使用动态名称创建变量通常是一种不好的做法.

Creating variables with dynamic names is typically a bad practice.

我认为，针对您的问题的***解决方案是将数据帧存储到字典中，并动态生成用于访问每个数据帧的密钥名称.

I think the best solution for your problem is to store your dataframes into a dictionary and dynamically generate the name of the key to access each dataframe.

import copy

dict_of_df = {}
for ym in [201511, 201612, 201710]:

    key_name = 'df_new_'+str(ym)    

    dict_of_df[key_name] = copy.deepcopy(df)

    to_change = df['YearMonth']< ym
    dict_of_df[key_name].loc[to_change, 'new_col'] = ym   

dict_of_df.keys()
Out[36]: ['df_new_201710', 'df_new_201612', 'df_new_201511']

dict_of_df
Out[37]: 
{'df_new_201511':     A    B  ID                       t  YearMonth  new_col
 0  -a    a   1 2016-12-05 07:53:35.943     201612   201612
 1   1  NaN   2 2016-12-05 07:53:35.943     201612   201612
 2   a    c   2 2016-12-05 07:53:35.943     201612   201612,
 'df_new_201612':     A    B  ID                       t  YearMonth  new_col
 0  -a    a   1 2016-12-05 07:53:35.943     201612   201612
 1   1  NaN   2 2016-12-05 07:53:35.943     201612   201612
 2   a    c   2 2016-12-05 07:53:35.943     201612   201612,
 'df_new_201710':     A    B  ID                       t  YearMonth  new_col
 0  -a    a   1 2016-12-05 07:53:35.943     201612   201710
 1   1  NaN   2 2016-12-05 07:53:35.943     201612   201710
 2   a    c   2 2016-12-05 07:53:35.943     201612   201710}

 # Extract a single dataframe
 df_2015 = dict_of_df['df_new_201511']