[Python] How to cleanup some content from the text file

I have the following data in a CSV.

"ID","OTHER_FIELDS_2"
"87","25 R160 22 13 E"
"87","25 R165 22 08 E"
"77",""
"18","20 BA-10 12 06 2 30 S"
"18","20 BA-20 12 06 2 30 S"
"88","20 TH-42 02 02 5 30 MT"
"66","20 AD-38 12 06 B"
"66","20 AD-38 30 07 B"
"70","20 OL-45 19 11 B"
"70","20 EM-45 19 08 B"


After running my Python code, I got the following output:

18,"
","20 BA-10 12 06 2 30 S
20 BA-20 12 06 2 30 S","
",**********
66,"
","20 AD-38 12 06 B
20 AD-38 30 07 B","
",**********
70,"
","20 OL-45 19 11 B
20 EM-45 19 08 B","
",**********
77,"
",,"
",**********
87,"
","25 R160 22 13 E
25 R165 22 08 E","
",**********
88,"
",20 TH-42 02 02 5 30 MT,"
",**********


But I have to generate the following output in txt format:

18
20 BA-10 12 06 2 30 S
20 BA-20 12 06 2 30 S
**********
66
20 AD-38 12 06 B
20 AD-38 30 07 B
**********
70
20 OL-45 19 11 B
20 EM-45 19 08 B
**********
77
**********
87
25 R160 22 13 E
25 R165 22 08 E
**********
88
20 TH-42 02 02 5 30 MT
**********


Here is my code:

import pandas as pd
import csv

df = pd.read_csv('idDetails.csv')
data_rows = []

group_column = 'ID'
selected_columns = ['OTHER_FIELDS_2']
grouped_data = df.groupby(group_column)[selected_columns]

for group_name, group_df in grouped_data:
#print(f"{group_name}")
other_data = group_df.to_string(header=False,index=False)
other_data_a = group_df.fillna('').dropna(axis = 0, how = 'all')
other_data_b = other_data_a.to_string(header=False,index=False)
#print(other_data_b)
other_data_c = '**********'
#print(other_data_c)
data_rows.append([group_name, '\n', other_data_b, '\n', other_data_c])
dfo = pd.DataFrame(data_rows)
dfo.to_csv('idDetailsoutput.txt', header=False, index=False)


A possible solution to get the desired output is appreciated.

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