TCS3123课程代写、代写Python程序

日期：2022-05-10 09:22

FACULTY OF ENGINEERING BUILT ENVIRONMENT AND INFORMATION TECHNOLOGY (FOEBEIT)

BACHELOR OF INFORMATION TECHNOLOGY (HONS)

FEBRUARY 2022 – MAY 2022

TCS3123 – DATA SCIENCE

COURSEWORK

DUE DATE : FRIDAY, 27 MAY 2022

? Assignments submitted after the due date will be considered late.

? Assignments submitted not later than two weeks after the due date will be marked, but the marks will

be capped to a maximum of 50%.

? Assignments submitted later than two weeks will be marked but carry zero mark.

? SEGi University, Kota Damansara takes allegations of plagiarism very seriously. Submissions involving

plagiarism will be marked but given zero mark.

Plagiarism is the attempt to pass off the work of another as your own. Information taken from the

work of others should be acknowledged by reference to obviate the charge of copying.

? Collusion is an academic irregularity within the SEGi University, Kota Damansara assessment

regulations. Any student found colluding in the production of any assessment will be subject to an

investigation with the imposition of any penalty deemed appropriate. Students must ensure they are

familiar with the definition of collusion.

TCS3123 – Data Science

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A. ASSIGNMENT OBJECTIVES

In this assignment, students should be able to :

i. Read, extract and clean a dataset from a web-based CSV source

ii. Manipulate the dataset using Python and Pandas to produce the required output

B. GENERAL INSTRUCTIONS

1. This is an individual assignment

2. Read the case study thoroughly. You may contact the lecturer for further explanation.

3. Develop the project using Python programming language. You may add external libraries

which you may find from your reading or references.

4. Write your code in the PROVIDED .ipynb file

C. SUBMISSION PROCEDURES

1. The assignment must be submitted via Blackboard no later than 11.59 pm on Friday, 27

May 2022.

2. Submission must be made in softcopy format.

3. Upload your file to the Blackboard using the provided submission link.

4. ONLY 1 SUBMISSION IS REQUIRED.

D. MARKING

1. Zero marks will be awarded if :

a. the file cannot be opened either by Anaconda Jupyter Notebook or Google Colab

b. the code cannot be executed due to syntax errors or other technical issues which

require the lecturer's intervention

c. the code produced runtime errors.

d. the file submitted is not in Jupyter Notebook format (.ipynb)

E. DELIVERABLES

1. One (1) Python code file – .ipynb file

a. Name format : <studentNo>.ipynb

TCS3123 – Data Science

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COVID 19 AEFI DATA

General Description

In this project, you will be working with a set of official data on the COVID-19 epidemic in Malaysia published

on the official Github account of Malaysia's Ministry of Health.

The project will explore data related to the adverse events following immunization (AEFI) or the side effects

of the COVID-19 vaccination.

As a data analyst, you are required to process the dataset and produce the required output based on the

scenario provided.

Dataset Overview

i. The dataset is accessible at: https://tinyurl.com/MyCovid19AEFI

ii. The dataset shows the number of AEFI reports made by the public after receiving their Dose 1 and

Dose 2 of the COVID-19 vaccines in 2021 and 2022

iv. The data are presented in 32 columns. Columns named with d1_x and d2_x are the AEFIs for Dose 1

and Dose 2, respectively.

iii. Twelve (12) AEFIs are recorded in the dataset :

a. Site pain

b. Site swelling

c. Site redness

d. Tiredness

e. Headache

f. Muscle pain

g. Weakness

h. Fever

i. Vomiting

j. Chills

k. Rash

l. Joint pain

v. For this project, the following assumptions are applicable:

a. The reports made in each AEFI are unique and do not overlap

b. The dataset is updated daily. For consistency, this project will only use data between January

2021 and 30 April 2022.

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Project Tasks

i. You are required to write Python code for each of the scenarios, questions or tasks mentioned in the

Jupyter Notebook (.ipynb) file

ii. Each code must be written in an individual cell. But all cells are interrelated, and thus incorrect code

in any cell will affect the output of the other cells.

Note :

i. Download the provided .ipynb file and write your answer/code in the file.

ii. Rename the file following the format mentioned in Section E of this worksheet