Space Stations_QN

100%

Space Stations_QN

✓ Published0🌍 Public

Last edited Mar 24, 2020

Created on Mar 24, 2020

This parallel coordinates chart displays the attributes of subsea control module (SCM) notifications, with each axis representing a categorical field such as notification type, priority, origin, cause, damage description, material, and defect date. Each polyline traces a single record through the dimensions, revealing patterns and correlations across these variables. The visualization is built with D3.js (v3 and v5), using SVG for rendering and custom axes with brushes for interactive filtering. The data is loaded from a pipe-delimited text file containing 19 records of inspection and defect reports.

AI-generated description

MIT Licensed

Similar vizzes

Loading thumbnail…

SCM Quality Notification

This example displays a parallel coordinates plot of subsea control module quality notifications. It shows how multiple categorical attributes—including notification origin, priority, type, and various defect descriptors—relate across dozens of recorded issues. The visualization uses D3 v3’s `d3.svg.axis`, ordinal and linear scales, and a line generator to render each data record as a polyline. Data is loaded from a pipe-delimited text file via `d3.dsv` and rendered as SVG with interactive brushable axes.

Nnadia-el

81% match

Loading thumbnail…

SCM QN v1

This visualization displays a parallel coordinates plot of supply chain quality notifications (SCM QN) from pipe-delimited text data, showing categorical dimensions like notification origin, priority, and damage group. The D3 v3 code uses d3.svg.axis and d3.scale.ordinal for axes, with d3.dsv parsing the data and truncating values to 20 characters. A foreground path layer renders the multi-dimensional lines, while CSS styling controls axis rotation and label formatting. The visualization was adapted from Curran Kelleher’s "World Countries Hierarchy" block.

Nnadia-el

78% match

Loading thumbnail…

Space Stations

This visualization uses a parallel coordinates chart to explore patterns in mining accident data, displaying multiple dimensions such as nature of injury, classification, injury source, body part, mining equipment, occupation, and accident dates. The d3.svg.axis and d3.scale.ordinal functions render the vertical axes, while d3.svg.line draws each accident as a connected polyline. Data is loaded from a pipe-delimited text file and coerced into numbers, strings, and dates. Brushing interactions on each axis allow users to filter the displayed records interactively.

Nnadia-el

74% match

Loading thumbnail…

Space Stations

Space Stations visualizes orbital data for satellites through an interactive parallel coordinates plot. The D3.js visualization maps each satellite's trajectory across multiple dimensions including inclination, eccentricity, and mean motion, with brushed axes allowing users to filter data ranges. The example parses two-line element (TLE) set data from a text file into structured CSV format, then renders the multidimensional relationships using d3.svg.brush and custom SVG paths with color-coded strokes for each orbital object.

Nnadia-el

72% match

Loading thumbnail…

Untitled

A parallel coordinates plot displays two data records across five categorical axes—Style, Intelligence, Focus, Magic, and Gender—with values scaled linearly from 1 to 10. Solid and dashed polylines represent each row, distinguishing the two series. Built with D3 v4, it uses `d3.scaleLinear` for y-axes, `d3.scalePoint` for x-axis positioning, and `d3.axisLeft` for rendering. SVG paths are generated via `d3.line`, with a custom legend annotating “Achieved Performance” and “Requirement.” Data loads from a CSV file containing two numeric rows.

JJoker-tr

64% match

Loading thumbnail…

Parallel Coordinates

This parallel coordinates chart uses color-coded polylines to display country-level survey data across multiple dimensions, including happiness, art/education, environmental concern, and organizational memberships. Built with D3.js v3, the visualization renders SVG paths for both background context (gray) and foreground focus (steel blue) lines. The code implements interactive brushing via `d3.svg.brush()` to filter data, and uses `d3.behavior.drag()` to allow users to reorder axes by dragging. Axis labels are mapped through `d3.scale.ordinal()` and `d3.scale.linear()`, with data loaded from the `total4.csv` file.

KKanwalNayan

64% match

Loading thumbnail…

d3 | Parallel Coordinates

This example shows a parallel coordinates plot of planetary data from NASA, displaying each planet’s day length, distance from the Sun, orbital period, mass, and diameter as linked polylines across vertical axes. Users can brush along any axis to filter the highlighted lines, and drag axes to reorder them. The visualization uses the d3.parcoords library, built on d3.v3, with SVG for axes and canvas layers for rendering shadow, foreground, and highlight strokes, plus animation during drag transitions.

GGoomble

63% match

Loading thumbnail…

Fault Localization 5

This visualization presents a tri-panel view of fault localization data for 25 source code lines, showing suspiciousness, recency, and line complexity as horizontal bar charts. Each panel shares the same y-axis ordering by line ID, enabling cross-comparison of metrics. The charts are rendered as SVGs using D3 v5, with the third panel featuring a sort button that reorders bars by line complexity. The suspiciousness and recency panels use `d3.scaleLinear` for x-axes, while all panels employ `d3.scaleBand` for categorical y-axis spacing. Data originates from a CSV file containing Apache Commons source file references.

KKanagaraj-NN

63% match