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Data Is Plural Submissions: Bob Ross

This edition of the Data Is Plural visualization challenge prompted readers to explore two complementary data sets on Bob Ross’s iconic television show from the 1980s and ’90s, The Joy of Painting. Check out the submissions:


Erin Klingmann: Entitled “You too can paint an almighty picture,” this unconventional “paint by numbers” area chart was inspired by Ross’ gentle encouragement in Episode 1: “You too can paint an almighty picture.” It invites the reader to pick up their pencil crayons and discover firsthand the amount of each colour used throughout the TV series. (I decided to focus on colour and exclude the three mediums that were part of Jared Wilber’s original dataset.) The chart itself is built on a background grid of 4,108 colour-coded dots, with one dot for every time that colour was used in an episode. It took a few tries (and a lot of counting) to create an image that worked with the correct number of dots per colour AND showcased Ross’ five most common motifs.

Paint by numbers scene with trees, mountains, grass, and a lake, with instructions showing which of 15 colors to use for each section, starting with Titanium white (used in 400 episodes) and ending with Indian Red (used in 1 episode).

Cornelia Hüsser: I recently started exploring Tableau and created a viz about Bob Ross’ paintings, sorted by season and episode. You can explore his favourite elements from Walt Hickey’s dataset and see when and how often he used each one. The background image was generated with Craiyon, an online AI image generator. You can find the dashboard here.

A grid of dots of varying sizes to the right of a word cloud (the largest word is "trees"), with a happy photo of Bob Ross painting in the upper left.

Elsie Lee-Robbins: Entitled “The Joy of Painting Data,” this is a stacked area chart of elements that appear in Bob Ross paintings each season: clouds, sun, snow, mountain, conifer trees, deciduous trees, bushes, river, lake, grass, and rocks. Percentages add up to 100 on the y-axis, with seasons from 1-31 on the x-axis. The data is painted on canvas with oil paints with slight variations in color within sections and visible brushstrokes. Inspirations were Michael Correll’s Ross-Chernoff Glyphs, Gabrielle Merite, Jill Pelto, and Alai Ganuza.

A hand painted area chart with canvas and brush strokes visible. The dark green section for conifers and bright green section for deciduous trees appear largest.

Arielle Kan: To represent Bob Ross as a painter, I wanted to visualize the data in a more artistic form – one large painting. Taking inspiration from an episode of NCIS TV show where a girl hid important information in a colorful geometric collage by encoding them like bar codes, I decided on a much simpler construction of the visualization’s background. It is made up of 403 vertical stripes, each stripe containing the colors used in one painting. The foreground is an abstract depiction of the 2 most common elements used in his paintings – trees and mountains. The curves and swirls can be thought of as annual growth rings in the cross-section of tree trunks, and also as topographic representation of mountains.

Abstract art with colored bars making up the background and loose white swirls resembling a topographic map overlaid on top

Louise Shorten: 403 paintings featured across 31 seasons of the Bob Ross show The Joy of Painting, each with 13 episodes. Season 1, Episode 1 is situated at the 12 o’clock point, and the visualisation can be read clockwise from there. The size of the outer circles represents the number of colours used. I published an interactive version of the viz to Tableau Public. It allows interaction and navigation to the images/Youtube links.

Concentric circles of colored bars, each circle one color, representing the paintings in which each color was used.

Xan Gregg: Noticing that Bob Ross painting titles are fairly descriptive, I made this visualization to look at paint color breakdown by title word. I attempted to un-mix the colors from each painting into the paints used (caveats: some images were cropped and color mixing is hard). Separately, I split each title into words, removed common words and merged similar words. Then I combined the two data sets to get the color breakdown by title word. Guest painters are excluded. For each title word visualization, the area of each paint color corresponds to its inferred usage in the painting, including the black frame and white header. Title word panels are ordered by amount of white (vertical) and green (horizontal). I used JMP for both the data wrangling and the custom visualization.

