KELVIN WAMBUA NZIOKI

@wambuakev·7 public vizzes

Fork of 3D Scatter Plot

This 3D scatter plot visualizes monthly vehicle sales using two distinct marker groups, with gray and colored points differentiating categories in three-dimensional space. Built with Plotly.js 2.9.0, the visualization loads data from a CSV file hosted on GitHub via d3.csv, then maps the x, y, and z coordinates from the specified columns into two traces. Custom marker styling, including size, opacity, and colored borders, distinguishes the second dataset from the first, while the layout removes all margins to maximize the plotting area.

Apr 2, 2023

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3D Bar Chart using D3.js

This example shows car manufacturer sales across the first six months of the year as an interactive 3D bar chart, with each manufacturer’s monthly values rendered as vertical bars in a three-dimensional scene. The visualization uses D3.js v5 for data loading and scaling, the d3-3d plugin to convert 2D bar coordinates into 3D geometry, and the X3DOM library to render the scene in the browser. Data comes from a CSV file parsed into per-manufacturer monthly series, which are then passed to the `d3.x3d.chart.barChartMultiSeries()` chart component. The chart updates its displayed data after initially loading a random dataset.

Apr 2, 2023

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Fork of 3D Bar Chart with d3.js

This fork demonstrates a minimal setup for D3 version 7 by rendering a static text message in the browser. It shows a bold “Hello D3 version 7” string centered on the page, using the `select` method from the d3 package to target the body element and set its text content. The example relies on the d3.v7 library loaded via a CDN, with no data or visual encoding involved, serving purely as a baseline for comparing API changes from earlier versions.

Apr 2, 2023

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Fork of D3 Starter

This example demonstrates the simplest possible D3 setup, rendering the text “Hello D3 version 7” centered on a blank page. It loads the full D3 library from a CDN and uses the `select` API to target the document body, then calls the `text` method to set its content. The page’s large font size is defined in an inline style, while the JavaScript logic resides in a separate `bundle.js` file. The visualization serves as a minimal starting point for learning how to integrate D3 into an HTML page.

Apr 2, 2023

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Fork of 3D Bar chart

This interactive 3D bar chart visualizes vehicle sales counts by month, comparing new vehicles, used vehicles, and their respective total sales across six months. The chart uses Highcharts with the highcharts-3d module to render stacked, grouped columns in a 3D perspective with adjustable rotation and depth. Monthly sales data is displayed on the x-axis, with sales values on the y-axis and product categories on the z-axis. The visualization is based on population-related data sourced from Macrotrends, though the visible series focus on vehicle sales figures rather than demographic data.

Apr 2, 2023

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Bar chart with D3.js

This visualization presents a bar chart of the most loved programming languages in 2018, using data from a Stack Overflow survey. It shows the percentage of developers who love each language, with bars colored per language. Built with D3 v5, the chart uses `d3.scaleBand` and `d3.scaleLinear` to map data to SVG rectangles. Hovering a bar triggers a transition that highlights it, draws a reference line at the hovered value, and displays divergence percentages for all other bars, using D3 selections and `transition.attr`.

Apr 2, 2023

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Fork of Making a Bar Chart

This bar chart displays the population of the top 10 most populous countries, based on 2018 estimates from the United Nations World Population Prospects. The visualization uses d3.csv, d3.scaleLinear, d3.scaleBand, d3.axisLeft, d3.axisBottom, and d3.format to render an SVG with labeled axes and a title. A custom tick formatter converts large numbers into abbreviated units, such as billions, while the y-axis labels are cleaned of extra lines. Data is loaded from a local CSV file and rendered with steel-blue bars.

Apr 2, 2023