Compare two dataframes and return common values

I have 2 data frame , Need to fetch system_type column based on "Name" column of both dataframe .

I have 500000 rows of df1 as format

Name  Timestamp       usage  
AXCS   2022-01-01     5  
BGXD   2022-02-01     70  
HFSD   2022-03-01     45  
AEVC   2022-01-01     25  
BHRF   2022-02-01     12

and 550000 rows of df2 as

Name  System_Type  
HFSD      Dev  
BHRF      Test  
BGXD      Prod  
AEVC      Prod  
AXCS      Test

I used the following coding

pd.merge(df1, df2, on="Name")

It is taking much time to process , Is there another way/method to process it . Please advise

>Solution :

You can use df2 as a dict mapping:

df1['System_Type'] = df1['Name'].map(df2.set_index('Name')['System_Type'])
print(df1)

# Output
   Name   Timestamp  usage System_Type
0  AXCS  2022-01-01      5        Test
1  BGXD  2022-02-01     70        Prod
2  HFSD  2022-03-01     45         Dev
3  AEVC  2022-01-01     25        Prod
4  BHRF  2022-02-01     12        Test