T9_Q1_Aadesh

Ssirichandana017@gmail.com

Activity9Ques-1

This pie chart visualizes tennis players' ratings, displaying each player's name and their total overall rating as slices. The chart uses D3 v5 (d3.pie, d3.arc, d3.scaleOrdinal) to generate the pie geometry, color the slices, and position labels at each slice's centroid. The data is fetched as CSV from a GitHub gist. Hovering over a slice reveals a tooltip with the player's name, average score, and total rating, while a legend on the left lists all players and their ratings. The chart is rendered as SVG with custom styling.

Aaadesh.pranesh@gmail.com

T9Q1

This pie chart shows the mortality rate from mental health deaths across different countries in the United States. The visualization uses D3 v5 with a standard SVG rendering approach, employing `d3.pie()` and `d3.arc()` to generate the chart segments. Each slice is colored using `d3.scaleOrdinal()`, with country names labeled directly on the segments and a legend on the right displaying country names and their corresponding death counts. The data is loaded asynchronously from a CSV file hosted on GitHub.

Ssriyaalugupalli@my.unt.edu

A7-Q1

This visualization displays a pie chart comparing the population of ten countries for the year 2000. Built with React and D3 v5, it renders an SVG with colored slices, percentage labels, and a legend. The code uses d3.pie, d3.arc, and d3.schemeCategory10 for the chart, while data is loaded via d3.csv and transformed in a custom useData hook.

Ssudhimaganti.49@gmail.com

Activity 7.1

This pie chart displays the total overall ratings of tennis players, with each slice representing an individual player and its size proportional to their rating. A legend and labels identify each player, while hovering reveals a tooltip with the player's country, average score, and total rating. Built with D3 v5, the visualization uses the `pie` and `arc` functions to generate the chart, `scaleOrdinal` for coloring, and custom mouseover events for interactivity. The data is loaded from a CSV file hosted as a GitHub gist.

AK's_PieChart

This D3.js pie chart visualizes social media usage percentages across ten countries, with each slice labeled by its corresponding value. The chart uses `d3.pie` to compute arc segments, `d3.arc` for generating the path geometry, and `d3.scaleOrdinal` to map categorical colors to each country. Data is loaded asynchronously from a CSV file using `d3.csv`. A legend on the right pairs each country with its percentage, and all text labels are formatted using `d3.format`. The SVG canvas is 960 by 500 pixels with a black background.

Aamulyakannam

shish's ice7-piechart

This pie chart displays the top 10 countries by world population share in 2025, with each slice labeled by country name and accompanied by a color-coded legend. Built with d3.v7 and rendered as SVG, it loads data from a CSV file, sorts by the World_Share column, and uses `d3.pie()` to generate the arcs. Slice colors come from `d3.scaleOrdinal()` with the `d3.schemeCategory10` palette, while `d3.arc()` defines the pie geometry. The visualization includes stroke outlines and text labels positioned at arc centroids, with a legend appended to the right of the chart.

SSai Shishir Koppula

Bbhavanadupati3@gmail.com

Activity-7 Q1

This pie chart visualizes tennis players’ overall ratings, with each slice representing a player and labeled with their name and rating. The chart includes a color-coded legend and an interactive tooltip that displays each player’s average score on hover. The visualization loads CSV data from a GitHub gist and uses D3 v5 APIs including `d3.pie`, `d3.arc`, `d3.scaleOrdinal`, and `d3.format` to generate and style the SVG elements with mouse event handlers.

Vvinaykollapudi@my.unt.edu

act 7 q1

This example displays a pie chart of the top 10 countries by 2022 population, with a legend alongside the slices. It uses D3.js v7 APIs including `d3.csv`, `d3.pie`, `d3.arc`, and `d3.scaleOrdinal` to load and process the dataset, generate the pie geometry, and assign categorical colors. The chart is rendered as SVG with text labels positioned via arc centroids, while a legend is built manually with `rect` and `text` elements. Data comes from a CSV hosted on GitHub.