Distinctive Analytics

Dataset Information

You have a dataset containing the subject marks (physics, chemistry, math, and biology) of students. Each row represents a student, and each column represents the marks in a specific subject.

Dataset Example:

Quiz Questions:

1. Calculate Average Marks:

   – Create a Python function to calculate the average marks for each subject (physics, chemistry, math, biology) across all students in the dataset.

Question:

Create a Python function to calculate the average marks for each subject (physics, chemistry, math, biology) across all students in the dataset.

Answer: Python

2. Overall Average Performance:

  Write a Python script to find the overall average marks of each student across all subjects. 

Question:

Write a Python script to find the overall average marks of each student across all subjects.

Answer: Python

3. Performance Summary:

   – Create a summary report that includes the overall average marks, the subject with the best average performance, and the best-performing student. Display this information in a clear and readable format.

Question:

Create a summary report that includes the overall average marks, the subject with the best average performance, and the best-performing student. Display this information in a clear and readable format.

Dataset for pivot

This dataset represents the marks of students (S1, S2, S3) in different subjects (Physics, Chemistry, Math, Biology). The ‘Student’ column represents the student IDs, the ‘Subject’ column represents the subjects, and the ‘Mark’ column represents the corresponding marks.

4. Pivot Table – Subject-wise Average:

Question: Create a pivot table to display the average marks for each subject across all students.

5. Pivot Table – Student-wise Subject Performance:

Question: Generate a pivot table that shows the marks of each student in physics, chemistry, math, and biology.