Split a string and create a news columns with parents

Question

let's say I have this dataframe, and I would like to split it into several after (.) and have it like that, with levels, help please Thanks!!

Answer 1

I think you can achive the expected result by applying the following method. I've just create a fake dataframe to test.

import pandas as pd

df = pd.DataFrame(columns=["section"], data=[["level1.level2.level3.level4.level5"],["level1.level2.level3.level4.level5.level6"]])


columns = ['section', 'level', 'parent']

def split_parent(row):
    levels = row["section"].split(".")
    count_level = len(levels)
    sub_levels = '.'.join(levels[:(count_level-1)])

    #  create a new row for each level of section
    new_df = pd.DataFrame(columns=columns, data=[[row["section"], count_level, sub_levels]])
    for num_level in range(count_level-1, 0, -1):
        sec = ".".join(levels[:num_level])
        par = "" if num_level == 1 else ".".join(levels[:num_level-1])
        new_df = new_df.append({'section': sec, 'level': num_level, 'parent': par}, ignore_index=True)

    return new_df

result = pd.DataFrame(columns=columns)
for index, row in df.iterrows():
    result = result.append(split_parent(row), ignore_index=True)

print(result)

As result, you'll get:

                                      section level  \
0          level1.level2.level3.level4.level5     5   
1                 level1.level2.level3.level4     4   
2                        level1.level2.level3     3   
3                               level1.level2     2   
4                                      level1     1   
5   level1.level2.level3.level4.level5.level6     6   
6          level1.level2.level3.level4.level5     5   
7                 level1.level2.level3.level4     4   
8                        level1.level2.level3     3   
9                               level1.level2     2   
10                                     level1     1   

                                parent  
0          level1.level2.level3.level4  
1                 level1.level2.level3  
2                        level1.level2  
3                               level1  
4                                       
5   level1.level2.level3.level4.level5  
6          level1.level2.level3.level4  
7                 level1.level2.level3  
8                        level1.level2  
9                               level1  
10                                      

If you need any further explanation, just write to me.

I hope I helped you.