Splitting "Check all that apply" survey column from Google Forms

I have a google forms data with a column Reasons which looks like this for 2 rows depending on how many the user checks on the survey:

import pandas as pd

filename = 'Example.csv'
df = pd.read_csv(filename)
print(df.to_dict("list"))

Output:

{
  'ID': [1, 2], 
  'Join Date': [
    Timestamp('2023-01-01 00:00:00'), 
    Timestamp('2022-12-01 00:00:00')
  ], 
  'Reasons': [
    'Benefits [Leave, Flexi, Dental, Insurance etc.], Compensation [Salary & Bonus]', 
    'Career & Growth Opportunities [Learning & Development, Progression], Meaningful work'
  ]
}

I want it to look like:

{
  'ID': [1, 1, 2, 2], 
  'Join Date': [
    Timestamp('2023-01-01 00:00:00'), 
    Timestamp('2023-01-01 00:00:00'), 
    Timestamp('2022-12-01 00:00:00'), 
    Timestamp('2022-12-01 00:00:00')
  ], 
  'Reasons': [
    'Benefits [Leave, Flexi, Dental, Insurance etc.]', 
    'Compensation [Salary & Bonus]', 
    'Career & Growth Opportunities [Learning & Development, Progression]',         
    'Meaningful work'
  ]
}

Converted back to a dataframe

After importing the data into python as a dataframe, how can i split this up in python and create duplicate rows for each reason checked by a user?

I cant split it by comma because there are commas in the reasons provided. Will it work using explode()?

Hopefully someone can help me.

Here is the regex rule:

r"([^,\[\]]+\[[^\[\]]+\])|([^,\[\]]+)"

Now, we can use this rule for dataframe:

import re
df["Reasons"]=df["Reasons"].apply(lambda x: re.findall(r"([^,\[\]]+\[[^\[\]]+\])|([^,\[\]]+)", x))

'''
|    |   ID | Join Date           | Reasons                                                                                                 |
|---:|-----:|:--------------------|:--------------------------------------------------------------------------------------------------------|
|  0 |    1 | 2023-01-01 00:00:00 | [('Benefits [Leave, Flexi, Dental, Insurance etc.]', ''), (' Compensation [Salary & Bonus]', '')]       |
|  1 |    2 | 2022-12-01 00:00:00 | [('Career & Growth Opportunities [Learning & Development, Progression]', ''), ('', ' Meaningful work')] |
'''

As you can see, empty strings and the answers we need are stored in tuples and in a list. Let's get rid of empty strings:

df = df.explode("Reasons") #list values to new rows
df["Reasons"]=df["Reasons"].apply(lambda x: [i for i in x if i != ""][0]) # if value not equal empty string put it on a list. And get the first element in that we have a list of one element.

Out:

|    |   ID | Join Date           | Reasons                                                             |
|---:|-----:|:--------------------|:--------------------------------------------------------------------|
|  0 |    1 | 2023-01-01 00:00:00 | Benefits [Leave, Flexi, Dental, Insurance etc.]                     |
|  0 |    1 | 2023-01-01 00:00:00 | Compensation [Salary & Bonus]                                       |
|  1 |    2 | 2022-12-01 00:00:00 | Career & Growth Opportunities [Learning & Development, Progression] |
|  1 |    2 | 2022-12-01 00:00:00 | Meaningful work                                                     |

Note:
I'm not good at regex rules. So I used chatgpt to find the regex rule. You can ask like this: what is the regex rule of the xxxxx clause ?