How do I cut a string based on digit first certain digit and the rest

Question

How do I cut a string based on digit first certain digit and the rest

Here's my data

Id       actual_pattern
1                100101
2                 10101
3               1010101
4                   101

Here's the expected output

for cut_pattern1 is the first 4 digits from actual_pattern for cut_pattern2 is the rest form from cut_pattern1, if the rest from cut_pattern1 is not exist make cut_pattern2 = 0

If any 1 in cut_pattern2, make binary_cut2 = 1 else make binary_cut2 = 0

Id       actual_pattern   cut_pattern1       cut_pattern2    binary_cut2
1                100101           1001                 01              1
2                 10101           1010                  1              1
3               1010101           1010                101              1
4                   101            101                  0              0

Answer 1

Create new columns by indexing with str, replace for change empty strings and for new column use Series.str.contains with casting to integers:

df['actual_pattern'] = df['actual_pattern'].astype(str)

df['cut_pattern1'] = df['actual_pattern'].str[:4]
df['cut_pattern2'] = df['actual_pattern'].str[4:].replace('','0')
df['binary_cut2'] = df['cut_pattern2'].str.contains('1').astype(int)
print (df)
   Id actual_pattern cut_pattern1 cut_pattern2  binary_cut2
0   1         100101         1001           01            1
1   2          10101         1010            1            1
2   3        1010101         1010          101            1
3   4            101          101            0            0

EDIT:

Solution for @Rick Hitchcock from comments:

df['actual_pattern'] = df['actual_pattern'].astype(str)

df['cut_pattern1'] = df['actual_pattern'].str[:4]
df['cut_pattern2'] = df['actual_pattern'].str[4:].replace('','0')
df['binary_cut2'] = df['cut_pattern2'].str.contains('1').astype(int)
print (df)
  Id actual_pattern cut_pattern1 cut_pattern2  binary_cut2
0  1         100101         1001           01            1
1  2          10101         1010            1            1
2  3        1010101         1010          101            1
3  4       00001111         0000         1111            1