Fork of Hello VizHub

Fork of Hello VizHub

This area chart visualizes a dataset loaded from a CSV file hosted on GitHub. The chart displays values over time, with dates parsed via `d3.timeParse` and a linear scale for the y-axis. The area path is generated using `d3.area` and rendered as a steelblue SVG path. Axes are created with `d3.axisBottom` and `d3.axisLeft`, and the chart is built with D3 v7.

SSeema Shrestha

Fork of Fork of Hello VizHub

This example presents a pie chart of aggregated sales data by product category, loaded from a CSV file hosted on GitHub and rendered as an SVG. It uses D3 v6 APIs such as `d3.csv`, `d3.rollups`, `d3.sum`, `d3.pie`, `d3.arc`, and `d3.scaleOrdinal` with `d3.schemeCategory10`. The chart displays each category’s total sales in thousands and its percentage share, with labeled arcs and a legend.

KKritin Kesav

CChiranjeeviUppala@my.unt.edu

Fork of Hello VizHub

This fork of Hello VizHub displays a pie chart of scores loaded from a remote CSV file. The visualization uses d3.pie and d3.arc to compute and render the donut-like segments, with a categorical color scale (d3.scaleOrdinal) assigning colors. Data is fetched via d3.csv from a GitHub gist, and the SVG paths and labels are drawn with D3's data-join pattern, placing names at each arc's centroid.

Fork of Hello VizHub

This fork of “Hello VizHub” displays a scatter plot of a two-feature dataset loaded from a CSV file, with points colored by category. It uses D3.js v6 functions like `csv`, `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to map data to SVG circles, with green axis labels and a red, underlined title. The visualization resizes to the full browser window and plots each row’s feature_1 against feature_2.

Pperamranji

Aankitgoudpoodhari07@gmail.com

Fork of Hello VizHub

This fork of Hello VizHub demonstrates three linked D3.js visualizations. It shows total sales by brand and region in a bar chart, units sold versus sales in a scatter plot, and profit alongside average price in a multi-series chart with bars and a line. The code uses `d3.csv` to load a remote dataset and `d3.scaleBand`, `d3.scaleLinear`, `d3.rollups`, and `d3.schemeTableau10` to bind data to SVG rects, circles, and a path via `d3.axisBottom` and `d3.axisLeft`. A dual y-axis is implemented for the final chart.

Fork of ICE-6: Rendering Marks and Channels with React & D3

This bar chart displays the top 10 most valuable unicorn companies, with company names on the y-axis and valuation in billions on the x-axis. The visualization is built using React and D3.js, where React manages the component state and rendering of SVG elements, while D3’s `scaleBand` and `scaleLinear` handle the chart’s scales and tick generation. Data is loaded asynchronously from a CSV file via `d3.csv`, filtered to the top 10 entries, and rendered as blue rectangles.

Pprashanth yamala

Fork of Hello VizHub

This example visualizes gold stock price data as a pie chart grouped by year, showing the sum of closing prices for each year. It loads CSV data from a GitHub Gist, cleans the dataset by removing columns and filtering low-volume rows, then aggregates values using `d3.nest` and `d3.sum`. The chart is rendered with D3 v6 as SVG elements, using `d3.pie`, `d3.arc`, and `d3.scaleOrdinal` with `d3.schemeCategory10`, alongside a color-coded legend beside the pie slices.

Ssohith kampalli

Fork of Hello VizHub 91

This example visualizes the distribution of data across ten team categories using a pie chart rendered in SVG. It loads a CSV file from a GitHub gist, processes the data with D3 v5, and displays each slice with its corresponding percentage value. The chart uses `d3.pie`, `d3.arc`, and a color scale, with a manually positioned legend listing team names and colored markers.

Iiamjathin11@gmail.com