graph3

Stylized Barchart Test

This stylized bar chart displays mobile app download totals across devices, with the dataset filtered to two rows and the x-axis scaled beyond the maximum value to expand tick labels. The visualization is built with React (v18) and D3 v7, using `scaleBand` for the categorical y-axis, `scaleLinear` for the numeric x-axis, and SVG `<rect>` elements for bars. Hovering changes bar color via CSS transitions, while `<title>` tooltips show formatted values. Data loads from a CSV via `d3.csv`, and axes are generated from D3 scales rather than D3 axis components.

Ddleoenri

Line Chart

This line chart displays the usage of mobile devices over a ten-year period, with the x-axis representing years and the y-axis showing usage values. The visualization uses D3 v5 to load CSV data and render an SVG chart, employing `d3.scaleTime` and `d3.scaleLinear` for axes, `d3.line` for the path, and `d3.axisBottom` and `d3.axisLeft` for labeled tick marks. The data is fetched from a GitHub gist, with a blue stroked line and styled text elements.

DDineshK2602

3D Bar Chart

This example displays mobile phone manufacturer sales data across six months as a 3D bar chart. It uses the d3-x3d library with X3DOM for 3D rendering, alongside d3.v5 for data loading and parsing. The visualization reads CSV data describing monthly sales figures, transforms it into multi-series format, and renders bars in three dimensions. The chart supports interactive viewing, with d3.x3d.chart.barChartMultiSeries handling the 3D scene construction from the parsed data.

Bbindusreeja

Aachyutanandmishra17@gmail.com

3D Bar Chart using D3.js

This example shows mobile phone sales data for multiple companies across twelve months as an interactive 3D bar chart. It uses the d3-x3d library to render the chart in X3DOM, a WebGL-based scene graph, by populating a `d3.x3d.chart.barChartMultiSeries()` component inside a React application. The data is loaded as CSV and parsed into a multiseries format, with D3 v5 handling scales, axes, and selections while d3-3d assists with 3D transformations.

D3 Bar Chart

This interactive D3 v4 bar chart displays two datasets of numbers as vertical steel-blue bars with value labels and a y-axis. Clicking the Update button toggles between a 10-element ascending dataset and an 8-element descending one, demonstrating the enter, update, and exit pattern. The code uses d3.scaleLinear for the y-scale, d3.axisLeft for the axis, and transition().duration(500) to smoothly animate bar heights, positions, widths, and labels when the data changes. SVG rendering handles all visual elements.

MMaxBotta

Apple Product Interactive

This interactive bar chart visualizes the growth of iPhone users from 2008 to 2020, with the y-axis showing millions of users and each bar labeled with its exact value. Hovering over a bar highlights it, displays a dashed reference line at that bar’s value, and shows the numeric difference between the hovered year and every other year as text above the bars. The visualization uses d3.csv to load data, d3.scaleBand and d3.scaleLinear for scaling, d3.axisLeft and d3.axisBottom for axes, and d3 transitions for hover effects.

KKenny Wu

Untitled

This visualization displays the market share of five major web browsers from 2008 to 2017 as multiple colored lines on a single time-series chart. The graph shows Chrome’s rapid rise and Firefox’s decline, along with the stable trends of Safari and Opera. Using D3 v4 within a React framework, the code loads CSV data with `d3.csv`, parses dates with `d3.timeParse`, and renders SVG paths via `d3.line` with `d3.curveMonotoneX`. Axes are generated using `d3.axisBottom` and `d3.axisLeft`, with a categorical color scale from `d3.scaleOrdinal`.

Rrichad97

Barchart Test

This example shows a horizontal bar chart comparing the number of downloads for two mobile device categories. The bars are rendered as SVG rectangles using React, with scales created by `d3.scaleBand` for the y-axis and `d3.scaleLinear` for the x-axis. It uses `d3.csv` to load data from a GitHub gist, filtering the dataset to two rows. The chart includes grid lines and tick labels generated from `xScale.ticks()`, while y-axis labels are positioned manually from the scale’s domain.

Ddleoenri