Create column based on existing column in dataframe and lists

I have a dataframe with multiple columns. One of the columns, ‘TName’, has a different track names. I would like to create a new column for my dataframe which has the country of each racetrack.

My code (idk what to do with the last two lines):

austracks = ['Ascot', 'Balnarring']
nztracks = ['Te Aura']
hktracks = ['Sha Tin']
singtracks = ['Singapore']

df['Country'] = df['TName'] 
(["AUS" for c in austracks] + ["NZ" for c in nztracks] + ["HK" for c in nztracks] + ["SING" for c in nztracks])

Desired dataframe:

TName        Country
Ascot          AUS
Balnarring     AUS
Te Aura        NZ

>Solution :

Use Series.map if need for each list assign only one country:

austracks = ['Ascot', 'Balnarring']
nztracks = ['Te Aura']

d = {**dict.fromkeys(austracks,'AUS'), **dict.fromkeys(nztracks,'NZ')}

df['Country'] = df['TName'].map(d)
print (df)
        TName Country
0       Ascot     AUS
1  Balnarring     AUS
2     Te Aura      NZ