[Python] Series won't convert tolist()

Data Object:

"FiveGigabitEthernet1/0/1": {
"enabled": true,
"data": "10",
"voice": "20",
"mode": "None",
"serviceOutput": "None",
"serviceInput": "None",
"noMacro": "None",
"template": "None",
"tracking": "None",
"speed": "None",
"duplex": "None",
"nonnegotiate": "None",
"trusted": "None",
"channelGroup": "None",
"channelProtocol": "None",
"ipAddress": "None",
"ipMask": "None",
"nativeVlan": "None",
"allowedVlan": "None"
},
"TenGigabitEthernet1/1/1": {
"serviceOutput": "POLICY",
"channelGroup": "1",
"channelProtocol": "active",
"nonnegotiate": true,
"mode": "trunk",
"allowedVlan": ["2", "10", "20", "30"],
"nativeVlan": "2",
"enabled": true,
"data": "None",
"voice": "None",
"serviceInput": "None",
"noMacro": "None",
"template": "None",
"tracking": "None",
"speed": "None",
"duplex": "None",
"trusted": "None",
"ipAddress": "None",
"ipMask": "None"
}


Pandas Init:

unique = r"GigabitEthernet0\/0|Bluetooth|AppGigabitEthernet|TwentyFiveGigE|FortyGigabitEthernet|Vlan"
ints = pd.DataFrame.from_dict(dataResult, orient="index")
ints.index.name = "port"
ints = ints.reset_index()
test = ints[(ints["mode"] != "trunk") & (~ints["port"].str.contains(unique,case=False,na=False))]
print(test)


The above output prints a correctly filtered database with the ports I want. Test also shows a data type as "series". Why can't I use the ".tolist()" method to get a return as a python list as the port's column?

Picture of test data type.

The below errors out with a type error because python thinks test is a dataframe instead of a series.

test = ints[(ints["mode"] != "trunk") & (~ints["port"].str.contains(unique,case=False,na=False))].tolist()
print(test)


Picture of type error.

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