Housing Violations Data - 2012

Housing Violations Data - 2012

This beeswarm plot shows the timing of housing violations in 2012, with each point representing a single violation. A drop-down menu filters the visualization by violation type, such as "Overgrown Vegetation" or "Refuse Accumulation." Hovering over a point reveals details about the specific violation. Built with d3.v4, the plot uses the `forceSimulation` API to arrange points along a horizontal time axis, avoiding overlap while preserving the density distribution of the data. The dataset comes from a CSV file containing violation dates, categories, and inspection IDs.

96% match

Housing Violations Data - 2012 (d3 dropdown)

A beeswarm plot shows the temporal distribution of 2012 housing violations, with each point representing a single violation. A dropdown menu filters the dataset by violation type, such as "Refuse Accumulation" or "Lead Hazard," and hovering reveals details. The x-axis maps violation dates using a time scale, while a force-directed simulation (`d3.forceSimulation`, `d3.forceX`, `d3.forceY`, `d3.forceCollide`) arranges overlapping points. The visualization uses SVG rendering, loads data from a CSV, and displays summary statistics like the number and earliest/latest violation dates.

95% match

Violations 2012 calendar view

This calendar view visualizes 2012 housing violations, using a color-coded grid of days to show the frequency of selected violation types throughout the year. Users choose a violation category from a dropdown menu, and each day’s rectangle is shaded by a linear color scale from red to green based on the count. The visualization uses D3.js (v4) to render SVG elements, with a tooltip on hover revealing details. The data comes from a CSV file containing inspection records, and the interface uses Bootstrap for the menu styling.

83% match

Violations 2012 calendar view (d3 dropdown)

A calendar view shows housing violation data for 2012, with each day represented by a colored rectangle. Users select a violation type from a dropdown menu, and the color of each cell reflects the count of that violation on that date. Hovering reveals details via a tooltip. Built with D3 v4, the visualization uses `d3.timeDays` and `d3.timeMonths` to structure the calendar layout and `d3.scaleQuantize` for color encoding. SVG rectangles and text labels are animated when the selection changes, drawing from the provided CSV dataset.

80% match

Fork 2 of beeswarm

A beeswarm plot uses a force-directed layout to visualize the distribution of honey bee colony loss percentages across U.S. states in 2015. Each circle represents a data point, positioned along a logarithmic x-axis according to its value, with a Voronoi tessellation overlay for interactive hover detection. The visualization employs d3.forceSimulation with forceX, forceY, and forceCollide to arrange points, and d3.voronoi for cell boundaries. Data originates from data_2015.csv, rendered as SVG with React and d3.v4.

Rryan-dirajlal

30.Beeswarm

A beeswarm plot distributes circular marks along a logarithmic x-axis to show the distribution of file sizes from the flare dataset, with a force simulation stacking points vertically to prevent overlap. A Voronoi overlay expands the hover target for each point, displaying a tooltip with the file’s ID and value. The visualization uses d3.forceSimulation with d3.forceX, d3.forceY, and d3.forceCollide, rendered as SVG, with a d3.axisBottom log scale and d3.voronoi polygons for interaction.

深深度碎片

Untitled

This visualization is a heatmap showing monthly property crime counts in San Francisco from 2005 to 2015. Each cell represents a month and year, colored on a viridis scale from low to high crime totals, with years on the y-axis and months on the x-axis. The code uses d3.nest and d3.map to aggregate the CSV data, d3.scaleBand for axes, and d3.scaleSequential with d3.interpolateViridis for the color encoding. A gradient legend with a d3.axisBottom is rendered using an SVG linearGradient.

Vvaynexie

Beeswarm

A beeswarm plot displays the distribution of numeric values from a CSV dataset, with each circle representing a data point positioned along a logarithmic x-axis. The circles are arranged using d3.forceSimulation with forceX, forceY, and forceCollide to prevent overlap. A Voronoi overlay via d3.voronoi improves hover interaction: hovering over any cell highlights the corresponding circle in red, and a tooltip shows the data point’s ID and value. The visualization renders in SVG with an axis label and tick formatting.

FFrissAnalytics