Box Plot with p5.js

100%

Box Plot with p5.js

✓ Published1🌍 Public

Last edited Mar 4, 2022

Created on Feb 14, 2022

This visualization displays box plots of California birth rates per 1000 people across seven years, with each plot summarizing the distribution for a given year. The p5.js sketch loads CSV data via `loadTable()`, groups rows by year, and computes quartiles and median for each group. It renders colored rectangles for interquartile ranges, median lines, and whiskers using `rect()` and `line()`, with gridlines and axis labels drawn on an 800×500 canvas.

AI-generated description

A bare minimum HTML page demonstrating use of CSS and JavaScript.

Similar vizzes

Loading thumbnail…

Histogram with p5.js

This example displays a histogram of birth rates per 1000 in California for 2016, with age groups on the x-axis and counts on the y-axis. The visualization uses p5.js to load a CSV dataset via `loadTable()` in `preload()`, then renders bars with `rect()` and axis labels with `text()` and `line()`. The data comes from a GitHub gist, and the sketch draws gridlines, a title, and a rotated y-axis label using canvas transforms.

OOlha

85% match

Loading thumbnail…

Box Plot

This interactive p5.js visualization displays a box plot of California state expenditures from 1992 to 2019, with values loaded from a remote CSV file and normalized to units of $10 million. The sketch uses p5.js functions like `loadTable()`, `sort()`, and canvas drawing primitives (`line()`, `point()`, `text()`) to render the median, quartiles, and whiskers on a static 740x520 canvas, with axes and tick labels marking expenditure values.

PPranay Matalia

81% match

Loading thumbnail…

p5 box plot

This p5.js visualization displays a box plot of infection counts across US states from 1970 to 1980, using a dark-themed canvas. It renders the box, whiskers, median line, and outlier points from a CSV dataset, with axis labels and gridlines. The sketch implements mouseover tooltips for the box and individual outliers, showing quartile values and summary statistics. The code relies on p5.js functions like `map`, `loadTable`, and custom quantile calculations to position elements.

AAndrew

76% match

Loading thumbnail…

P5 BoxPlot

This example renders a boxplot of industrial natural gas prices in Hawaii using p5.js. It loads CSV data from a GitHub gist, computes quartiles and median from the price array, and draws the plot with rectangles, lines, and text labels. The chart displays minimum, maximum, and quartile values on a numeric scale, with axes marked from 0 to 800. The sketch uses p5.js functions like `loadTable`, `createCanvas`, and `rect` within the `setup` and `draw` loops.

Mmariahdiaz

76% match

Loading thumbnail…

Strip Chart without Randomizer Using p5.js

This example displays Florida birth rates per 1000 people from 1988 to 2016, grouped by year as a strip chart. It loads CSV data via p5.js’s `loadTable` function, then uses nested loops to draw horizontal gridlines, axis labels, and orange points with `point()` and `strokeWeight()`. The chart sorts values within each year and maps them to a fixed y-axis scale, while the p5.js `createCanvas` and `text()` functions render the visualization and annotations.

OOlha

75% match

Loading thumbnail…

Boxplot

This example renders a box plot using the p5.js library through its `rect()` and `line()` functions within the `draw()` loop. The visualization displays five-number summary statistics—minimum, first quartile, median, third quartile, and maximum—as a rectangular box with whiskers extending to the extremes. Synthetic data is generated directly in the sketch using JavaScript arrays and mathematical calculations. The plot is drawn on a canvas created by `createCanvas()`, with axes and labels positioned manually through coordinate arithmetic. The code demonstrates a straightforward implementation of statistical visualization without external data sources.

SShazil Taqi

75% match

Loading thumbnail…

Strip Chart with p5.js

This visualization shows birth rates per 1000 people in Florida from 1988 to 2016, grouped by year along the x-axis with rates plotted on the y-axis. It uses a strip chart format where individual data points are rendered as yellow dots, with a subtle randomized horizontal jitter applied to reduce overplotting. The code loads CSV data via p5.js’s `loadTable`, processes it into a dictionary keyed by year, and draws the chart using p5.js canvas functions like `point()`, `line()`, and `text()`. Axes labels and gridlines are manually constructed, and a fixed random salt stored in `localStorage` ensures consistent jitter across reloads.

OOlha

75% match

Loading thumbnail…

Box Plot

This example visualizes the distribution of salary data as a box plot, highlighting the minimum, first quartile, median, third quartile, and maximum values using a green box with a red median line. The data is loaded from a CSV file using p5.js’s `loadTable`, then processed and sorted in `setup` before a custom `drawBoxPlot` function renders the chart on a dimmed background. The code computes quantiles via a `quantile` helper function and uses p5.js drawing commands like `rect` and `line` to construct the plot directly on the canvas.

RRiya Mathur

74% match