Jan0RodGar

@Jan0RodGar·4 public vizzes

Gist 0bd164d320049d1926cdb6310644fa40

This visualization uses the classic Iris dataset to display the relationships between sepal and petal measurements for three flower species. The code loads the CSV data and renders a scatter plot that maps sepal length and width on the axes, with each point colored by species. The implementation relies on the Plotly.js library's `Scatter` and `Layout` classes to generate the interactive chart, with species values driving both the color and legend entries for the setosa, versicolor, and virginica groups.

Jul 27, 2018

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Gist a7dcca17dd6f9275b5d6435007f6b9f0

A small scatterplot displays five manually defined points with x and y coordinates from a fixed data array. The visualization uses d3.forceSimulation to position the circles, applying a simple force layout that settles the nodes into place. Each point is rendered as a circle with a fill color and stroke, while the simulation drives subtle movement before stabilizing. The code does not include axes, labels, or interaction, focusing solely on the force-directed placement of the given data.

Jul 27, 2018

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D3 Example

This example displays grouped bar charts comparing the populations of five countries across eight religious categories. The visualization uses a stacked-to-grouped layout, with each religion represented by a distinct color from a categorical scale. The code loads data from a CSV file and leverages D3.js (version 3.5.5) with d3.nest, d3.layout.stack, d3.svg.axis, and d3.legend to render the SVG chart. Axes and legends are styled with the Open Sans font.

Jul 27, 2018

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D3 Example

This example visualizes the religious demographics of the top five most populous countries—China, India, the USA, Indonesia, and Brazil—using grouped bar charts. Each country’s population is broken down by religion, with bars colored according to the religious category. The visualization is built with D3.js, specifically using `d3.layout.stack` for the stacked data structure and `d3.legend.color` to generate the color legend. The data originates from the CSV file `religionByCountryTop5.csv`, which is loaded using `d3.csv`. The chart employs SVG rendering with ordinal and linear scales for the axes.

Jul 27, 2018