Write syntax to combine dataframes df1 and df2 based on common column named key

To combine two dataframes df1 and df2 based on a common column named key, you can use the merge function in pandas, a popular data manipulation library in Python. Here’s the syntax:

import pandas as pd

# Assuming df1 and df2 are your dataframes
combined_df = pd.merge(df1, df2, on='key')

Explanation:

• import pandas as pd: This line imports the pandas library, allowing you to use its functions and data structures.
• pd.merge(...): This function is used to combine two dataframes.
• on='key': Specifies the column to join on, which in this case is key.

This will create a new dataframe combined_df that includes all rows from df1 and df2 where the values in the key column match. If you want to perform different types of joins, you can specify additional parameters like how='inner', how='outer', how='left', or how='right'.

If you want to keep all entries from both dataframes (outer join), the syntax would be:

combined_df = pd.merge(df1, df2, on='key', how='outer')

This approach ensures that you have control over how the dataframes are combined based on your requirements.