How to add new column in Pandas using multiple conditions

I have a dataframe that looks like this:

destination_zip destination_state
502111387        IA
388588179        MS           
T2A2L9           AB                  
891              AUK     
774653028        TX   

I am trying to write a code that will be adding a new column as destination_country to my dataframe, something like this:

destination_zip destination_state  destination_country
502111387        IA                 US
388588179        MS                 US 
T2A2L9           AB                 CA
891              AUK                NZ
774653028        TX                 US

what I have tried so far is:

df.loc[df['destination_state']=='TX', df['destination_country']]= 'US'
df.loc[df['destination_state']=='IA', df['destination_country']]= 'US'
df.loc[df['destination_state']=='MS', df['destination_country']]= 'US'
df.loc[df['destination_state']=='AUK', df['destination_country']]= 'NZ'
df.loc[df['destination_state']=='AB', df['destination_country']]= 'CA'

but this is not way too long to work with, I wanted something that would be based on multiple conditions in a single line of code, something like this:

df.loc[df['destination_state']=='TX','IA','MS' , df['destination_country']]= 'US'

but this code is not working, can anyone help me with this? My dataframe has 7k rows, that's why I wanted something with multiple conditons. I am using juypter notebook, python-3