Slice/split string Series at various positions

Question

I\'m looking to split a string Series at different points depending on the length of certain substrings:

In [47]: df = pd.DataFrame([\'group9class1\', \'grou         


        

Answer 1

This works, by using double [[]] you can access the index value of the current element so you can index into the split_locations series:

In [119]:    
df[['group_class']].apply(lambda x: pd.Series([x.str[split_locations[x.name]:][0], x.str[:split_locations[x.name]][0]]), axis=1)
Out[119]:
         0        1
0   class1   group9
1   class2  group10
2  class20  group11

Or as @ajcr has suggested you can extract:

In [106]:

df['group_class'].str.extract(r'(?Pgroup[0-9]+)(?Pclass[0-9]+)')
Out[106]:
     group    class
0   group9   class1
1  group10   class2
2  group11  class20

EDIT

Regex explanation:

the regex came from @ajcr (thanks!), this uses str.extract to extract groups, the groups become new columns.

So ?P here identifies an id for a specific group to look for, if this is missing then an int will be returned for the column name.

so the rest should be self-explanatory: group[0-9] looks for the string group followed by the digits in range [0-9] which is what the [] indicate, this is equivalent to group\d where \d means digit.

So it could be re-written as:

df['group_class'].str.extract(r'(?Pgroup\d+)(?Pclass\d+)')