finding dupes (with a twist)

[buran]

Your code skips first occurrence of division, email combination.
I assume your csv file has hader, e.g.

Output:
Division,field2,field3,field4,Email
Electrical,field2,field3,field4,[email protected]
Automotive,field2,field3,field4,[email protected]
Fuses,field2,field3,field4,[email protected]
Electrical,field2,field3,field4,[email protected]
Automotive,field2,field3,field4,[email protected]
Fuses,field2,field3,field4,[email protected]
Electrical,field2,field3,field4,[email protected]
Automotive,field2,field3,field4,[email protected]
Fuses,field2,field3,field4,[email protected]

using csv module

import csv
from collections import defaultdict

dupes = defaultdict(list)
with open('Tdf contacts.csv', 'r') as read_obj:
    csv_reader = csv.DictReader(read_obj)
    fieldnames = csv_reader.fieldnames
    for line in csv_reader:
        key = (line['Email'].lower(), line['Division'])
        dupes[key].append(line)

with open('new_dupes_file.csv', 'w') as f:
    wrtr = csv.DictWriter(f, fieldnames=fieldnames)
    wrtr.writeheader()
    for key, values in dupes.items():
        if len(values) > 1:
            wrtr.writerows(values)

using pandas

import pandas as pd 

df = pd.read_csv('Tdf contacts.csv')
df['Email'] = df['Email'].apply(lambda x: x.lower())
df['Duplicated'] = df.duplicated(subset=['Division', 'Email'], keep=False)
df_dupes = df[df['Duplicated']].sort_values(by=['Division', 'Email'])
df_dupes.drop(['Duplicated'], axis=1).to_csv('dupes.csv', index=False)