# (Python Example for Beginners)

Write a Pandas program to combine the columns of two potentially differently-indexed DataFrames into a single result DataFrame.

Test Data:

data1:
A   B
K0  A0  B0
K1  A1  B1
K2  A2  B2
data2:
C   D
K0  C0  D0
K2  C2  D2
K3  C3  D3

Sample Solution:

Python Code :

import pandas as pd

data1 = pd.DataFrame({'A': ['A0', 'A1', 'A2'],
'B': ['B0', 'B1', 'B2']},
index=['K0', 'K1', 'K2'])

data2 = pd.DataFrame({'C': ['C0', 'C2', 'C3'],
'D': ['D0', 'D2', 'D3']},
index=['K0', 'K2', 'K3'])

print("Original DataFrames:")
print(data1)
print("--------------------")
print(data2)

print("nMerged Data (Joining on index):")
result = data1.join(data2)
print(result)

Sample Output:

Original DataFrames:
A   B
K0  A0  B0
K1  A1  B1
K2  A2  B2
--------------------
C   D
K0  C0  D0
K2  C2  D2
K3  C3  D3

Merged Data (Joining on index):
A   B    C    D
K0  A0  B0   C0   D0
K1  A1  B1  NaN  NaN
K2  A2  B2   C2   D2

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