Entitled "Unmixing Bob Ross paintings: paint profile by title word," a grid of small multiples, each showing a bar code chart with the colors used in paintings for given words appearing in the paintings' titles (e.g., "Snow" shows mostly brown and blue and almost no green)

Chunwei Ma, Meichen Dong, Xan Gregg, Russ Wolfinger, JMP Statistical Discovery, LLC: Of all the painting masters, from the Renaissance to Expressionism, from Leonardo da Vinci to Andy Warhol, whose work mostly inspired Bob Ross? Equipped with the new Deep Learning add-in, JMP Pro empowers us to answer this question exploratorily and visually. By virtue of large-scale online artist databases like WikiArt and Web Gallery of Art, a dataset containing 8683 paintings from 50 artists is curated. A deep neural network is trained using JMP Pro. The top 12 artists giving the highest scores for Bob Ross’s 403 paintings are used to create a Circos plot. Nine representative Bob Ross paintings are shown in which the curve width indicates the similarity. Interestingly, the French Impressionist Edgar Degas (1834-1917) and Peter Paul Rubens (1577-1640) of the Flemish Baroque tradition are the two most influential painters on Bob Ross.

A neon-colored chord diagram showing connections between famous artists (represented with circular headshots along the edge of the diagram) and Bob Ross paintings (also shown with circular images)

Luisa Bider and the Flourish Team: We plotted each pixel in the painting “Meadow Lake” in the nearest color to the one supplied in the dataset and ended up with a grid of scatter plots showing which parts of the painting used which color. It’s reminiscent of the layered approach to printing. An interactive version of this is available here.

A grid of small multiples, each showing only the pixels of a certain color used in a single painting, entitled "Is it a painting? Is it a scatter plot?"

Sian Phillips: This visualisation explores the colour palette of Bob Ross. It uses data collected from his long-running television programme; ‘The Joy of Painting’. I was interested in producing a summary of where his colours came from on the traditional colour wheel, how they were used together, and how his palette may have changed over time. I used three different visualisations in my figure to answer these questions: a chord diagram, a dot plot timeline, and a colour wheel. The visualisations were created using a mixture of R and d3.js, and finishing touches were added using InDesign.

Three charts arrayed together: a color map with annotations calling out specific colors used in the top left, a chord diagram showing color combinations in the top right, and a timeline showing color use by episode across the bottom.

Emilia Ruzicka: This is a digital painting using the same colors that Bob Ross used throughout The Joy of Painting. The colors of the squares are determined by each of the paint colors that Ross used on his show. Each square shows one use of that color. Inspired by Ross’ works, the squares have been rearranged into a field of flowers and a hilly landscape, complete with happy little clouds in the sky.

A pixelated grid depicting a field of flowers with three white clouds in the sky

Winnie Poel: Entitled “Colors of Joy”—Over 12 years and 31 seasons full of ‘happy little accidents’, Bob Ross’ show ‘The Joy of Painting’ has produced 403 original paintings and inspired millions. Here, each painting is represented by its composition of its main five colors (obtained by k-means clustering). Paintings are arranged on a circular time axis at the time they originally aired. Temporally coherent rows of paintings constitute one season. Most seasons start in January and late August, but what else can you discover? Do colors get darker over the years and is Bob painting more bright and colorful when he is waiting for spring to arrive?

A circular depiction of the 5 main colors used in each episode in each month and year from 1983 to 1994.

Kerry Kolosko: Remembering that the artistic style of artists such as Monet and Remembrandt evolved due to deteriorating eyesight, I became interested in examining whether and how Bob Ross’ paintings underwent changes over the years. Acknowledging that the outcomes could be influenced by the quality of the photograph, I used Python to extract the primary colors and their corresponding percentages from the images listed in the dataset then created pie charts of the dominant colors for each painting. This simple visual allowed me to get a quick overview to satisfy my curiosity before exploring the data further.

A grid of small multiple pie charts showing dominant colors by episode and season
Nightingale Editors

Our Nightingale editorial team currently consists of Alejandra Arevalo, William Careri, Jason Forrest, Elijah Meeks, and Teo Popescu. Reach us at Nightingale(at)Datavisualizationsociety.org