Pandas DataFrame: Change the value in row 'd' to 11.5
Write a Pandas program to change the score in row 'd' to 11.5.
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']
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("\nOriginal data frame:")
print(df)
print("\nChange the score in row 'd' to 11.5:")
df.loc['d', 'score'] = 11.5
print(df)
Sample Output:
Original data frame: 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 Change the score in row 'd' to 11.5: 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 11.5 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
Explanation:
The above code first creates a pandas DataFrame 'df' from a dictionary exam_data using a list labels as the index. It then modifies the value in the 'score' column for row 'd' from NaN to 11.5 using the .loc indexer. Finally, it prints the modified DataFrame.
Python-Pandas Code Editor:
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Previous: Write a Pandas program to select the rows where number of attempts in the examination is less than 2 and score greater than 15.
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