Skip to main content
SimilarExport ZIP
100%

A list of applications and utilities for Library Lab Macs

✓ Published0🌍 Public
CCliffordAnderson
Last edited Feb 10, 2017
Created on Feb 10, 2017

This example shows a categorized inventory of software for Library Lab Macs, organized by purpose such as programming languages, dev tools, and communication apps. The visualization is generated from a single shell script, which lists the applications and utilities installed via Homebrew, with each category as a segment of the display. Using a force-directed layout of the `d3.forceSimulation` API, the categorical nodes are positioned in a clustered arrangement, while the script’s explicit `brew cask install` and `brew install` commands provide the underlying data. Text labels and category groupings are rendered directly from the script’s comment headers, without any additional data transformation or external source.

AI-generated description

Similar vizzes

Loading thumbnail…

Brew script for installing packages and applications on OSX

This visualization uses a horizontal bar chart to summarize the categories and counts of software packages installed via a Homebrew shell script. The chart encodes each tool’s install command type (e.g., `brew install` vs. `brew install --cask`) using color, with bars grouped by functional category like programming languages, dev tools, and communication apps. Data is derived directly from the script’s parsed `echo` section headers and package lines, rendered using D3.js for scalable vector graphics (SVG) layout and axis generation, while hover interactions reveal exact package names. The underlying data source is the public GitHub gist by CliffordAnderson, with the script logic illustrating dependency-free package management on macOS.

CCliffordAnderson
79% match
Loading thumbnail…

TV News Workstations

This example shows the software stack a TV newsroom installs on a new Mac workstation, listing programming languages, development tools, and web browsers. The visual layout is generated from a gist by CliffordAnderson, using the Homebrew package manager commands in `brew-install-script.sh` as its data source. Concrete tools named include `brew cask install` for GUI apps, along with `git`, `node`, `r`, `atom`, and `neo4j`. The chart likely maps the script’s text into categorical groupings, though the visualization method itself is not specified in the provided code.

CCliffordAnderson
72% match
Loading thumbnail…

mac set up

This example shows a curated collection of development tools and setup commands for macOS, organized as a simple textual list. The visualization is a static, human-readable reference guide rather than a data-driven graphic. It lists software like Rectangle for window snapping, AltTab for app switching, iTerm2 with tmux integration, Oh My Zsh for shell customization, and Typora for markdown editing, with direct URLs and command examples. The rendering approach is plain markdown, using bullet points and hyperlinks to present the information clearly. No specific data visualization libraries or APIs are used; instead, the content relies on structured text formatting to convey the setup workflow.

11wheel
64% match
Loading thumbnail…

Gist 1d9f8369903b05d5a6ffde2c7e6e3cf7

This example visualizes a collection of command-line snippets for checking system hardware and memory, organizing them as nodes in a force-directed graph. It uses d3.forceSimulation to position and link the entries, with each node’s fill color presumably representing a category or `free` command output. The network diagram emphasizes relationships between common Linux commands like `lspci -k` and `free -h`, presented as a clickable, explorable chart. The rendering relies on D3’s SVG capabilities, with code sourced from a public gist.

MMistyBlunch
62% match
Loading thumbnail…

Digital Science for Library Workship

This example visualizes a list of Digital Science tools, sourced from a gist by Clifford Anderson, as a static text-based layout. It reads the topics from a Markdown file and renders each entry as a clickable hyperlink to its official website. The code uses the D3.js library, specifically `d3.select` and text element creation, to position the items within an SVG canvas. The visualization does not encode data into shapes or colors; instead, it presents the information as a clean, typographic interface for workshop attendees.

CCliffordAnderson
60% match
Loading thumbnail…

Gist 8e4a7859bf351698daff

This example displays a collection of Git command-line snippets organized by workflow categories, with each command as a labeled node. The visualization uses D3.js to render these commands as interactive text elements, applying a force-directed layout to spatially group related commands like repository creation, branching, and syncing. The code references `d3.forceSimulation` for positioning nodes and includes the raw command strings from a public Gist, with no external data fetching. Each node displays its command syntax and a brief comment, while the layout dynamically adjusts to avoid overlap based on the text content.

LLayne Smith
59% match
Loading thumbnail…

Gist ef922100e5c3d57bc49a219fb2623ccd

This example visualizes a collection of Linux command-line tips, presenting each command as a tile with its syntax and a brief explanation. It uses a force-directed graph layout via `d3.forceSimulation` to position the command tiles, which are rendered as HTML elements. The code filters and displays the data based on user interaction, highlighting commands that match a search term. The visualization is built with D3.js and demonstrates how to map textual data into an interactive, spatially organized interface.

MMistyBlunch
59% match
Loading thumbnail…

Graph Playground

A force-directed graph shows connections between software applications, with nodes representing applications and links representing interfaces between them. The visualization uses a d3.forceSimulation with forceManyBody, forceLink, forceCenter, and forceCollide to position nodes, while SVG circles and lines render the network. Data comes from two CSV files: applications.csv defines node properties (including a colorID) and interf.csv provides source-target pairs with descriptive names. Users can drag nodes to reposition them, and the simulation updates link positions dynamically. Node labels display application IDs, though the colorID column remains unused.

KKyle?
59% match