Pandas Example – Write a Pandas program to sort a given DataFrame by two or more columns

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(Python Example for Beginners)

 

Write a Pandas program to sort a given DataFrame by two or more columns.

 

Sample Solution :

Python Code :


import pandas as pd
import numpy as np

exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}

df = pd.DataFrame(exam_data)
print("Original DataFrame:")
print(df)
print("nSort the above DataFrame on attempts, name:")

df = df.sort_values(['attempts', 'name'], ascending=[True, True])
print(df)

Sample Output:

Original DataFrame:
   attempts       name qualify  score
0         1  Anastasia     yes   12.5
1         3       Dima      no    9.0
2         2  Katherine     yes   16.5
3         3      James      no    NaN
4         2      Emily      no    9.0
5         3    Michael     yes   20.0
6         1    Matthew     yes   14.5
7         1      Laura      no    NaN
8         2      Kevin      no    8.0
9         1      Jonas     yes   19.0

Sort the above DataFrame on attempts, name:
   attempts       name qualify  score
0         1  Anastasia     yes   12.5
9         1      Jonas     yes   19.0
7         1      Laura      no    NaN
6         1    Matthew     yes   14.5
4         2      Emily      no    9.0
2         2  Katherine     yes   16.5
8         2      Kevin      no    8.0
1         3       Dima      no    9.0
3         3      James      no    NaN
5         3    Michael     yes   20.0

 

Pandas Example – Write a Pandas program to sort a given DataFrame by two or more columns

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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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