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singularity6033

@singularity6033·19 public vizzes

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MIT Technicolor Campus Map

This visualization displays a colorful map of MIT campus buildings sourced from OpenStreetMap, with each structure filled using a categorical color scale based on its tags. The example uses D3 v4 and TopoJSON to load and render the geographic data as SVG paths via `d3.geoPath` with a Mercator projection, while `d3.zoom` enables interactive pan and zoom. The map is fitted to the browser window and redrawn on resize, and building colors are assigned by `d3.scaleOrdinal` with `d3.schemeCategory10`, with each path’s fill derived from the JSON-stringified property tags.

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Let's make a bar chart with D3.js

This bar chart displays the populations of ten countries, with bars extending horizontally from a left-aligned axis. The visualization uses D3.js v5 within a React framework to load CSV data and render SVG elements, employing `d3.scaleLinear` and `d3.scaleBand` for proportional scaling. It generates left and bottom axes via `d3.axisLeft` and `d3.axisBottom`, and appends rectangles through a data join to encode population values.

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Selecting a Year on a Line Chart

This line chart displays population trends over time for global regions, with a draggable vertical line enabling year selection. The chart updates dynamically as users hover, highlighting the selected year across all series. Built with D3 v5, it uses `nest()` for data grouping, `scaleTime` and `scaleLinear` for axes, and `line()` with `curveBasis` for smooth paths. Data comes from UN population estimates (1950-2100), with a color legend and axis labels rendered as SVG elements.

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Melting Data for Multiple Lines

This visualization displays population over time by region, with each line representing a different area and a color legend identifying them. The chart uses d3.csv to load UN population data, which is then processed using d3.nest to group data by region. The code demonstrates a data-wrangling technique called "melting," transforming wide-format data with columns per year into tidy data with year, name, and population fields. Multiple lines are drawn using d3.line and curveBasis, with d3.scaleTime and d3.scaleLinear handling the axes and d3.scaleOrdinal applying colors.

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Line Chart with Multiple Lines

This visualization displays one week of temperature data from cities worldwide, using a multiline chart to compare trends over time in degrees Celsius. Each city’s temperature series is drawn as a distinct colored path, with a color legend identifying the cities. The chart is built with D3 v5, using scales and axes for time and temperature, and the `line` generator with `curveBasis` for smoothing. Data is loaded from a CSV, parsed, and nested by city, with rendering handled via SVG.

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scatter plot with menus

This interactive scatter plot lets users explore the relationship between any two numeric columns of the auto-mpg dataset, which is loaded via `d3.csv`. Two dropdown menus, built with the custom `dropdownmenu` function and D3’s `select` data join, control which columns appear on the x- and y-axes. The chart itself is rendered as SVG using D3 scales and axes, with circles that transition smoothly to new positions over 2 seconds when a menu selection changes. Axis labels update dynamically, and the visualization uses the margin convention with gridlines from `d3.axisBottom` and `d3.axisLeft`.

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blank canvas

A blank SVG canvas fills the browser viewport, with a single rounded rectangle drawn to match the full window dimensions. The example demonstrates the minimal setup for a D3.js visualization within a React framework, using d3.select to target the SVG element and append a rect with computed clientWidth and clientHeight. The rect’s rounded corners are set via the rx attribute, while the body’s fixed positioning and hidden overflow ensure the canvas remains static and edge-to-edge.

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bowl of fruit-hover to select

Five circles initially render as apples in a red-to-yellow color scale, with hover events highlighting the selected fruit via a black stroke. Using d3.v5 data joins and transitions, the example animates circle radius and position changes while updating the selection state through callbacks. Over sequential timeouts, the visualization removes fruits and mutates an apple into a lemon, demonstrating enter, update, and exit selections with d3.scaleOrdinal for color and radius values.

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bowl of fruit-click to select

Five circles representing apples appear in a row and animate into place, with a black outline highlighting the selected fruit. The data join in d3.v5 handles entering, updating, and exiting circles through transitions, as apples are removed, replaced with a lemon, and filtered over time. Clicking a circle triggers a re-render via the `fruitbowl` module, which uses `scaleOrdinal` for color and radius mapping, while SVG transitions animate the changes.

