Magic Bar Chart

Magic Bar Chart

This example demonstrates a Magic Bar Chart, a reusable visualization component built with Chiasm and bundled with Browserify for production use. The chart animates the transition of bar positions and heights based on changing data, rendering smooth, dynamic updates with SVG. The visualization reads from the `adult.csv` dataset, which contains demographic records including age, education, occupation, and income category. The chart likely groups or aggregates this data by income category and animates between different categorical groupings (such as sex, race, or workclass) using Chiasm's reactive dataflow. The SVG-based rendering and animation make the bar chart transitions fluid, providing an interactive and engaging way to explore the dataset. The example demonstrates how Chiasm can be used to build a reusable, production-ready data visualization component.# Magic Bar Chart This example demonstrates a reusable bar chart built with Chiasm and bundled using Browserify. It visualizes the UCI Adult dataset, showing income distributions across demographic categories. The chart uses animated SVG transitions to smoothly morph between different data groupings, making it easy to compare income patterns across attributes like education, occupation, and native country. The visualization showcases how Chiasm's reactive dataflow architecture enables clean, maintainable visualization code in production environments. The "magic" refers to the chart's ability to automatically update and animate when the underlying data or configuration changes. ---

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Magic Heat Map

This visualization uses the Chiasm library to build an interactive heat map from the adult census dataset. The data is aggregated by counting records along both the X and Y axes, and the resulting two-dimensional bin counts are rendered as colored cells in an SVG heat map. The view supports interaction, allowing users to explore patterns in the dataset. The project, authored by Curran, is a 2D adaptation of the earlier Magic Bar Chart example, reusing its reactive/data-joining approach for the heat map case.

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Chiasm Charts Example

This example demonstrates the Chiasm Charts library’s ability to dynamically adjust scale types based on input data, such as switching between linear and ordinal scales in scatter plots. Axis labels are positioned relative to the outer container, allowing interactive margin adjustments to prevent overlapping tick labels. The bar chart includes configurable color options and a new background color mixin. The visualization is rendered with SVG and supports animation, as shown in the provided bar chart and Iris dataset examples.

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Gist 95392bf4a37344793786

This interactive bar chart displays comparative proportions across four categories, rendered as vertical bars (SVG rectangles) with a rotated axis label. Using D3.js v3, users can click and drag on any bar to resize it, with a semi-transparent background bar indicating the current editing area. The visualization distinguishes major and minor gridlines through separate `d3.svg.axis` configurations, while mouse events (`mousedown`, `mousemove`, `mouseup`) update bar heights dynamically based on cursor position. Hardcoded data arrays provide initial values, and all styling is applied via CSS classes.

HHoffmannP

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Chiasm Charts Example

This example demonstrates the chiasm-charts package (v0.1.0), rendered with SVG and animation. It shows a bar chart and a line chart side by side, each with its own data loaded from CSV files. The visualizations support interactive editing—users can drag the chart margins to adjust the layout. The charts are part of the Chiasm Project, a reactive visualization framework, and this example highlights early-stage functionality with known limitations around build tooling and component registration.

Bar chart

A bar chart displays categorical values with six colored, semi-transparent rectangles. The visualization maps lettered categories (A through F) to numeric values, with axes labeled and gridlines rendered via D3's SVG axis API. It uses `d3.scale.ordinal` for the x-axis bands and `d3.scale.linear` for the y-axis range, while `d3.svg.axis` generates the ticks. Rectangles are appended and styled with `d3.scale.category10` colors, and the data comes from an inline array of objects with `x` and `y` properties.

DDDDDDanica

Bar Chart interactive

This interactive bar chart visualizes a dataset of 50 random values, with bars colored on a blue scale and labeled with their numeric values. Clicking the text prompt triggers an update that replaces the data with 25 new random values, resizing the bars accordingly. Built with D3 v6, the example uses the scaleBand and scaleLinear APIs to map data to SVG rectangles, while the d3.select method binds the click event to the paragraph element.

DDasbach.EJ

Interactive Bar Chart

This interactive bar chart, built with D3.js and Chiasm, visualizes the classic Auto MPG dataset, allowing users to explore relationships between vehicle attributes. The chart includes dropdown menus that let users select which numeric columns to plot on the x- and y-axes, enabling comparisons such as horsepower against miles per gallon. The visualization updates smoothly in response to user selections, demonstrating how interactive column selection can reveal patterns in multivariate data. The source code and data are available under the MIT License.