Gist 5916418

Interactive scatterplot

This interactive scatterplot visualizes Twitter user activity by plotting tweets based on quantitative dimensions on logarithmic x and y scales, with each point colored and sized by tweet type and a related metric. The visualization includes a custom legend with lines and circles to explain the size mapping. Built with D3.js version 3.5.5, the code uses d3.svg.axis, d3.scale.log, d3.scale.ordinal, and d3.scale.linear to construct the axes and scales, with SVG rendering for all graphical elements. The dataset is loaded from a CSV file containing tweet samples, and the graph includes a title and axis labels.

AAndresAnayaIsaza

64% match

URL list from Wednesday, Jul. 1 2015 17:21 PM

This example displays a list of tweets about maps, cartography, and GIS, scraped from a single day in July 2015. The visualization is a simple text list, with each entry showing the tweet’s author, message, and URL. The data comes from a plain-text gist, and the rendering uses basic HTML and CSS to format the list, with no interactive or dynamic elements. It serves as a static archive of social-media activity rather than a chart or map.

64% match

URL list from Thursday, Aug. 27 2015 11:11 AM

A flow map visualizes the geographic spread of a single day's Twitter links, sourced from a Gist and plotted as points on a basemap. It uses the D3.js library, with `d3.geoPath` to render country boundaries and `d3.geoGraticule` for the graticule, while a force-directed layout (`d3.forceSimulation`) positions nodes representing each URL. The map encodes each tweet's source location and destination via curved lines, with color and opacity indicating interaction intensity. The geographic projection and point placement are computed using the `d3.geo` module.

64% match

URL list from Saturday, May. 23 2015 11:12 AM

This example compiles a crowd-sourced list of geospatial and data-visualization links shared on Twitter on May 23, 2015, using a GitHub Gist as its raw data source. The visualization presents each tweet as a serial entry, rendering the original tweet text alongside the author and the direct Twitter URL. The code parses the Markdown file to extract tweets, handles the embedded media and link-shortener expansions for readability, and formats the entries with timestamps and author names. It relies on a simple text-based rendering pipeline, using standard JavaScript string processing to clean and display the tweet content without any charting or mapping libraries.

Gist 242e773969e53286f87a

This example presents a dynamic geographic mapping interface powered by a live data feed from a Quadrant server, visualizing real-time information over a map of the United States. The code employs `d3.forceSimulation` to position and animate network nodes, while `d3.geoPath` and Canvas's `getImageData` handle the rendering and manipulation of the geographic base layer. The visualization, likely representing network activity or fleet locations, refreshes over a rolling two-hour window, with user controls for time range and sub-app navigation embedded in the URL. The UI is constructed with HTML and CSS, with the map generated from a topojson data source.

fresh block

This interactive map visualization plots geolocated tweets across New York City’s fire divisions over time. The view displays colored borough regions overlaid with small circular markers for each tweet’s coordinates, with a slider to step through days and a control to adjust the map’s zoom scale via d3.geo.mercator and d3.geo.path. The code uses d3.v3, TopoJSON for boundary data, and scales for color and opacity.

GGregory-Howard

URL list from Friday, Aug. 14 2015 11:07 AM

This gallery item displays a curated timeline of tweets from geospatial and data-visualization professionals, captured as a text list. The code renders each tweet as a card with its timestamp, author, and content, drawing from a linked data file. It uses simple DOM manipulation to append elements, without a visualization library. The layout is a vertical flow, and no interactive features or data-driven scales are present.

URL list from Wednesday, May. 13 2015 9:25 AM

This example visualizes a collection of tweets about maps, geospatial technology, and data visualization, as shared by TheMapSmith on May 13, 2015. The visualization presents the raw text of each tweet alongside its corresponding URL, linking each entry to its original Twitter post. Rendered as a simple markdown file, the data is displayed as a chronological list without any additional styling or graphical encoding. The source content comes directly from a public gist, capturing a snapshot of the geospatial community’s social media activity at that moment.