You're right! The default merge method in Pandas is an "inner join" similar to the one in database systems. It only includes rows where there is a match between the specified columns in both dataframes. If you want to perform other types of joins, such as "left", "right", or "outer" joins, you can specify the 'how' parameter in the pd.merge() function like this:

- For a left join: pd.merge(df1, df2, left_on='A', right_on='B', how='left')
- For a right join: pd.merge(df1, df2, left_on='A', right_on='B', how='right')
- For an outer join: pd.merge(df1, df2, left_on='A', right_on='B', how='outer')

These join types will handle non-matching rows differently, either including or excluding them in the resulting dataframe based on the join type.
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