htmlq3

HTML Starter_mohammed

This example presents a dataset summary dashboard for DFW public library weekly visits in 2025, showing five key metrics in a dark-themed card layout. The visualization uses D3 v7 to load CSV data via `d3.csv`, calculates aggregate statistics with `d3.mean` and `d3.max`, and renders metric cards using `d3.select` with a data join. The SVG badge and styled metric cards are built with HTML and CSS, while the data-driven values update dynamically through D3's data binding.

83% match

ice6_part1

A bar chart shows total weekly visits per public library from a DFW libraries dataset, with libraries sorted in descending order and bars colored red. The code uses D3 v7’s `d3.text`, `d3.csvParse`, and `d3.rollup` to load and aggregate the CSV data, then renders an SVG chart with `d3.scaleBand`, `d3.scaleLinear`, `d3.axisBottom`, and `d3.axisLeft`. Data is sourced from a GitHub gist containing the 2025 weekly visits CSV.

76% match

ice 6 part 3

A dual-axis chart displays total weekly visits as blue bars and average events per week as a red line for each Dallas public library, sorted by descending visit totals. The visualization uses D3 v7 APIs including `d3.text` and `d3.csvParse` to load and parse the CSV data from a GitHub Gist, `d3.rollup` for aggregation, `d3.scaleBand` and `d3.scaleLinear` for axes, and `d3.line` for the trend line. An interactive legend and rotated axis labels aid readability.

75% match

area chart

This area chart visualizes weekly visits to Dallas-Fort Worth public libraries across 52 sequential weekly observations. The chart uses D3 v7’s `d3.area` generator with a linear scale for both axes, filling the region beneath the line with a light blue `#9ecae1` and overlaying a darker stroke. Data is loaded from a CSV via `d3.csv`, with numeric values parsed to remove commas. The y-axis includes gridlines and a “Weekly Visits” label, while the x-axis displays integer index ticks with a “Library Index” label.

Ddrusyawontparticipate@gmail.com

Fork of ICE-5-KUMAR-DANAM-Q3

This visualization displays a summary and preview of a CSV dataset by fetching it from a remote URL. It uses D3 v7’s `d3.csvParse` to parse the text, then presents file size, row count, and column count in styled stat cards. The code renders the first five data rows into an SVG-backed HTML table using D3’s `select`, `append`, and data joins, with custom CSS for a dark, glassmorphism-themed layout. The example demonstrates basic D3 data loading, parsing, and DOM manipulation for tabular data exploration.

Reusable D3 Scatter Plot

This reusable D3 scatter plot visualizes the relationship between events per week and weekly visits for Dallas-Fort Worth public libraries, using CSV data loaded directly from a GitHub gist. The SVG visualization encodes the quantitative variables on the x- and y-axes, with data points rendered as circles sized by a fixed radius. Built with modular D3 6.7.0 functions, the plot implements a configurable `scatterPlot` generator that leverages `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` APIs. The plot animates by cycling between the two data columns every two seconds, updating the x-axis and circle positions via a `setInterval` callback. The example demonstrates a reusable chart module with idempotent rendering, likely intended for easy parameterization across datasets.

Ppriyankachary1701@gmail.com

Q3

This example presents a data-summary and preview tool for library book CSV data. It loads a user-provided CSV file and displays a statistical summary of each column, distinguishing numeric columns with min/max/mean values from categorical columns with unique counts. The application then renders the first ten rows of data in a styled HTML table. All visualization is built using the D3.js library (v7), primarily using `d3.csvParse` with `d3.autoType` for data ingestion and `d3.min`, `d3.max`, and `d3.mean` for column analysis. A separate static SVG graphic demonstrates basic shapes like rectangles, circles, and polygons.