Date_Int

import numpy as np
import pandas as pd
df = pd.DataFrame({"Date": ["2014-03-21","2014-03-22","2014-03-23","2014-03-24", "2014-03-25", "2014-03-26","2014-03-21","2014-03-22","2014-03-23","2014-03-24", "2014-03-25", "2014-03-26","2014-03-21","2014-03-22","2014-03-23","2014-03-24", "2014-03-25", "2014-03-26","2014-03-21","2014-03-22","2014-03-23","2014-03-24", "2014-03-25", "2014-03-26","2014-03-27","2014-03-28","2014-03-29", "2014-03-30", "2014-03-31"],
                   "X0":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1]})
y0 = np.array([0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1])
df["Date"] = pd.to_datetime(df["Date"]).dt.strftime("%Y%m%d")
print( df )

from imblearn.over_sampling import SMOTE
sm = SMOTE()

y0.shape
x, y = sm.fit_sample(np.array(df), np.array(y0))

pd.DataFrame(x).astype(dtype=int)

>>>
           0  1
0   20140321  0
1   20140322  0
2   20140323  0
3   20140324  0
4   20140325  0
5   20140326  0
6   20140321  0
7   20140322  0
8   20140323  0
9   20140324  0
10  20140325  0
11  20140326  0
12  20140321  0
13  20140322  0
14  20140323  0
15  20140324  0
16  20140325  0
17  20140326  0
18  20140321  0
19  20140322  0
20  20140323  0
21  20140324  0
22  20140325  0
23  20140326  1
24  20140327  1
25  20140328  1
26  20140329  1
27  20140330  1
28  20140331  1
29  20140330  1
30  20140326  1
31  20140326  1
32  20140327  1
33  20140329  1
34  20140328  1
35  20140330  1
36  20140328  1
37  20140327  1
38  20140328  1
39  20140329  1
40  20140327  1
41  20140328  1
42  20140328  1
43  20140329  1
44  20140327  1
45  20140329  1

pd.to_datetime(df.iloc[:,0])