Dataframe first performs grouping operation and then combines output

dataframe First group operation and then merge output ： It mainly uses grouping functions groupby And merge function append、concat, Specific code ：

For example, group first , Delete outliers for each group of data （MAD）, Then merge the processed data into one dataframe Output .

import os
import pandas as pd
from pyod.models.mad import MAD

import warnings
warnings.filterwarnings('ignore')

#%%
#test
df = pd.read_csv('./21.csv')
# print(len(df))#2273824

def fit_model(model, data, column='s'):
    # fit the model and predict it
    df = data.copy()
    data_to_predict = data[column].to_numpy().reshape(-1, 1)
    predictions = model.fit_predict(data_to_predict)
    df['Predictions_1'] = predictions
    
    return df

df_groupby = df.groupby(["class"])#group by class
frames = []
for decyear,group in df_groupby:
    # print(decyear)
    # print(group)
    mad_model = MAD()
    group_mad = fit_model(mad_model,group)
    group_mad_filter = group_mad[(group_mad['Predictions_1'] == 0)]
    # print(group_mad_filter) 
    frames.append(group_mad_filter)
    
result = pd.concat(frames, axis=0, names=None)
print('done!')