How can we combine two dataframes that complement each other, and do not contain any missing values where a value is present?

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We can combine the two dataframes using the merge() function in pandas. This function can combine two dataframes based on common columns or indices. To ensure that we only combine the rows that complement each other and do not contain any missing values where a value is present, we can use the inner join option in the merge() function.

For example, if we have two dataframes df1 and df2 with a common column 'id', we can merge them using the following code:

combined_df = pd.merge(df1, df2, on='id', how='inner')

This will create a new dataframe called combined_df that contains only the rows where there is a match between the 'id' column in both dataframes, and where there are no missing values in either dataframe where a value is present.

The inner join option ensures that we only retain the rows where there is a match between the two dataframes. Any rows that exist in one dataframe but not the other will be discarded.