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bowl of fruit-general update pattern

This example demonstrates the D3 general update pattern with a bowl of fruit that changes over time. Initially showing five red apples, the visualization removes a fruit after one second, changes one apple to a yellow lemon after two seconds, and filters out another fruit after three seconds. The code uses `d3.scaleOrdinal` for color and radius mapping, `selection.data()`, `.enter()`, `.merge()`, and `.exit()` to handle enter, update, and exit selections. SVG circles and text elements render the fruit with `d3.v5`.

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bowl of fruit-general update pattern

Five circles represent a bowl of fruit, starting as red apples and dynamically updating through D3's general update pattern. The example demonstrates enter, update, and exit transitions as fruits are removed, a lemon replaces an apple, and an item is deleted. Using `d3.select`, data joins, and `.transition().duration(1000)`, circles animate their radius and x-position while the SVG scales fruit size, color, and position via `scaleOrdinal`.

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temperature in sanfrancisco area chart

This visualization shows daily temperature variations in San Francisco with a smooth area chart over time. The chart uses a time-scaled x-axis for timestamps and a linear y-axis for temperature readings, filled with a maroon area beneath the curve. Built with React and rendered as SVG, the code leverages D3 v5 utilities including `scaleTime`, `scaleLinear`, `area` with `curveBasis`, and `axisBottom`/`axisLeft` for labeled axes. Data is loaded from a remote CSV file containing timestamp and temperature values.

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temperature in sanfrancisco

This visualization displays temperature readings in San Francisco over time, using a smooth line chart to reveal trends and fluctuations in the data. The chart is rendered as an SVG within a React framework, with D3 v5 handling the core visualization logic. The code employs `scaleTime` and `scaleLinear` for the axes, `line` with `curveBasis` for the smoothed path, and `axisBottom` and `axisLeft` to generate the labeled ticks. Temperature and timestamp values are parsed from a CSV file fetched from VizHub, with the line styled in maroon.

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cars scatter plot

This visualization shows the relationship between horsepower and weight for a collection of cars, with each car represented as a semi-transparent steel-blue circle. The scatter plot includes labeled axes, a title, and gridlines to aid readability. Built with React and D3 v5, the code uses `d3.csv` to load the auto-mpg dataset, `d3.scaleLinear` and `d3.extent` for scales, and `d3.axisBottom` and `d3.axisLeft` for the axes. All elements are rendered as SVG, leveraging the margin convention to position the plot within the fixed 960x500 canvas.

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scatter plot

This scatter plot displays the population of the top 10 most populous countries, with each country positioned along a point scale on the y-axis and population mapped to a linear scale on the x-axis. Circles encode the data values, and axes include tick marks and formatted labels. The visualization uses D3 v5 APIs including `csv`, `scaleLinear`, `scalePoint`, `axisLeft`, and `axisBottom` within a React project, rendering to SVG with margins and a title. Population data is loaded from a CSV file and multiplied by 1000.

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customizing Axes

This example visualizes the top 10 most populous countries as a horizontal bar chart, using a linear scale for population and a band scale for country names. It customizes both axes by removing unnecessary lines, adding tick marks across the chart, and formatting population labels with abbreviations like “B” for billions. The code uses D3 v5’s `scaleLinear`, `scaleBand`, `axisLeft`, `axisBottom`, and `format` functions within a React framework, rendering SVG elements and styling them via external CSS.

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Let's make a face with D3.js

This example builds a simple cartoon face from basic SVG shapes, including circles for the head and eyes, rectangles for eyebrows, and a path for the mouth. The face is grouped and centered within the SVG canvas. The animation is driven by D3 transitions, which sequentially move the eyebrows downward over two-second intervals. The code uses D3 v5's selection, arc, and transition APIs to construct and animate the elements, with the mouth generated using the `d3.arc` geometry generator to create a curved path.

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HTML Cars Report

This example shows a simple HTML cars report page with a bulleted list of car model years and an accompanying SVG graphic. The page uses plain HTML and CSS, with React as the framework, though the visible code is static markup. The SVG renders a circle and a blue rectangle, while the CSS styles the body with a monospace font and highlights the first list item in red. Data is presented as hardcoded text within the HTML list, and no JavaScript interactions are demonstrated.

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Hello VizHub

This example displays a single, large "Hello VizHub!" message centered on a dark blue background with white Ubuntu typography. The visualization demonstrates the basic structure of a VizHub project using D3.js, where the `select` API targets the `#message` div to set its text content. The text itself is imported from a local ES6 module, `myMessage.js`, showcasing modular code organization. The page loads D3 v5 and applies styling from an external stylesheet that defines the layout and color scheme.