10/9/23, 9:33 PM Homework 1 - INFORMATION VISUALIZATION, Section A - NYU
Instructions
Homework 1
In this homework, you will write a visualization using D3 on observable to analyze a year of soccer matches. We will explore the Premier League dataset. This dataset contains useful information about soccer matches that happened during the last 10 years in the Premier League. For each year, you can find all the games played during the season and their associated statistics, such as the game score, goals scored by the home team, goals scored by the away team, ball possession, and more.
Questions (50%)
The goal of this homework is to help soccer analysts to answer the following questions:
1. Is it possible to recognize groups of teams that scored many goals but also suffer a lot of goals during the season?
2. Is it possible to recognize groups of teams that scored a few goals but also suffered only a few goals during the season?
3. Is it more likely that teams who scored more points in the league will have a better attack or a better defense?
Tasks (50%)
1. Sketching the visualization: Your first task is to sketch the visualization that you think will answer the
questions above. You can use any tool you like (PowerPoint, Photoshop, Gravit Designer, Hand drawing...) (10%).
2. Creating the visualization: Using observable and D3, you should complete the following tasks to generate your chart (40%):
2.1) Load and process the Premier League dataset (10%). You should write code that loads the Premier League dataset and process it to the following format: a list of objects containing the aggregated results for one season for the attribute shown above:
2.2) Create the scales to encode the data attributes that will help you create your visualization (10%).
Tip: We want to encode three attributes in our visualization: goals for, goals against, and the number of
points.
2.3) Create the axes of the visualization you are proposing to answer the questions above (10%). Submit Cancel
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10/9/23, 9:33 PM Homework 1 - INFORMATION VISUALIZATION, Section A - NYU
2.4) Bind the data to D3 using the selection join pattern discussed in the lab to render the data points (10%).
Observation: You should pick only one of the seasons provided on the dataset page.
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