Skip to main content
SimilarExport ZIP
100%

Test2

✓ Published0🌍 Public
SSitanshu Rupani
Last edited Oct 14, 2021
Created on Oct 14, 2021

This interactive scatter plot visualizes player attributes from the FIFA19 English Premier League dataset, allowing users to compare quantitative metrics like Potential, Overall, Dribbling, and Acceleration via dropdown menus for both x and y axes. Built with D3 v6, it uses `scaleLinear` for quantitative axes and `scalePoint` for categorical positions, rendering circles with SVG and animating transitions using the `transition` API. The visualization updates smoothly with a 1000-millisecond duration, using data fetched from a GitHub gist.

AI-generated description

An interactive viz showcasing a scatter plot with user customisable axes.
The user can choose from a variety of choices of player attribute to tailor their analysis

This dataset contains attributes and demographic details of all players in the English Premier League. The dataset contains player attribute such as passing, shooting, crossing, etc. as seen in FIFA games.

The Source for this FIFA19 Player Dataset.

MIT Licensed

Similar vizzes

Loading thumbnail…

Adding Interaction for Scatter Plot - FIFA19 Players Dataset - Sitanshu Rupani

This interactive scatter plot visualizes player attributes from the FIFA19 English Premier League dataset, allowing users to dynamically select which quantitative or categorical attributes appear on the x- and y-axes via dropdown menus. The D3 v6 code uses `scaleLinear` and `scalePoint` for numeric and categorical mappings, with axes rendered through `axisLeft` and `axisBottom`. Data points are drawn as SVG circles with opacity, and transitions animate position changes and circle growth over 1000 milliseconds when axes change. The dataset is loaded as CSV from a GitHub Gist.

SSitanshu Rupani
88% match
Loading thumbnail…

D3 Scatter Plot - FIFA Dataset - Sitanshu Rupani

This visualization shows a D3.js scatter plot comparing FIFA 19 player potential against their current overall rating, using data from a public gist of the FIFA19 English Premier League dataset. Each circle represents a player, plotted with potential on the x-axis and overall on the y-axis. The code uses d3.csv for data loading, d3.scaleLinear for both axes, and d3.axisLeft and d3.axisBottom to render the axes. The SVG-based chart fills the full browser window and applies a fixed radius of five pixels to all data points.

SSitanshu Rupani
84% match
Loading thumbnail…

Testing D3 V 3.2

A scatterplot displays FIFA player attributes such as age, overall rating, and wage from a CSV dataset. The visualization uses D3 v5 with an SVG rendering approach. It employs `d3.csv` to load the data and `d3.scaleLinear` for axes, with `d3.axisBottom` and `d3.axisLeft` to render the scales. Circles positioned via `d3.forceSimulation` show player distribution, though the layout appears partially constrained.

PpramodK
83% match
Loading thumbnail…

Project Momentum - Sitanshu Rupani

This interactive scatterplot explores player attributes from a FIFA 19 English Premier League dataset. Users select X and Y axes from metrics like Potential, Overall, Dribbling, and Acceleration, and filter data by Preferred Foot, Nationality, or Club. The visualization uses React with d3.scaleLinear for axes and d3.scaleOrdinal for coloring, rendering marks as SVG circles. A color legend highlights specific filter categories on hover, fading other points to emphasize the selection.

SSitanshu Rupani
83% match
Loading thumbnail…

Interactive Scatter Plot

This interactive scatter plot visualizes top football league scorers using D3.js, letting users explore relationships between performance metrics like goals, shots, expected goals (xG), and minutes played. Three dropdown menus allow selection of the x-axis variable, y-axis variable, and season year (2016–2020). The chart renders circles colored by league, with player labels on hover and a color legend that supports filtering by league via click, with double-click to clear. All visual elements—including axes, scatter points, and legend—update in response to user input, creating a dynamic, animated exploration of the dataset. The visualization is built with D3 v7 and is responsive to container resizing.

Eeschuman20@gmail.com
80% match
Loading thumbnail…

Address Project Feedback - Sitanshu Rupani

This scatterplot visualizes the relationship between FIFA 19 players’ overall ratings and their weekly wages, using D3.js v4 with SVG rendering. It plots each player as a circle, with data sourced from a CSV of English Premier League players. Users can brush over the plot to highlight specific players, which triggers a table below showing their name, club, nationality, and potential. The visualization uses `d3.brush()` for selection, `d3.axisBottom` and `d3.axisLeft` for axes, and `d3.scaleLinear` for positioning, dynamically updating the table via `d3.selectAll('.brushed')`.

SSitanshu Rupani
79% match
Loading thumbnail…

Make Something with Brushing - Sitanshu Rupani

This visualization uses a scatterplot to show the relationship between Overall and Potential ratings for FIFA 19 English Premier League players. Users can brush an area of the plot with d3.brush, which highlights selected circles in pink while dimming others, and upon releasing the brush, a table appears listing the player names, Overall, and Potential values for the brushed points. The plot is rendered with SVG, using d3.csv to load the dataset and d3.scaleLinear for axes.

SSitanshu Rupani
78% match
Loading thumbnail…

Viz_9

This interactive scatter plot displays FIFA player statistics across six national teams (ARG, BRA, ESP, FRA, GER, ITA), letting users compare any two attributes via dropdown menus. The visualization uses React with D3 v5 scales (d3.scaleLinear) to map data to SVG circles, with tooltips showing x-values. Data loads from a CSV via d3.csv. Users can dynamically switch axes, and the plot renders with custom axis components and formatted tick labels using d3.format.

NNikithakatta30
78% match