2022-2-32146-Ass2-v11b-update26Sep2022 2022-11-2 232152 4.pdf

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1、2022 Spring DVVA:Assignment Two Page 1 32146 Data Visualization and Visual Analytics-2022 Spring SemesterAssignment Two:Advanced Data Visualisation(30%)individual This assignment aims to ensure that students understand the high-dimensional data types and format.The high-dimensional data visualisatio

2、ns required using different interaction and illustration tools.This assignment mimics an analysts role in real life.The assignment also ensures that students understand the various visualisation techniques when dealing with other forms of high-dimensional data.Students must analyse and visualise the

3、 Tennis dataset containing US Open championship matches,which includes 141 years of championship matches,both men and women,between 1881 and 2021.Dataset has various data types and forms,including year,gender,champions name,nationality,champion seed,match time,runner-ups name,nationality,and score.S

4、tudents have to use the required method to analyse and visualise,which needs to convert into a different format for comparison.15 pages,including tables and graphs,excluding bibliography.Page guideline:General Requirements:Students must use the US Open Tennis dataset,which can be found and downloade

5、d from Canvas.After downloading the dataset,make sure to rename the dataset as Student-ID-Ass2.xlsx.The US Open Tennis dataset styles are as follows.There are three blank columns for Champion Seed,Mins,and Runner-up Seed.Those three values hadnt been appropriately recorded before 1945,so we removed

6、them from the dataset.Two columns have been created and filled for champion and runner-up countries because Tableau doesnt recognise the nationality code.In the scoreboard field,data is the text format that couldnt compare.We have converted it into 10 x new columns representing each set of win and l

7、oss.Students should create several new data sheets inside the Student-ID-Ass2.xlsx file to import them into Tableau apps for visual analysis.Several visualisation graphs need to be created,including Treemap,Parallel 2022 Spring DVVA:Assignment Two Page 2 coordinates,Geo-map,etc.Students must complet

8、e the champions win rate for champion and runner-up performance analysis and visualisation.Storytelling is the key when attempting sports data visualisation in this assignment.The visualisation should explore the whole dataset at a sufficiently specific level to enable the reader to understand the a

9、ttributes and trends of the particular champions performance against the different players.Students must cite all data sources and references used.The weighting of this assignment is 30%of a students overall final grade.Detailed Requirements:1.Exclusive summarises the US Open Tennis dataset and indi

10、cates datas format,value and characteristics.Explains the visualisation techniques used in this assignment.The dataset with Tableau files has to submit with an assignment report.(5 marks)2.Select the different visualisation techniques to analyse players nationalities,genders,and performances in time

11、 series and group by nation.Illustrate the data graphically in time series,genders,or country by using designed a)layout techniques;b)rescaling axes techniques;c)labelling techniques;d)trends techniques;e)highlight and commands inserting storytelling techniques.Those visualisations should base on th

12、e concept of tennis players performance,including 1.Treemap Analyse the players pattern between the champions nationality,gender,score,etc.2.Parallel coordinate Analyse the relationship between time,champions nationality,gender,score,etc.3.Geographic Map Analyse the champions location and performanc

13、e.4.Win rate performance chart Analyse performance patterns of top players(players who won 5 or more championships,both men and women).Excel files,Tableau files or other visualisation apps should be saved and zipped into a file(Student-ID-Ass2.zip).And those analysis graphs should be used in the rep

14、ort as well.Weight is 15 marks.3.Write a report explaining how you dealt with high-dimensional data in your data visualisation,particularly in combining multi-dimensional data.Describe the graphic attribute designs and labelling techniques used in your data visualisation and how they enhanced the re

15、adability and storytelling of the visualisation.Highlights any trends and breakthrough analysis you have discovered through the data visualisation process,particularly the top players performance patterns in the visual comparison chart.Concludes and summarises the advantages of Tableau or other visu

16、alisation apps you have used.(10 marks)Submission method:The assignment must be submitted via UTS Canvas in PDF or Doc format for your report(Student-ID-Ass2.docx/or pdf)and zipped Excel file+Tableau files(Student-ID-Ass2.zip).The fake data results in ZERO for this assignment.There will be a link to the submission form set up on the subject homepage.Note that late submission will incur a penalty of 10%.