def convert(self, values, nan_rep, encoding, errors):
<EOL>if values.dtype.fields is not None:<EOL><INDENT>values = values[self.cname]<EOL><DEDENT>self.set_data(values)<EOL>meta = _ensure_decoded(self.meta)<EOL>if self.dtype is not None:<EOL><INDENT>dtype = _ensure_decoded(self.dtype)<EOL>if dtype == '<STR_LIT>':<EOL><INDENT>self.data = _set_tz(self.data, self.tz, coerce=True)<EOL><DEDENT>elif dtype == '<STR_LIT>':<EOL><INDENT>self.data = np.asarray(self.data, dtype='<STR_LIT>')<EOL><DEDENT>elif dtype == '<STR_LIT:date>':<EOL><INDENT>try:<EOL><INDENT>self.data = np.asarray(<EOL>[date.fromordinal(v) for v in self.data], dtype=object)<EOL><DEDENT>except ValueError:<EOL><INDENT>self.data = np.asarray(<EOL>[date.fromtimestamp(v) for v in self.data],<EOL>dtype=object)<EOL><DEDENT><DEDENT>elif dtype == '<STR_LIT>':<EOL><INDENT>self.data = np.asarray(<EOL>[datetime.fromtimestamp(v) for v in self.data],<EOL>dtype=object)<EOL><DEDENT>elif meta == '<STR_LIT>':<EOL><INDENT>categories = self.metadata<EOL>codes = self.data.ravel()<EOL>if categories is None:<EOL><INDENT>categories = Index([], dtype=np.float64)<EOL><DEDENT>else:<EOL><INDENT>mask = isna(categories)<EOL>if mask.any():<EOL><INDENT>categories = categories[~mask]<EOL>codes[codes != -<NUM_LIT:1>] -= mask.astype(int).cumsum().values<EOL><DEDENT><DEDENT>self.data = Categorical.from_codes(codes,<EOL>categories=categories,<EOL>ordered=self.ordered)<EOL><DEDENT>else:<EOL><INDENT>try:<EOL><INDENT>self.data = self.data.astype(dtype, copy=False)<EOL><DEDENT>except TypeError:<EOL><INDENT>self.data = self.data.astype('<STR_LIT:O>', copy=False)<EOL><DEDENT><DEDENT><DEDENT>if _ensure_decoded(self.kind) == '<STR_LIT:string>':<EOL><INDENT>self.data = _unconvert_string_array(<EOL>self.data, nan_rep=nan_rep, encoding=encoding, errors=errors)<EOL><DEDENT>return self<EOL>
set the data from this selection (and convert to the correct dtype
        if we can)