Makes a little histogram in bash from your data. Uses = for bars

Gist 6568151

A histogram displays a randomly generated Irwin–Hall distribution of 50 values, showing the count of scores binned into twenty uniform intervals. The chart uses D3’s histogram layout and linear scales to position bars, with axis ticks placed between bars to clarify bin boundaries. Bar counts are labeled above each rectangle, and mouseover events log the original data objects and associated names filtered from the source array. Rendered as SVG using d3.v2, the example demonstrates binning and interactive data binding.

11wheel

60% match

Histogram

This histogram visualizes the distribution of a numeric variable, grouping observed values into discrete bins and displaying their frequencies as vertical bars. It uses the D3.js library, specifically leveraging `d3.histogram` and `d3.scale` APIs to compute bin ranges and map data to screen coordinates. The rendering relies on SVG paths generated from the binned counts, with axes and labels drawn via D3’s measurement and tick utilities. The dataset originates from a GitHub gist, and the code operates entirely in the browser without external data files.

58% match

Bar Chart IIc

This example shows a basic horizontal bar chart, with each bar labeled by its value in white text. It uses D3 v3 to load tab-separated data from `data.tsv`, scales the bar widths with a linear scale, and appends SVG `<rect>` and `<text>` elements. The chart is rendered as an SVG with a fixed width, and the bar height is computed from the number of data rows. The `d3.tsv` method parses the data, and the `type` function coerces values to numbers before rendering.

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bash profile

This visualization parses the contents of a bash profile script to reveal its structure and composition. It shows the file’s lines grouped by type—such as aliases, exports, and functions—and highlights the distribution of shell constructs. The code uses JavaScript to read the raw text and a custom layout algorithm, likely d3.js, to render an interactive treemap. The data source is the gist containing the bash_profile, and the rendering approach relies on hierarchical rectangles whose sizes reflect character counts or line frequencies, making the script’s organization immediately visible.

Histogram

This interactive histogram visualizes the distribution of one numeric variable using data loaded from a CSV file. Built with D3 v7, it renders bars as SVG rectangles, with the x-axis scaled linearly and the y-axis representing bin counts. The chart updates responsively on window resize, recalculating the histogram with 40 thresholds to accommodate the new width. Data is fetched from the `data_to_viz` GitHub repository.

Aarjun-lab663

Bar Chart I

This bar chart visualizes six numeric values—4, 8, 15, 16, 23, and 42—as horizontal bars whose widths are proportional to the data. The chart uses D3 v3’s `d3.scale.linear` to map the domain from zero to the maximum value (42) onto a pixel range of 0–420. Each bar is a styled `div` element with a steelblue background, white text, and a width set via the `style` operator. The code appends these divs using `d3.select` and `.selectAll("div").data(...)`, with the data bound to the DOM. The bars’ labels display the original values.

histogram

This histogram visualizes the distribution of power data values from a CSV file, grouping the data into eight bins spanning 0 to 800. The code uses p5.js to load the external dataset in a `preload()` function, then draws vertical grid lines and cyan bars, with each bar’s height scaled proportionally to the count of values in its bin. Axis labels and bin ranges are rendered directly on the canvas, and the visualization’s fixed dimensions and styling are defined through p5.js canvas drawing commands.

Hhollyjpotter