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Final Submission For DataViz

✓ Published0🌍 Public
PPatrick-Houlihan
Last edited Dec 10, 2021
Created on Nov 17, 2021

This visualization combines a world map and an animated scatterplot to explore chess player transfer data. The map uses `d3.geoNaturalEarth1` and `d3.geoPath` with TopoJSON world-atlas data, allowing users to select up to 20 countries. The scatterplot, rendered with SVG circles, plots selected quantitative attributes like ELO ratings or birth year, with transitions from `d3.transition`. Menu selectors and brushing filter the data, updating map highlights and the plot’s title. The dataset is loaded via `d3.json` from a GitHub gist.

AI-generated description

Final Project

Dataset

The dataset can be found here

Project README

The readme chronicling work completed can be found here

What This Shows

This viz has a view of the world stacked on top of a scatterplot below showing the standard elo of a player relative to their standard elo, so it begins as a line of dots.

Features

Menus

When changing to another value using the menu selector, the columns of interest in the data change and the scatterplot reflects the new columns. This can be used to augment the scatterplot to see different relations between ratings and rankings by region. These chosen columns will be reflected as more filtering of data occurs through the country selector and brushing. The title of the scatterplot will update as the columns change.

Country Selector

Countries can be selected for data filtering by selecting the map above. By selecting up to 20 countries, each will be assigned a color that will be reflected below in the scatterplot points. These points are filtered by treating the selected country as the destination. By selecting Russia, the points shown in the graph will be those that have Russia as a destination.

Brushing

By selecting a region of points in the scatterplot below, the countries selected can be highlighted. These highlighted countries are only the countries that appear as destinations in the subset highlighted by brushing. This can be used to see a subset of points based on rating score, to see where strong players are going.

MIT Licensed

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