日本欧洲视频一区_国模极品一区二区三区_国产熟女一区二区三区五月婷_亚洲AV成人精品日韩一区18p

COMP 315 代做、代寫 java 語言編程

時(shí)間:2024-03-10  來源:  作者: 我要糾錯(cuò)



1 Introduction
Assignment 1: Javascript
COMP 315: Cloud Computing for E-Commerce March 5, 2024
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 Ob jectives
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.
 Data name Title
First name
Middle name Surname Date of birth Age
Email
Note
This value may be either: Mr, Mrs, Miss, Ms, Dr, or left blank.
Each individual must have one. The first character is capitalised and the rest are lower case, with the exception of the first character after a hyphen.
This may be left blank.
Each individual must have one.
This must be in the format of DD/MM/YYYY.
All data were collected on 26/02/2024, and the age values should reflect this.
The format should be [first name].[surname]@example.com. If two individuals have the same address then an ID is added to differentiate them eg john.smith1, john.smith2, etc
Table 1: The attributes that should be stored for each user
         1

4 Initial setup
Create a Javascript file called Data Processing.js. Create a class within that file called Data Processing. 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.
7 Queries
Often, once the data has been processed, we perform a series of data analysis tasks on the cleaned data. Each of these queries are outlined in Table 2. Write a function with the name given in the ’Function name’ column, that carries out the query given in the corresponding ’Query description’. The answer should be returned by the function, and not stored locally or globally.
 Function name
most common surname average age
youngest dr
most common month
Query description
What is the most common surname name?
What is the average age of the users, given the values stored in the ’age’ column? This should be a real number to 3 significant figures.
Return all of the information about the youngest individual in the dataset with the title Dr.
What is the most common month for individuals in the data set?
        percentage titles
 What percentage of the dataset has each of the titles? Return this in the form of an array, following the order specified in the ’Title’ row of Table 1. This should included the blank title, and the percentage should be rounded to the nearest integer using bankers rounding.
  percentage altered
 A number of values have been altered between formatted user data and cleaned user data. What percentage of values have been altered? This should be a real number to 3 significant figures.
  Table 2: The queries that should be carried out on the cleaned data
2

8 Marking
The marking will be carried out automatically using the CodeGrade marking platform. A series of unit tests will be ran, and the mark will correspond with how many of those unit tests were successfully executed. Your work will be submitted to an automatic plagiarism/collusion detection system, and those exceeding a threshold will be reported to the Academic Integrity Officer for investigation regarding adhesion to the university’s policy https://www.liverpool.ac.uk/media/livacuk/tqsd/code-of-practice-on-assessment/appendix L cop assess.pdf.
9 Deadline
The deadline is 23:59 GMT Friday the 22nd of March 2024. Late submissions will have the typical 5% penalty applied for each day late, up to 5 days. Submissions after this time will not be marked. https: //www.liverpool.ac.uk/aqsd/academic-codes-of-practice/code-of-practice-on-assessment/
請(qǐng)加QQ:99515681  郵箱:99515681@qq.com   WX:codehelp 

標(biāo)簽:

掃一掃在手機(jī)打開當(dāng)前頁
  • 上一篇:代寫 CSSE7030 Connect 4
  • 下一篇:代做ACS61012、代寫ACS61012 Machine Vision
  • 無相關(guān)信息
    昆明生活資訊

    昆明圖文信息
    蝴蝶泉(4A)-大理旅游
    蝴蝶泉(4A)-大理旅游
    油炸竹蟲
    油炸竹蟲
    酸筍煮魚(雞)
    酸筍煮魚(雞)
    竹筒飯
    竹筒飯
    香茅草烤魚
    香茅草烤魚
    檸檬烤魚
    檸檬烤魚
    昆明西山國家級(jí)風(fēng)景名勝區(qū)
    昆明西山國家級(jí)風(fēng)景名勝區(qū)
    昆明旅游索道攻略
    昆明旅游索道攻略
  • NBA直播 短信驗(yàn)證碼平臺(tái) 幣安官網(wǎng)下載 歐冠直播 WPS下載

    關(guān)于我們 | 打賞支持 | 廣告服務(wù) | 聯(lián)系我們 | 網(wǎng)站地圖 | 免責(zé)聲明 | 幫助中心 | 友情鏈接 |

    Copyright © 2025 kmw.cc Inc. All Rights Reserved. 昆明網(wǎng) 版權(quán)所有
    ICP備06013414號(hào)-3 公安備 42010502001045

