How do I merge two DataFrames on multiple columns in pandas?

How do I merge two DataFrames on multiple columns in pandas?

You can use the merge() function in pandas and specify the columns to merge on using the on parameter. For example:

import pandas as pd

df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
df2 = pd.DataFrame({'A': [1, 2, 3], 'C': [7, 8, 9]})

merged_df = pd.merge(df1, df2, on=['A'])

What if the column names are different in both DataFrames?

You can use the left_on and right_on parameters to specify different column names. For example:

merged_df = pd.merge(df1, df2, left_on='A', right_on='B')

Can I merge on more than two columns?

Yes, you can merge on multiple columns by passing a list to the on, left_on, or right_on parameters. For example:

merged_df = pd.merge(df1, df2, on=['A', 'B'])

What happens if there are duplicate values in the merge columns?

If there are duplicate values, the resulting DataFrame will have a Cartesian product of the matching rows. You may want to handle duplicates before merging.