Split pandas dataframe column based on number of digits

Question

I have a pandas dataframe which has two columns key and value, and the value always consists of a 8 digit number something like

>df1
key value
10  10000100
20  10000000
30  10100000
40  11110000

Now I need to take the value column and split it on the digits present, such that my result is a new data frame

>df_res
key 0 1 2 3 4 5 6 7
10  1 0 0 0 0 1 0 0
20  1 0 0 0 0 0 0 0
30  1 0 1 0 0 0 0 0
40  1 1 1 1 0 0 0 0

I cannot change the input data format, the most conventional thing I thought was to convert the value to a string and loop through each digit char and put it in a list, however am looking for something more elegant and faster, kindly help.

EDIT: The input is not in string, it is integer.

Answer 1

This should work:

df.value.astype(str).apply(list).apply(pd.Series).astype(int)

Answer 2

One approach could be -

arr = df.value.values.astype('S8')
df = pd.DataFrame(np.fromstring(arr, dtype=np.uint8).reshape(-1,8)-48)

Sample run -

In [58]: df
Out[58]: 
   key     value
0   10  10000100
1   20  10000000
2   30  10100000
3   40  11110000

In [59]: arr = df.value.values.astype('S8')

In [60]: pd.DataFrame(np.fromstring(arr, dtype=np.uint8).reshape(-1,8)-48)
Out[60]: 
   0  1  2  3  4  5  6  7
0  1  0  0  0  0  1  0  0
1  1  0  0  0  0  0  0  0
2  1  0  1  0  0  0  0  0
3  1  1  1  1  0  0  0  0