Question 1: Bar Chart

Question 2: Pie Chart

This example visualizes product revenue distribution as an interactive pie chart, with slices colored by product and sized by aggregated revenue from a CSV file loaded via `d3.csv()`. The SVG-based chart uses `d3.pie()` and `d3.arc()` to generate the slices, while hovering highlights a slice with a `transition` animation. A legend and title accompany the chart, and the background uses a CSS gradient. The chart sorts products by revenue and uses an ordinal color scale.

Question 3: Line Chart

This line chart displays monthly revenue trends for multiple products, with each product represented by a colored line and interactive dots. The visualization uses D3 v7 to load CSV data from a GitHub gist, aggregate revenue by month and product name, and render an SVG chart with a categorical color scale, gridlines, and hover effects that increase stroke width and dot radius. The chart is presented on a gradient background within a styled card container, with a legend and axis labels.

Question 4: Multi-Series Chart (Bar + Line)

This example combines a bar chart and line chart into a single multi-series visualization, showing revenue as blue bars and units sold as a red line for each product category. The data is loaded as CSV from a remote GitHub gist and aggregated by product using d3.csv and manual JavaScript object mapping. The chart uses d3.scaleBand for the categorical x-axis and two separate d3.scaleLinear scales for the revenue and units y-axes, with d3.axisLeft for gridlines and d3.line to generate the units-sold path. The SVG is rendered with a gradient background and includes hover transitions on bars and circles.

Question 4: Area Chart

This area chart visualizes monthly revenue trends across multiple products, with each product represented as a colored filled region that can be hovered to adjust opacity. The chart uses D3 v7 to load CSV data via `d3.csv`, aggregates revenue by product and month using `d3.group` and `d3.rollup`, and renders the areas with `d3.area` alongside scaled point-based x-axes (`d3.scalePoint`) and linear y-axes (`d3.scaleLinear`). Interactive dots respond to mouse hover by increasing their radius, and gridlines provide reference for revenue values.

Question2

A stacked bar chart displays quarterly sales by product category, with categories on the y-axis and sales totals on the x-axis. The visualization uses D3 v7's `d3.stack`, `scaleBand`, `scaleLinear`, and `scaleOrdinal` APIs to construct the chart, with tooltips revealing the category and sales amount per segment. Data from the CSV file is loaded and rendered as SVG rectangles, with an interactive legend and axis labels. The code leverages D3's declarative `.join` pattern for efficient element updates.

Gganesh.hns48@gmail.com

80% match

Question 1

This pie chart visualizes sales distribution by product category, using a categorical color scale to differentiate segments and displaying numeric values directly inside each slice. It loads CSV data from a GitHub Gist, converts the values to numbers, and renders the chart with d3.pie, d3.arc, and d3.scaleOrdinal. A custom legend built with SVG rectangles and text identifies each category, while positional labels for "Product Categories" and "Sales Value" reinforce the chart’s context. The visualization uses D3 v7 with an SVG-based rendering approach.

Ppavanbellam@my.unt.edu

79% match

Aavvarijayakrishna99@gmail.com

Product Sales Bar Chart

This bar chart displays product sales figures from a CSV file, with each product’s sales value represented by a steelblue bar. The visualization uses D3.js to create an SVG, scaling the x-axis with `d3.scaleBand` and the y-axis with `d3.scaleLinear`. Axis labels are rotated, and a title is added, all rendered via the D3 SVG API. Data is loaded asynchronously from a GitHub gist using `d3.csv`.

79% match