reusable updating voroni scatterplot

D3 voronoi interaction

This example demonstrates how Voronoi diagrams improve hover interaction on a scatterplot by partitioning the chart area into cells around 50 randomly generated points. Clicking the chart reveals the Voronoi overlay, while moving the mouse highlights the nearest data point with a colored ring and displays its properties in a text output. The implementation uses D3 v4’s `d3.voronoi` layout with the `find()` method to locate the closest site, alongside `d3.scaleLinear`, `d3.axisBottom`, and `d3.axisLeft` for scales and axes. Points and axes are rendered as SVG elements within an HTML page.

FFrissAnalytics

76% match

projet vfinal

An interactive line chart visualizes player rankings from ATP tennis tournament match data. The visualization uses D3.js (v3) to parse CSV match results, track individual player progression through tournament rounds, and display the difference between player rankings and their opponents' rankings. Animated SVG paths with dashed and solid line styles represent player trajectories, while a reset button and tooltips provide interaction. The code also includes dataset files and uses the `d3.csv` function to load and process the external tennis tournament data.

projet v22

This visualization shows the ranking differences between winners and losers across the rounds of a Grand Slam tennis tournament, with each player represented as a line tracking their progress from the first round through the finals. The SVG chart uses two line styles—a solid steelblue line for wins and a dashed line for losses—and includes a reset button to reinitialize the animation. Built with D3 v3, the code loads ATP match data from a CSV file, parses player rankings, and constructs a parallel-coordinates-style plot with an interactive tooltip.

Point Distributions by Set Scores

This visualization compares tennis match statistics by showing the distribution of total points (and total shots) across different set scores, such as 6-0 or 7-5. Sets are grouped along the x-axis, with each group displaying an animated, exploding boxplot that highlights quartiles, outliers, and individual data points. The chart uses D3.js v3 with SVG and supports dynamic transitions when switching between point or shot metrics. Tooltips are configurable via d3-tip or Bootstrap popovers, and the data comes from parsed ATP and WTA match records.

TTennisVisuals

projet

This example visualizes the progression of tennis players through the rounds of a tournament, tracking the ranking difference against each opponent. The code loads match data from a CSV file and constructs a player-by-player record of wins and losses across seven rounds. Using D3.js v3, it processes the data to compute ranking gaps and structure results in a JSON object containing round, difference, status, and opponent information for each player. The visualization is built with SVG, though the current implementation logs the processed data to the console without rendering a chart.

projet v11

This example visualizes the progression of 128 tennis players through the rounds of a tournament, showing the difference in ranking between each player and their opponent at each stage. The code loads match data from a CSV file, processes it to track each player's path, and renders multiple line charts using D3.js version 3 with SVG. The charts display ranking differences across the rounds, with blue lines connecting data points for each player on a shared axis.

projet v20

This visualization tracks the progress of tennis players through a tournament, plotting the difference in their ranking against their opponents at each round. It shows the trajectory of individual players with lines, where wins and losses are marked, and a reset button allows the view to be refreshed. The visualization is built with D3 version 3 and uses SVG for rendering, with animation for interactive feedback. Data is loaded from CSV files containing tournament results, and the code uses D3's `d3.csv` function to parse the data, while custom logic calculates ranking differences.

74% match