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Consider the following table of data containing module marks for 5 students: Student_ID CCIT4020 CCIT4088 CCIT4092 20201234 64 29 81 20076236 16 21 42 20201224 70 62 58 20213134 16 17 51 20201299 79 50 61

Consider the following table of data containing module marks for 5 students: Student_ID CCIT4020 CCIT4088 CCIT4092 20201234 64 29 81 20076236 16 21 42 20201224 70 62 58 20213134 16 17 51 20201299 79 50 61

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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**using jupyter notebook (Python)**

 

Task 1 Consider the following table of data containing module marks for 5 students: Student_ID CIT4020 CCIT4088 CCIT4092 20201234 64 29 81 20076236 16 21 42 20201224 70 62 58 20213134 16 17 51 20201299 79 50 61 1. Create five lists. Name it as student1, student2, .. , student5. Each of the list contains the Student ID, marks of CCIT4020, marks of CCIT4088 and marks of CCIT4092 of the student. 2. Create a numpy array named data which is a 2D array contains the 5 lists formed in Step (1). 3. Create a list named column_names based on the column header of the given table. 4. Create a DataFrame named df with column_names and data. 5. Display df. 6. Display only the list of student IDs. 7. Using the function iloc (), extracts only the marks of the students from df. Stores the result in a variable named marks. 8. Show the summary statistics of the extracted frame marks. 9. Calculate the average of each of the course using marks. Stores the result in avg. 10. Visualize the average of each of the course using the pandas build-in function plot() with kind=' bar'.
Transcribed Image Text:Task 1 Consider the following table of data containing module marks for 5 students: Student_ID CIT4020 CCIT4088 CCIT4092 20201234 64 29 81 20076236 16 21 42 20201224 70 62 58 20213134 16 17 51 20201299 79 50 61 1. Create five lists. Name it as student1, student2, .. , student5. Each of the list contains the Student ID, marks of CCIT4020, marks of CCIT4088 and marks of CCIT4092 of the student. 2. Create a numpy array named data which is a 2D array contains the 5 lists formed in Step (1). 3. Create a list named column_names based on the column header of the given table. 4. Create a DataFrame named df with column_names and data. 5. Display df. 6. Display only the list of student IDs. 7. Using the function iloc (), extracts only the marks of the students from df. Stores the result in a variable named marks. 8. Show the summary statistics of the extracted frame marks. 9. Calculate the average of each of the course using marks. Stores the result in avg. 10. Visualize the average of each of the course using the pandas build-in function plot() with kind=' bar'.
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