I have two datasets that contains domain names:
df1:
varA domains
123 www.google.com
456 www.ebay.com
789 www.amazon.com
101 www.nbc.com
....
df2:
urls varB
www.cnn.com xsd
www.ebay.com wer
www.nbc.com xyz
www.amazon.com zyx
....
I need to populate urls values in df2 with varA values from df1 for the matching domains/urls, so the output would look like this:
urls varA varB
www.ebay.com 456 wer
www.nbc.com 101 xyz
www.amazon.com 789 zyx
....
All of the domains in df2 that do not have a matching domain in df1 should be removed.
I have this code:
target_cols = ['domains', 'urls', 'varB', 'varA']
df2.merge(df1[target_cols], on='urls', how='inner')
The code is generating an error.
How do I fix it? Any alternative solutions that can work?
The error is because keys on which you are merging do not have same name This will work
pd.merge(df1, df2, left_on = 'domains', right_on = 'urls', how = 'inner').drop('domains', axis = 1)
varA urls varB
0 456 www.ebay.com wer
1 789 www.amazon.com zyx
2 101 www.nbc.com xyz