activity7_Q1

Ccharankumarreddyveeramreddy@my.unt.edu

Activity 7.1_Question 1

A pie chart displays the distribution of penguin species from a CSV dataset, showing counts for each species with labeled segments. The visualization uses D3 v6 APIs including `d3.csv` for data loading, `d3.pie` and `d3.arc` for generating the pie geometry, and `d3.scaleOrdinal` with `schemeCategory10` for colors. Each segment is rendered as an SVG path with a white stroke, and text labels using `arcPath.centroid` position the species name and count at the center of each slice.

AAP19110020041-Pavan Kumar

Activity 6

This pie chart visualization displays the proportional breakdown of categorical data loaded from a remote CSV file. Constructed with D3.js v7, the SVG graphic uses `d3.pie` to compute arc segments and `d3.arc` for path geometry, with `d3.scaleOrdinal` and `d3.schemeCategory10` providing categorical colors. A legend, including color swatches and labels, is positioned on the left side, while the chart title appears above. The code loads data via `d3.csv` and renders all elements as SVG paths and text nodes.

Kkeerthana11.mcs@gmail.com

Activity7_Q1

A pie chart visualizes the distribution of car classes from a CSV dataset, showing the proportions of categories like 'unacc', 'acc', 'vgood', and 'good' as colored slices with percentage labels. The chart uses D3.js (version 7.8.5) with the `d3.pie`, `d3.arc`, and `d3.scaleOrdinal` APIs to compute and render the pie geometry and colors. A legend on the right lists each class with its count. The SVG is built programmatically, with data loaded asynchronously from a GitHub-hosted CSV file.

Vvishnutejareddyambati@my.unt.edu

Activity 7 Q1

This example shows a pie chart that visualizes categorical data loaded from a remote CSV file, with each slice colored using a categorical color scale and a legend pairing colors with category and subcategory labels. The chart is rendered as SVG using D3.js v6, where the `d3.pie()` generator computes slice angles and `d3.arc()` creates the path shapes. Data is fetched via `d3.csv`, and the color mapping uses `d3.scaleOrdinal` with `d3.schemeCategory10`. The code also adds axis labels (X and Y) that are not tied to the pie chart, acting as placeholders within the SVG layout.

Activity 7 Q2

This visualization presents the distribution of penguin species in a dataset, breaking down the counts of each species in a simple pie chart. The chart uses D3 v7’s pie and arc generators to compute and draw the proportional slices, with colors assigned by scaleOrdinal and schemeCategory10. The code loads data from a CSV file, groups records by species to calculate counts, and renders the pie with white stroke separations and labels placed at each arc’s centroid. A manual legend and red axis annotations are added for context.

Hhui249378@gmail.com

Ssaikarthiknimmagadda@gmail.com

act7_q1piechart

This pie chart visualizes the distribution of flower species from a CSV dataset, displaying the proportion of each species with colored slices and labels. The chart is built with D3.js v7, using `d3.pie()` to compute arc angles and `d3.arc()` to generate SVG paths, with an ordinal color scale assigning light green, blue, and orange to species groups. A legend on the right side, rendered as SVG rectangles and text, maps each color to its corresponding species, while `d3.rollups` aggregates the raw data into species counts before drawing.

Activity 7_Q1

A pie chart displays the proportional spending across unnamed categories, with each slice color-coded and paired with a legend on the right side. The visualization loads CSV data from a GitHub repository using `d3.csv`, then constructs the chart with `d3.pie()` and `d3.arc()`. Color assignment uses `d3.scaleOrdinal` with the `schemeSet2` range. The SVG is rendered via D3 v7, with slices stroked in white and space reserved for axis labels.

Mmsnikhil2608@gmail.com

Activity_7.1 q1

This pie chart visualizes the distribution of student performance categories, with each slice labeled and colored according to its category. The visualization uses D3 v7’s `d3.pie()` and `d3.arc()` to generate the slices, while `d3.scaleOrdinal` with `schemeSet2` assigns colors. Data is loaded asynchronously from a CSV file hosted on GitHub Gist and rendered as an SVG, with a legend positioned to the right of the chart to identify each category.

Ssanjanaadapa7@gmail.com