How to extract a particular bits of a specific column of Python pandas dataframe

For a particular column of pandas dataframe,
the column is actually a 16 bit data converted to BCD.
I want to extract only bit 14-8 of a particular row and convert to BCD.
The below formula works for small dataframe as below.

df=pd.DataFrame({'Value':[128,128,436,465], 'Minutes':[1280,16384,1792,1536] })

df['Minutes_1']=df.Minutes.apply(int).apply(bin).str[2:].str[:-8].apply(int, base=2)
df

But when I apply

df['Minutes_1']=df.Minutes.apply(int).apply(bin).str[2:].str[:-8].apply(int, base=2)

for bigger data frame of 688126 rows I get an error saying

invalid literal for int() with base 2: ''

Note:  Few values of the row are 
0, 256,512,768,1024,1280,1536,1792,2048,2304,4096,4352,4608,4864,
5120,5276,5632,5888,6144,6400,8192,8448,8704,8960,9216,9472,9728,9984,10240,10496,12288,

12544,12800,13056,13312,13568,13824,14080,14336,14592,16384,16640,16896,17152,17408,17920,
18176,18432,18688,20480,20736,20992,21248,21504,21760,22016,22272,22528,22784

Error is as below

ValueError Traceback (most recent call last)
in
1 df.LO_TIME_0_J2_0

----> 2 df['Minutes_1']=df.LO_TIME_0_J2_0.apply(int).apply(bin).str[2:].str[:-8].apply(int, base=2)
3 df.LO_TIME_0_J2_0

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\series.py in apply(self, func, convert_dtype, args, **kwds)
3192 else:
3193 values = self.astype(object).values
-> 3194 mapped = lib.map_infer(values, f, convert=convert_dtype)
3195
3196 if len(mapped) and isinstance(mapped[0], Series):

pandas/_libs/src\inference.pyx in pandas._libs.lib.map_infer()

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\series.py in (x)
3179 # handle ufuncs and lambdas
3180 if kwds or args and not isinstance(func, np.ufunc):
-> 3181 f = lambda x: func(x, *args, **kwds)
3182 else:
3183 f = func

ValueError: invalid literal for int() with base 2: ''

Please Help