def to_native_types(self, slicer=None, na_rep='<STR_LIT>', float_format=None,<EOL>decimal='<STR_LIT:.>', quoting=None, **kwargs):
values = self.values<EOL>if slicer is not None:<EOL><INDENT>values = values[:, slicer]<EOL><DEDENT>if float_format is None and decimal == '<STR_LIT:.>':<EOL><INDENT>mask = isna(values)<EOL>if not quoting:<EOL><INDENT>values = values.astype(str)<EOL><DEDENT>else:<EOL><INDENT>values = np.array(values, dtype='<STR_LIT:object>')<EOL><DEDENT>values[mask] = na_rep<EOL>return values<EOL><DEDENT>from pandas.io.formats.format import FloatArrayFormatter<EOL>formatter = FloatArrayFormatter(values, na_rep=na_rep,<EOL>float_format=float_format,<EOL>decimal=decimal, quoting=quoting,<EOL>fixed_width=False)<EOL>return formatter.get_result_as_array()<EOL>
convert to our native types format, slicing if desired