Dot Plot

p5.js.billionaires.dotPlot

This dot plot visualizes the relationship between billionaire inheritance type and total wealth, with each circle representing an individual. Data is loaded from a remote CSV file using p5.js `loadTable` in `preload()`. The sketch draws axes, gridlines, labels, and data points via the p5.js `circle()` function, mapping wealth values to x-coordinates and inheritance categories to y-positions. The visualization uses a dark background and blue circles to distinguish data points.

83% match

Billionaires Dot Chart

This dot plot visualizes the founding years of ten billionaire-owned companies, with each dot positioned along a horizontal axis scaled to represent the year founded and labeled vertically by company name. Hovering over a dot displays its approximate founding year. Built with the p5.js library, the sketch loads a CSV file from a GitHub Gist using `loadTable()`, sorts the year data, and renders interactive circles with custom hit-testing via `mouseOnHover()`. Axis labels, tick marks, and a legend are drawn directly on the canvas.

AAllen Ho

82% match

Scatterplot in D3

This scatterplot visualizes the relationship between the age and wealth of billionaires, sourced from a CSV file. Each purple circle represents a billionaire, with its position determined by age on the x-axis and wealth in billions on the y-axis. The visualization uses D3.js version 7 within an SVG rendering to create the plot, axes, and labels. The code employs `d3.csv` to load the data, `d3.scaleLinear` for scaling, and `d3.axisBottom` and `d3.axisLeft` to construct the chart axes.

RRiya Mathur

81% match

dot

This dot-and-bar visualization displays the relationship between inherited type and total net worth for billionaires, plotting categorical data along the x-axis and numerical worth values scaled vertically. The sketch loads a CSV dataset from a GitHub gist using the `loadTable` function in Processing (via p5.js), then draws axes, gridlines, and text labels on an 800×800 canvas. Bars represent worth values, with labels for inherited types positioned below, while the y-axis includes tick marks and numeric increments.

bi_scatter

This scatterplot uses p5.js to visualize the relationship between billionaires' age and net worth, drawing data from the included billionaires.csv. The chart plots each billionaire as a green dollar sign on a canvas with age on the x-axis and net worth in billions on the y-axis. Interactive tooltips display the individual's name, age, and net worth when the mouse hovers near a point. The visualization filters out entries with missing age values and includes axis labels and a title. The code is written in p5.js and loads data from a CSV file, mapping age to horizontal position and net worth to vertical position, with a manual coordinate transformation for the axes.

BByronHan333

dotplot_billionaires.p5.js

A dot plot shows the average net worth in billions for billionaires grouped by inheritance type, ranging from spouse or widow at $4.53 billion to fifth-generation at $2.64 billion. Built with p5.js, the sketch loads a remote CSV via `loadTable` in `preload`, then draws axes, gridlines, labels, and blue circles positioned by scaling each value along the x-axis in `draw`. The data comes from the Corgis billionaires dataset, filtered to two columns and averaged per category.

Assignment 3 - Histogram - P5.js

This visualization displays a boxplot of billionaire ages from the billionaires.csv dataset, summarizing the distribution through quartiles, median, and outliers. It highlights the interquartile range with a colored rectangle, extends whiskers to the upper and lower fences, and marks outlier values as grey circles. Built with p5.js, the sketch loads the CSV in `preload()`, calculates statistical measures in `cleanData()`, and renders interactively in `draw()`. A tooltip appears when the mouse hovers over the box, revealing the computed five-number summary values.

SSimon Hackbert

dotplot.billionaires.p5.js

This dot plot compares the average net worth of billionaires across different inheritance categories, from non-inherited wealth to those inherited through a spouse or widow. The p5.js sketch loads a filtered CSV dataset from the Corgis billionaires collection via `loadTable`, then renders labeled axes with tick marks and grid lines. It places each category label along the x-axis while computing the plotted positions from the average worth values in billions, though the visual encoding relies on the canvas drawing API rather than a dedicated charting library.