Vectorized way of checking dataframe values (as key, value tuple) against a dictionary?

Question

I'd like to create a column in my dataframe that checks whether the values in one column are the dictionary values of another column which comprises the dictionary keys, like so:

In [3]:
df = pd.DataFrame({'Model': ['Corolla', 'Civic', 'Accord', 'F-150'],
                   'Make': ['Toyota', 'Honda', 'Toyota', 'Ford']})
dic = {'Prius':'Toyota', 'Corolla':'Toyota', 'Civic':'Honda', 
       'Accord':'Honda', 'Odyssey':'Honda', 'F-150':'Ford', 
       'F-250':'Ford', 'F-350':'Ford'}
df

Out [3]:
     Model    Make
0  Corolla  Toyota
1    Civic   Honda
2   Accord  Toyota
3    F-150    Ford

And after applying a function, or whatever it takes, I'd like to see:

Out [10]:
     Model    Make   match
0  Corolla  Toyota    TRUE
1    Civic   Honda    TRUE
2   Accord  Toyota   FALSE
3    F-150    Ford    TRUE

Thanks in advance!

Edit: I tried making a function that is passed a tuple which would be the two columns, but I don't think I'm passing the arguments correctly:

def is_match(make, model):
  try:
    has_item = dic[make] == model
  except KeyError:
    has_item = False
  return(has_item)

df[['Model', 'Make']].apply(is_match)

results in:
TypeError: ("is_match() missing 1 required positional 
argument: 'model'", 'occurred at index Model')

Answer 1

You can using map

df.assign(match=df.Model.map(dic).eq(df.Make))
Out[129]: 
     Make    Model  match
0  Toyota  Corolla   True
1   Honda    Civic   True
2  Toyota   Accord  False
3    Ford    F-150   True