COMP315 JavaScript Cloud Computing for E Commerce

作者：小丑西瓜9 | 2024-03-27 10:00:20

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Assignment 1: Javascript

1 Introduction

A common task in cloud computing is data cleaning, which is the process of taking an initial data set that may contain erroneous or incomplete data, and removing or fixing those elements before formatting the data in a suitable manner. In this assignment, you will be tested on your knowledge of JavaScript by implementing a set of functions that perform data cleaning operations on a dataset.

2 Objectives

By the end of this assignment, you will:

• Gain proficiency in using JavaScript for data manipulation.

• Be able to implement various data cleaning procedures, and understand the significance of them.

• Have developed problem-solving skills through practical application.

3 Problem description

For this task, you have been provided with a raw dataset of user information. You must carry out the following

series of operations:

• Set up a Javascript class in the manner described in Section 4 .

• Convert the data into the appropriate format, as highlighted in Section 5

• Fix erroneous values where possible e.g. age being a typed value instead of a number, age being a real number instead of an integer, etc; as specified in Section 6 .

• Produce functions that carry out the queries specified in Section 7 .

4 Initial setup

Create a Javascript file called Data P rocessing.js . Create a class within that file called Data P rocessing .

Write a function within that class called load CSV that takes in the filename of a csv file as an input, eg load CSV (” User Details ”). The resulting data should be saved locally within the class as a global variable called raw user data . Write a function called format data , which will have no variables are a parameter. The functionality of this method is described in Section 5 . Write a function called clean data , which will also have no parameters. The functionality of this method is similarly described in Section 6 .

5 Format data

Within the function format data , the data stored within raw user data should be processed and output to a global variable called formatted user data . The data are initially provided in the CSV format, with the delimiter being the ’,’ character. The first column of the data is the title and full name of the user. The second and third columns are the date of birth, and age of the user, respectively. Finally, the fourth column is the email of the user. Ensure that the dataset is converted into the appropriate format, outlined in Table 1 . This

data should be saved in the JSON format (you may use any built in JavaScript method for this). The key for each of the values should be names shown in the ’Data name’ column, however converted to lower case with an

underscore instead of a space character eg ’first name’.

6 Data cleaning

Within the function clean data , the data cleaning tasks should be carried out, loading the data stored in formatted user data . All of this code may be written within the clean data function, or may be handled by a series of functions that are called within this class. The latter option is generally considered better practice.

Examine the data in order to determine which values are in the incorrect format or where values may be missing.

If a value is in the incorrect format then it must be converted to be in the correct format. If a value is missing or incorrect, then an attempt should be made to fill in that data given the other values. The cleaned data should be saved into the global variable cleaned user data.my wechat：_0206girl

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