Gist 403e87d556c707e6d2b4d920c05ba2e3

100%

Gist 403e87d556c707e6d2b4d920c05ba2e3

✓ Published0🌍 Public

Last edited Feb 23, 2021

Created on Feb 20, 2021

A scatterplot maps veterinary clinics and animal hospitals by geographic coordinates, with each point labeled by facility name. The visualization uses d3.forceSimulation to prevent label overlap, while d3.geoPath renders a base map from geographic data. Points are colored and positioned via an equirectangular projection, with tooltips activated on hover. The dataset originates from a gist containing longitude, latitude, and facility names, though a stray SQL injection string appears in the data. The visualization highlights spatial clustering of animal care providers across the western United States, using Canvas getImageData for pixel-level collision detection during label placement.

AI-generated description

Similar vizzes

Loading thumbnail…

Gist 854f56f011fd6edf9b89b9038dafaa43

This visualization maps a set of veterinary-related locations from a CSV file containing longitude and latitude coordinates, with some rows missing latitude values. It uses D3.js to project and render geographic points, likely employing `d3.geoPath` to draw map features and `d3.forceSimulation` for any positional adjustments. The data source is an invalid CSV with incomplete coordinate pairs, which the code parses and filters to plot only valid entries. The rendering approach appears to rely on canvas or SVG paths to display the spatial distribution of the listed animal clinics and hospitals, highlighting the geographic spread while exposing data quality issues in the source file.

WWill Carter

91% match

Loading thumbnail…

Gist 3ae03a54f78bce4717e04618615091c2

This visualization maps animal hospitals across California using a CSV dataset of longitude and latitude coordinates. It renders the points as a scatterplot over a geographic boundary, likely using D3’s `d3.geoPath` for the state outline and `d3.forceSimulation` for spatial layout or collision avoidance. The map highlights individual facility names on hover, drawing from the included truncated data. The rendering approach relies on Canvas or SVG, with the points colored and positioned directly from the parsed coordinates.

WWill Carter

90% match

Loading thumbnail…

Gist 2d2ef2fe6bf41bb7f10cb7a87efbb803

A force-directed simulation uses latitude and longitude coordinates from the animal_hospitals_ca.csv file to map veterinary clinics across California. The visualization employs d3.forceSimulation to position points, with d3.geoPath rendering the state's geography. The code loads hospital data including names and locations, then projects these coordinates onto a map. Labels appear for many of the plotted points, and the visualization layers points over geographic boundaries using standard map projections. The data is sourced from the CSV file provided in the gist.

WWill Carter

86% match

Loading thumbnail…

Gist f9bc908e8a1ac9bc6cd4cd65fbf4dcac

This visualization maps a CSV of Alaska veterinary clinics onto a geographic scatterplot, using longitude and latitude to place each clinic as a point. The graphic highlights a data-quality issue by displaying the raw CSV filename, “missing_latitude.csv,” as a title, suggesting the data was originally incomplete. The code relies on D3.js for data binding and SVG rendering, while geographic projection and path generation use `d3.geoPath` with a GeoJSON map. Canvas `getImageData` is not used; instead, the visualization appears to be drawn entirely with SVG elements, and no force simulation or transition tweens are present.

WWill Carter

85% match

Loading thumbnail…

Gist b95090d5c494ced48a1610c3e954a382

This visualization maps the locations of animal hospitals and veterinary clinics across Anchorage, Alaska, using longitude and latitude coordinates from a dataset of US animal hospitals. Rendered in a Vue application, each point on the map represents a facility, with multiple clinics often sharing identical coordinates when they occupy the same building or address. The map reveals a dense clustering of veterinary services in central Anchorage, with notable concentrations along major thoroughfares like Old Seward Highway, Boniface Parkway, and the Dimond Boulevard corridor, while outlying areas show sparser coverage. The geographic distribution highlights the relationship between population density and veterinary service availability, with the highest concentration of facilities in the urban core and fewer options in the surrounding areas.

WWill Carter

83% match

Loading thumbnail…

Gist 13ef2eb825b72036568cce3d413c0fab

This example shows the distribution of veterinary clinics in Anchorage, Alaska, with each clinic positioned by its geographic coordinates and labeled with its name. The visualization highlights a missing-longitude data issue by plotting points from the provided CSV, which includes clinic names, addresses, and phone numbers. The code uses D3’s `d3.forceSimulation` to adjust label collisions and `d3.geoPath` to render the map background, while the underlying data comes from a local CSV file parsed with `d3.csv`. The rendering approach relies on SVG elements, with circles for clinic locations and text labels, and the map projection is applied via D3’s geographic projection utilities.

WWill Carter

82% match

Loading thumbnail…

Gist 6770f82c17c1f4dd4ad2

This visualization maps vaccine-preventable disease outbreaks across the United States, displaying each incident as a circle on a geographic canvas. The size and color of the circles encode the number of cases and fatalities, respectively, while the chart includes a timeline of outbreak dates. The code uses the `d3.geoPath` projection to render the U.S. map and employs JavaScript canvas drawing for the points. Data is loaded from an embedded CSV array, with each outbreak’s location, date, case count, and fatality count parsed from the text file.

PPaperpanic

72% match

Loading thumbnail…

Gist e5accfd5c404e44ded12

This example maps the locations of parks from a CSV of city park attributes, encoding facility types with colored dots overlaid on a blank canvas. The visualization reads latitude/longitude coordinates from the data and uses a custom projection to plot each park, with legend markers indicating amenities like playgrounds or beaches. It relies on the D3 library for CSV parsing and SVG element creation, while the rendering itself is driven by plain JavaScript loops rather than a dedicated geographic mapping API.

11pixelzz

70% match