I have a list of addresses that I scraped from a site and I would like to compare that to a list of addresses from a previous scrape to merge and remove the duplicates. The list I scraped has zip codes and sometimes cities while the previous scraped list only has cities, no zip. My end goal is to merge all the duplicates and leave entries without duplicates.

Here is an example of 2 entries that I would like to merge:

```
['2 DUDES RC HOBBIES', 'SALT LAKE CITY', 'UT', '84106', '(801) 849-0292']

['2 DUDES RC HOBBIES', 'SALT LAKE CITY', 'UT', '', '(801) 849-0292']

```

Here's another snippet:

```
['1 STOP HOBBY & CRAFT SHOP', 'BATH', 'NY', '', '(607) 776-9293']

['1/32 SLOTCAR RACEWAY', 'UNIVERSITY PLACE', 'WA', '', '(253) 255-1807']

['2 DUDES RC HOBBIES', 'SALT LAKE CITY', 'UT', '84106', '(801) 849-0292']

['2 DUDES RC HOBBIES', 'SALT LAKE CITY', 'UT', '', '(801) 849-0292']

['2 JACKS HOBBIES AND MORE', 'LAFAYETTE', 'LA', '70507', '(337) 212-2916']

['2 JACKS HOBBIES AND MORE', 'LAFAYETTE', 'LA', '', '(337) 212-2916']

['3D HOBBIES', 'SOCIAL CIRCLE', 'GA', '', '(678) 283-9662']

['3DXHOBBIES', 'GREEN BROOK', 'NJ', '', '(732) 424-6400']

['5TH GEAR POWERSPORTS', 'ELKO', 'NV', '89801', '(775) 777-3373']

['5TH GEAR POWERSPORTS', 'ELKO', 'NV', '', '(775) 777-3373']

```

Entries 1 and 2 should stay while the 3rd and 4th should be merged

EDIT:

I apologize if I wasn't clear, this is my first time posting a question and I still have a lot to learn. I'll try to explain my question better. 

I have two CSV files that have a list of stores. Both files have the same fields; NAME, CITY, STATE, ZIP, PHONE. One file has data in the ZIP column while the other does not. The goal is to end up with a CSV file that has the stores that are unique to the file with zip codes.

```
without_zips = []
with open('without_zips.csv', newline='') as f:
    reader = csv.reader(f)
    for row in reader:
        without_zips.append(row)

with_zips = []
with open('with_zips.csv', newline='') as f:
    reader = csv.reader(f)
    for row in reader:
        with_zips.append(row)

```

Using the method @kzimmerman suggested worked but I switched each instance of `without_zips` with `with_zips`. The following code worked:

```
for without_zip_entry in without_zips:
    this_telephone = without_zip_entry[-1]
    for i, zip_entry in enumerate(with_zips):
        that_telephone = zip_entry[-1]
        if this_telephone in that_telephone:
            # Remove duplicate without zip code
            del with_zips[i]

```