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@anuratim·6 public vizzes
The chart compares the inflation-adjusted prices of chicken and a dozen eggs in the United States from 1924 to 1993, using two overlaid line series rendered as SVG paths with d3.v3. Steelblue lines track chicken prices, while red lines track egg prices, with hover highlighting on the circular data points. The x-axis is a time scale formatted by year, and the y-axis is a linear price scale. Both datasets are loaded from CSV files, merged to compute shared scale domains, and plotted using a line generator with axes and hover interactions.
This animated scatterplot uses d3.v3 with SVG to compare income per capita and life expectancy across countries. Each dot represents a country, positioned by income per capita (x-axis) and life expectancy (y-axis), with an animation that reveals the data points over time. The visualization reads from a CSV file containing WHO data for over 40 health and demographic indicators, allowing users to explore the relationship between economic prosperity and health outcomes.
This visualization plots income per capita for each country using a diverging color scale on an SVG-based world map built with d3.v3. Country-level income data from WHO_data.csv is joined to geographic boundaries, with each nation filled by its income category. The view uses a sequential color encoding to reveal global income inequality, with tooltips to display exact values and country names on hover. The map projection and layout provide a clear, at-a-glance comparison of economic disparities across continents.
This visualization shows income per capita by country as horizontal bars of varying length, one per country in the dataset. The chart is built with D3 v3 and rendered as SVG. Each bar’s length encodes the country’s incomePerCapita value, with countries listed in the order they appear in the CSV source data. The visualization is static—it does not include sorting, transitions, axes, labels, or interaction. The bar colors are uniform, and the chart focuses on raw comparison of per-capita income across countries. Data comes from the WHO dataset provided by anuratim.
This example demonstrates how to load CSV data into a web page using D3.js. The page displays a simple bird shape composed of SVG circles and lines, while the CSV file’s contents are parsed into an array of JSON objects. The code explicitly logs that parsed data to the browser’s console for verification. The visualization uses d3.csv to load and transform the WHO health statistics dataset, though the visual itself does not reflect the data—it serves as a minimal demonstration of asynchronous data loading with D3 v3.
This visualization uses WHO health and demographic data from the MINE Project to plot countries as points on a world map. It shows how indicators like life expectancy, mortality rates, and health expenditure vary across continents. The code uses D3.js with `d3.forceSimulation` to position the country points and `d3.geoPath` to draw geographic outlines, while Canvas `getImageData` supports pixel-level interactions. The dataset is a CSV containing numerous health metrics, with a separate list of eliminated countries filtered out before rendering.