str)
            else:
                values = np.array(values, dtype='object')

            values[mask] = na_rep
            return values

        from pandas.io.formats.format import FloatArrayFormatter
        formatter = FloatArrayFormatter(values, na_rep=na_rep,
                                        float_format=float_format,
                                        decimal=decimal, quoting=quoting,
                                        fixed_width=False)
        return formatter.get_result_as_array()