class deals_abnormal_by_3delta():'''3*delta法处理异常值属性：self.data ：data的浅复制self.scale ：默认为3self.val_low：下边界self.val_high：上边界self.high_index：触犯了上边界的索引self.low_index：触犯了下边界的索引self.all_abnormal_index：所有有问题的索引方法：__init__data：需要处理异常值的数据DataFrame（只保留有异常值的列）  scale：默认为3remove_all_abnormal返回：删除所有有问题行的数据remove_specific_column返回：删除制定列有问题行的数据replace_all_abnormal_with_boundary返回：用边界值替换所有有问题行的数据replace_all_abnormal_with_nan返回：用np.nan替换所有有问题行的数据    '''def __init__(self,data,scale = 3):self.data = data.copy()self.scale = scaleiqr = (self.data.quantile(0.75) - self.data.quantile(0.25)) * self.scaleself.val_low = self.data.quantile(0.25) - iqrself.val_high = self.data.quantile(0.75) + iqrself.operate_columns = [x for x in self.data.columns ]self.high_index = {}self.low_index = {}for i in self.operate_columns:temp_data = self.data[i]high_val = self.val_high[i]low_val = self.val_low[i]high_index = self.data[self.data[i] > high_val].indexlow_index = self.data[self.data[i] < low_val].indexif len(high_index) > 0:self.high_index[i] = high_indexif len(low_index) > 0:    self.low_index[i] = low_indexself.all_abnormal_index = []for i in self.high_index.keys():for j in self.high_index[i]:self.all_abnormal_index.append(j)for i in self.low_index.keys():for j in self.low_index[i]:self.all_abnormal_index.append(j)self.all_abnormal_index = [x for x in set(self.all_abnormal_index)]def remove_all_abnormal(self):result = self.data.drop(self.all_abnormal_index,inplace = False)return resultdef remove_specific_column(self,col):result = self.data.copy()result.drop(self.high_index[col],inplace = True)result.drop(self.low_index[col],inplace = True)return resultdef replace_all_abnormal_with_boundary(self):result = self.data.copy()for i in self.operate_columns:if i in self.high_index.keys():for j in self.high_index[i]:result[i][j] = self.val_high[i]if i in self.low_index.keys():for j in self.low_index[i]:    result[i][j] = self.val_low[i]return resultdef replace_all_abnormal_with_nan(self):result = self.data.copy()for i in self.operate_columns:if i in self.high_index.keys():for j in self.high_index[i]:result[i][j] = np.nanif i in self.low_index.keys():for j in self.low_index[i]:    result[i][j] = np.nanreturn result