Best way to find matched record using two Data frames in Python

Question

Actually I am writing a script to find matched records using df1 and df2. Now I am doing this by iterating both df1 and df2 in O N^2.

for i,row1 in df1.iterrows:

   for j,row2 in df2.iterrows:

      if row1['fname'] == row2['fname'] 
        and row1['lname'] == row2['lname'] 
        and row1['email'] == row2['email']:
        #matched

I want to make it in more efficient way. Anyone can guide me which algorithm or Python thing I can use for it.

Mayank Porwal · Accepted Answer · 2018-10-18 09:38:56Z

1

Consider using merge.

pd.merge(df1, df2, on=(['fname','lname','email']), how='inner')

answered Oct 18, 2018 at 9:38

Mayank Porwal

34.2k9 gold badges45 silver badges65 bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

Mayank Porwal Over a year ago

@U.Malik merge command joins both dataframes df1 and df2 on 3 columns fname,lname,email using inner join. This will basically return only those records which are present in both dataframes. Let me know if need further explanation.

Collectives™ on Stack Overflow

Best way to find matched record using two Data frames in Python

1 Answer 1

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related