Creating variables with dynamic names is typically a bad practice.

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']

Best way is to create a dict with the dynamic names as keys:

chunks = {f'{sub}{i}':chunk for i, chunk in enumerate(np.array_split(df, 10))}

If you absolutely insist on creating the frames as individual variables, then you could assign them to the globals() dictionary, but this method is NOT advised:

for i, chunk in enumerate(np.array_split(df, 10)):
    globals()['{}{}'.format(sub, i)] = chunk

I think the best is create dictionary of DataFrames:

d = {}
for i in range(12,0,-1):
    d['t' + str(i)] = df.shift(i).add_suffix('_t' + str(i))

If need specify columns first:

d = {}
cols = ['column1','column2']
for i in range(12,0,-1):
    d['t' + str(i)] = df[cols].shift(i).add_suffix('_t' + str(i))

dict comprehension solution:

d = {'t' + str(i): df.shift(i).add_suffix('_t' + str(i)) for i in range(12,0,-1)}

print (d['t10'])
    column1_t10  column2_t10
0           NaN          NaN
1           NaN          NaN
2           NaN          NaN
3           NaN          NaN
4           NaN          NaN
5           NaN          NaN
6           NaN          NaN
7           NaN          NaN
8           NaN          NaN
9           NaN          NaN
10          0.0         19.0
11          1.0         18.0
12          2.0         17.0
13          3.0         16.0
14          4.0         15.0
15          5.0         14.0
16          6.0         13.0
17          7.0         12.0
18          8.0         11.0
19          9.0         10.0

EDIT: Is it possible by globals, but much better is dictionary:

d = {}
cols = ['column1','column2']
for i in range(12,0,-1):
    globals()['df' + str(i)] =  df[cols].shift(i).add_suffix('_t' + str(i))

print (df10)
    column1_t10  column2_t10
0           NaN          NaN
1           NaN          NaN
2           NaN          NaN
3           NaN          NaN
4           NaN          NaN
5           NaN          NaN
6           NaN          NaN
7           NaN          NaN
8           NaN          NaN
9           NaN          NaN
10          0.0         19.0
11          1.0         18.0
12          2.0         17.0
13          3.0         16.0
14          4.0         15.0
15          5.0         14.0
16          6.0         13.0
17          7.0         12.0
18          8.0         11.0
19          9.0         10.0

I think better is use dict of DataFrames:

d = {file[:7] : pd.read_csv(file, encoding = 'ISO-8859-1') for file in glob.glob("*.csv")}

and then select DataFrame by keys - first 7 letters of filenames:

print (d['AC20170'])

But if dont want use dicts:

for file in glob.glob("*.csv"):
    globals()[file[:7]] = pd.read_csv(file,encoding = 'ISO-8859-1')

print (AC20170)

I'm not sure why you don't want to just use a dictionary for this, but for the sake of just answering the question you can modify your current module to set these variables using sys and setattr like so

import sys

# Now instead of exec'ing
setattr(sys.modules[__name__], '{}_df'.format(filename), frame)

Again though, you almost definitely want to use a dict instead. See this question: How can you dynamically create variables via a while loop?