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39 def _drop_col(self, df): 40 ''' 41 Drops last column, which was added in the parsing procedure due to a 42 trailing white space for each sample in the text file 43 Arguments: 44 df: pandas dataframe 45 Return: 46 df: original df with last column dropped 47 ''' 48 return df.drop(df.columns[-1], axis=1)
35 @property 36 def drop_columns(self): 37 drop_col=self.uni_table.query('Iv<%s'%(self._iv_threshold)) 38 return pd.concat([drop_col,self.uni_table[self.uni_table['Iv'].isnull()]])
420 def df_column_types_rename(df): 421 result = [df[x].dtype.name for x in list(df.columns)] 422 result[:] = [x if x != 'object' else 'string' for x in result] 423 result[:] = [x if x != 'int64' else 'integer' for x in result] 424 result[:] = [x if x != 'float64' else 'double' for x in result] 425 result[:] = [x if x != 'bool' else 'boolean' for x in result] 426 427 return result
78 def _clean_column(self, column): 79 if not isinstance(column, (int, str, unicode)): 80 raise ValueError('{} is not a valid column'.format(column)) 81 return column in self.df.columns
80 def _clean_columns(df, keep_colnames): 81 new_colnames = [] 82 for i,colname in enumerate(df.columns): 83 if colname not in keep_colnames: 84 new_colnames.append(i) 85 else: 86 new_colnames.append(colname) 87 return new_colnames