    日本欧洲视频一区_国模极品一区二区三区_国产熟女一区二区三区五月婷_亚洲AV成人精品日韩一区18p

              午夜视频一区在线观看| 久久免费视频在线| 国产一区二区福利| 美女视频黄a大片欧美| 亚洲少妇中出一区| 亚洲国产精品va在线观看黑人| 欧美激情一区在线观看| 久久精品欧美日韩精品| 在线中文字幕不卡| 亚洲国产视频一区二区| 国产欧美一区二区精品婷婷 | 韩日精品中文字幕| 国产精品高清网站| 欧美日韩成人一区| 欧美激情女人20p| 久久免费高清视频| 欧美一区二区三区四区视频| 亚洲视频电影在线| 日韩午夜在线视频| 日韩写真视频在线观看| 亚洲欧洲一区二区天堂久久| 激情综合久久| 国内自拍视频一区二区三区| 国产精品综合久久久| 国产精品欧美一区二区三区奶水 | 久久日韩粉嫩一区二区三区| 亚洲欧美区自拍先锋| 亚洲一区欧美二区| 亚洲视频1区| 亚洲欧美999| 亚洲中字在线| 欧美一区二区三区免费在线看| 亚洲一级黄色片| 亚洲欧美日韩网| 小黄鸭视频精品导航| 欧美资源在线| 久久青草福利网站| 欧美激情一区二区三区全黄| 欧美黑人在线观看| 国产主播一区二区| 亚洲人成网站色ww在线| 在线观看福利一区| 亚洲国产精品成人综合| 亚洲国产一区二区三区高清| 亚洲人体大胆视频| 亚洲精品一品区二品区三品区| 亚洲经典在线看| 中日韩美女免费视频网址在线观看 | 男人天堂欧美日韩| 欧美大片第1页| 国产精品va在线播放| 国产日韩精品入口| 影音国产精品| 一本色道久久综合一区| 欧美一级久久久| 免费不卡欧美自拍视频| 欧美日韩午夜在线视频| 国产午夜精品视频| 亚洲美女中文字幕| 欧美一区二区三区男人的天堂| 久久看片网站| 国产精品美女久久福利网站| 亚洲电影自拍| 午夜精品久久久久久久久久久久| 老司机aⅴ在线精品导航| 欧美三级日本三级少妇99| 国产一区二区精品在线观看| a4yy欧美一区二区三区| 久久精品国产欧美激情| 欧美日韩综合| 尹人成人综合网| 亚洲宅男天堂在线观看无病毒| 麻豆精品精华液| 国产日韩精品在线播放| 99精品国产在热久久下载| 久久久久久久久一区二区| 欧美一级淫片aaaaaaa视频| 久久久午夜视频| 国产精品人人爽人人做我的可爱| 亚洲品质自拍| 久久亚洲综合网| 国产欧美日韩精品专区| 在线一区观看| 欧美日韩精品久久久| 在线免费观看日本欧美| 欧美影院久久久| 国产精品美女久久久| 一区二区三区导航| 欧美另类在线观看| 亚洲国产毛片完整版| 麻豆精品在线视频| 黄色成人av| 欧美中文在线字幕| 国产精品一二| 午夜精品成人在线视频| 国产精品xxx在线观看www| 亚洲乱码视频| 欧美精品一二三| 99v久久综合狠狠综合久久| 欧美剧在线观看| 日韩一区二区免费高清| 欧美日韩成人在线观看| 999亚洲国产精| 欧美视频日韩视频在线观看| 一区二区三区福利| 久久嫩草精品久久久久| 亚洲东热激情| 欧美美女操人视频| 亚洲视频综合| 国产女优一区| 久久亚洲精品伦理| 亚洲人www| 国产精品女主播| 久久精品女人| 亚洲精品乱码久久久久久黑人 | 国产色婷婷国产综合在线理论片a| 亚欧成人在线| 18成人免费观看视频| 欧美高清在线一区| 亚洲性线免费观看视频成熟| 国产精品综合av一区二区国产馆| 欧美制服丝袜第一页| 尤物精品国产第一福利三区| 欧美激情欧美激情在线五月| 一区二区三区视频在线看| 国产精品一区二区你懂得| 美国三级日本三级久久99| 99亚洲视频| 国产一区二区三区四区hd| 欧美aaa级| 亚洲免费视频中文字幕| 亚洲高清网站| 国产精品视频男人的天堂| 蜜臀av一级做a爰片久久| 亚洲夜间福利| 最新亚洲电影| 国产精自产拍久久久久久| 老牛影视一区二区三区| 亚洲影视中文字幕| 亚洲激情影院| 国产一区二区精品丝袜| 欧美日韩伊人| 欧美高清日韩| 久久―日本道色综合久久| 亚洲在线视频网站| 99热免费精品| 亚洲国产天堂久久综合| 国产综合av| 国产欧美一区二区三区国产幕精品 | 正在播放亚洲| 国产精品青草久久久久福利99| 亚洲电影免费观看高清完整版在线 | 亚洲国产第一| 国产亚洲午夜| 欧美精品18videos性欧美| 亚洲国产精品久久久久| 一区二区三区在线观看视频| 欧美午夜不卡视频| 欧美成人在线免费视频| 久久综合国产精品台湾中文娱乐网| 亚洲天堂免费观看| 99这里有精品| 日韩午夜在线电影| 亚洲美女少妇无套啪啪呻吟| 一区二区在线视频| 黑丝一区二区三区| 国产亚洲成年网址在线观看| 国产亚洲va综合人人澡精品| 国产精品免费一区豆花| 国产精品视频999| 国产女精品视频网站免费| 国产精品亚洲综合色区韩国| 国产精品视频免费在线观看| 国产欧美视频一区二区三区| 国产麻豆精品在线观看| 国产日韩视频| 精品999成人| 亚洲黄色在线看| 99riav1国产精品视频| 一区二区电影免费在线观看| 亚洲视频一区二区| 亚洲欧美三级伦理| 久久av二区| 美女久久一区| 欧美日韩视频在线第一区| 国产精品久久久亚洲一区 | 欧美日韩福利视频| 国产精品草草| 国产午夜精品全部视频在线播放 | 欧美在线亚洲在线| 免费成人av| 欧美色欧美亚洲另类七区| 国产精品午夜电影| 在线观看日韩欧美| 亚洲天堂激情| 美女视频黄免费的久久| 国产精品扒开腿爽爽爽视频 | 玉米视频成人免费看| 一个色综合导航| 久久久久久亚洲精品中文字幕|