Compare columns in Pandas between two unequal size Dataframes for condition check

I have two pandas DF. Of unequal sizes. For example :

Df1
id     value
a      2
b      3
c      22
d      5 

Df2 
id     value
c      22
a      2

No I want to extract from DF1 those rows which has the same id as in DF2. Now my first approach is to run 2 for loops, with something like :

x=[]
for i in range(len(DF2)):
    for j in range(len(DF1)):
        if DF2['id'][i] == DF1['id'][j]:
          x.append(DF1.iloc[j])    

Now this is okay, but for 2 files of 400,000 lines in one and 5,000 in another, I need an efficient Pythonic+Pnadas way

import pandas as pd

data1={'id':['a','b','c','d'],
       'value':[2,3,22,5]}

data2={'id':['c','a'],
       'value':[22,2]}

df1=pd.DataFrame(data1)
df2=pd.DataFrame(data2)
finaldf=pd.concat([df1,df2],ignore_index=True)

Output after concat

   id   value
0   a   2
1   b   3
2   c   22
3   d   5
4   c   22
5   a   2

Final Ouput

finaldf.drop_duplicates()

    id  value
0   a   2
1   b   3
2   c   22
3   d   5