How do I merge two DataFrames in pandas using multiple keys?
An example of an AI chatbot conversation about merging DataFrames in pandas using multiple keys.
How do I merge two DataFrames in pandas using multiple keys?
You can use the merge() function in pandas and specify the keys in the on parameter. For example, pd.merge(df1, df2, on=['key1', 'key2']).
What if the keys have different names in each DataFrame?
In that case, you can use the left_on and right_on parameters. For example, pd.merge(df1, df2, left_on='key1', right_on='key2').
Can I merge on more than two keys?
Yes, you can merge on multiple keys by passing a list to left_on and right_on. For example, pd.merge(df1, df2, left_on=['key1', 'key2'], right_on=['key3', 'key4']).
What happens if there are duplicate keys?
If there are duplicate keys, the merge will result in a Cartesian product for those keys, meaning you'll get all combinations of the matching rows.
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