Convincing Features
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– Description of your data
– The description with the initial questions
– For each question, a description of your visualization strategies, including data cleaning, transformation, visual encoding, etc.
– An explanation of the exploratory process of generating new questions and visualizations.
– Critical discussion of your visualization design (e.g. why you picked these encodings or this visualization)
– A reflection on the development process
Answer the questions by visualizing the dataset using R in an exploratory fashion
– Further, refine/propose questions and produce the visualization for those refined/proposed (more exploratory) questions (<= 10 questions in total). – It is a bonus if you can make your visualization interactive
– You can also try other visualization tools for the ultimate visualization if you want (optional, e.g., to make it more interactive). However, using R for the initial exploratory analysis is required. You should work closely with the “R Graphics Cookbook”.
Written report: Due date: 15th April 2022, maximum 10 pages
– Description of your data
– The description with the initial questions
– For each question, a description of your visualization strategies, including data cleaning, transformation, visual encoding, etc.
– An explanation of the exploratory process of generating new questions and visualizations.
– Critical discussion of your visualization design (e.g. why you picked these encodings or this visualization)
– A reflection on the development process
– You need to upload your R codes as well
An Example Case Study: House Price Visualization
– Pick a dataset of your interest: The land registry Price Paid Data includes information on all property sales in England and Wales that are sold for full market value and are lodged with us for registration. Format: tid,price,date,postcode,type,age,tenure,paon,saon,street,locality,city,district, county, category, record status
Assessment Criteria
Your written report and codes will be assessed concerning the following
criteria:
– the description of your data and research questions are clear and insightful;
– Appropriate visualizations are selected for each research question; – the R codes are developed in a manner that is readable and appropriate for the given visualization;
– A clear explanation of your visualization strategies and the exploratory process of generating new questions, and visualizations.
– Critical discussion of your visualization design and a reflection on the development process
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