Merging two DataFrames on a single column in Pandas

Last update on December 21 2024 07:41:34 (UTC/GMT +8 hours)

Pandas: Custom Function Exercise-1 with Solution

Write a Pandas program to merge two DataFrames on a single column.

In this exercise, we have merged two DataFrames on a single common column using pd.merge().

Sample Solution :

Code :

import pandas as pd

# Create two sample DataFrames
df1 = pd.DataFrame({
    'ID': [1, 2, 3],
    'Name': ['Selena', 'Annabel', 'Caeso']
})

df2 = pd.DataFrame({
    'ID': [2, 3, 4],
    'Age': [25, 30, 22]
})

# Merge the two DataFrames on the 'ID' column
merged_df = pd.merge(df1, df2, on='ID')

# Output the result
print(merged_df)

Output:

   ID     Name  Age
0   2  Annabel   25
1   3    Caeso   30                   

Explanation:

• Created two DataFrames df1 and df2 with a common column 'ID'.
• Used pd.merge() to merge the two DataFrames on the 'ID' column.
• The result includes rows where 'ID' exists in both DataFrames, joining on the common values.

Python-Pandas Code Editor:

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