w3resource

Pandas DataFrame: Replace the ‘qualify' column contains the values 'yes' and 'no' with True and False

Pandas: DataFrame Exercise-17 with Solution

Write a Pandas program to replace the ‘qualify' column contains the values 'yes' and 'no' with True and False.

Sample DataFrame:
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']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
Values for each column will be:
name : ‘Suresh’, score: 15.5, attempts: 1, qualify: ‘yes’, label: ‘k’

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']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
df = pd.DataFrame(exam_data , index=labels)
print("Original rows:")
print(df)
print("\nReplace the 'qualify' column contains the values 'yes' and 'no'  with True and  False:")
df['qualify'] = df['qualify'].map({'yes': True, 'no': False})
print(df)

Sample Output:

Original rows:                                                          
   attempts       name qualify  score                                  
a         1  Anastasia     yes   12.5                                  
b         3       Dima      no    9.0                                  
c         2  Katherine     yes   16.5                                  
d         3      James      no    NaN                                  
e         2      Emily      no    9.0                                  
f         3    Michael     yes   20.0                                  
g         1    Matthew     yes   14.5                                  
h         1      Laura      no    NaN                                  
i         2      Kevin      no    8.0                                  
j         1      Jonas     yes   19.0                                  
                                                                       
Replace the 'qualify' column contains the values 'yes' and 'no'  with T
rue and  False:                                                        
   attempts       name  qualify  score                                 
a         1  Anastasia     True   12.5                                 
b         3       Dima    False    9.0                                 
c         2  Katherine     True   16.5 
d         3      James    False    NaN                                 
e         2      Emily    False    9.0                                 
f         3    Michael     True   20.0                                 
g         1    Matthew     True   14.5                                 
h         1      Laura    False    NaN                                 
i         2      Kevin    False    8.0                                 
j         1      Jonas     True   19.0                      

Python-Pandas Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Write a Pandas program to sort the data frame first by 'name' in descending order, then by 'score' in ascending order.
Next: Write a Pandas program to change the name 'James' to 'Suresh' in name column of the data frame.

What is the difficulty level of this exercise?

Test your Programming skills with w3resource's quiz.



Share this Tutorial / Exercise on : Facebook and Twitter

Python: Tips of the Day

Inserting if statements using conditional list comprehensions:

x = [1, 2, 3, 4, 5, 6]
result = []
for idx in range(len(x)):
    if x[idx] % 2 == 0:
        result.append(x[idx] * 2)
    else:
        result.append(x[idx])
result

Output:

[1, 4, 3, 8, 5, 12]
[(element * 2 if element % 2 == 0 else element) for element in x]

Output:

[1, 4, 3, 8, 5, 12]
[element * 2 for element in x if element % 2 == 0]

Output:

[4, 8, 12]