How to apply inner join on two DataFrames?

Hello everyone, I am seeking your help in writing correct code to apply an inner join on two DataFrames. I am currently working on a project that requires me to merge two DataFrames based on a common column. However, I am relatively new to coding and struggling with the syntax for applying an inner join in Python.

Here is the code I am getting issues with:

import pandas as pd

# create two sample dataframes
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})
df2 = pd.DataFrame({'A': [2, 3, 4], 'B': [5, 6, 7], 'D': [8, 9, 10]})

# join the two dataframes on columns A and C with an inner join
result = pd.merge(df1, df2, on=['A', 'C'], how='inner')

# display the joined dataframe

KeyError: 'C'

I would appreciate any guidance or examples of correct code for applying an inner join on two DataFrames in Python.

1 Like

Hey @nimrah, it is giving a KeyError that means at the time of merging, it is unable to find the same column in both dataframes. You can remove this error by using the below solution:

It seems that your code is raising a KeyError which indicates that the columns on which you’re trying to join the two dataframes are not common. A possible solution to this problem is to set the indexes of both dataframes to the common columns you want to join on. Here’s an example code that demonstrates this approach:

In this code, we use the join() function with an inner join type, which means that only the rows with common indexes are included in the output.