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

By on Monday, April 12, 2021

(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

 

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

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Two Machine Learning Fields

There are two sides to machine learning:

  • Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
  • Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
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