How to remove duplicate rows based on multiple columns

You can remove duplicate rows based on multiple columns in Pandas by using the drop_duplicates method.

Here is an example of how you could remove duplicate rows based on multiple columns in a Pandas DataFrame:

import pandas as pd

# Create a sample DataFrame
df = pd.DataFrame({'A': [1, 2, 3, 4, 2, 3],
'B': [10, 20, 30, 40, 20, 30],
'C': [100, 200, 300, 400, 200, 300]})

# Remove duplicate rows based on columns 'A' and 'B'
df = df.drop_duplicates(subset=['A', 'B'])

# Print the result
print(df)

In this example, the drop_duplicates method is used to remove duplicate rows based on the values in the columns ‘A’ and ‘B’. The result is stored in a new DataFrame.