Pandas DataFrame: Calculate the mean of all students' scores

Last update on December 21 2024 07:41:52 (UTC/GMT +8 hours)

Write a Pandas program to calculate the mean of all students' scores. Data is stored in a dataframe.

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("\nMean score for each different student in data frame:")
print(df['score'].mean())

Sample Output:

Mean score for each different student in data frame:                   
13.5625                         

Explanation:

The above code first creates a Pandas DataFrame 'df' from a dictionary 'exam_data' with row labels 'labels'. It then computes and prints the mean value of the 'score' column of the DataFrame using the mean() method of Pandas.

The 'score' column contains numerical values with one missing value represented by numpy.nan. The mean() method automatically excludes the missing value from the computation.

Python-Pandas Code Editor:

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