def _replace_nans(self, data):<EOL>
for c in data:<EOL><INDENT>dtype = data[c].dtype<EOL>if dtype in (np.float32, np.float64):<EOL><INDENT>if dtype == np.float32:<EOL><INDENT>replacement = self.MISSING_VALUES['<STR_LIT:f>']<EOL><DEDENT>else:<EOL><INDENT>replacement = self.MISSING_VALUES['<STR_LIT:d>']<EOL><DEDENT>data[c] = data[c].fillna(replacement)<EOL><DEDENT><DEDENT>return data<EOL>
Checks floating point data columns for nans, and replaces these with
        the generic Stata for missing value (.)