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**Jon Harmon** @jonthegeek@fosstodon.org · 12h

12h

Jon Harmon @jonthegeek@fosstodon.org

Curator: @jonthegeek
https://DSLC.io welcomes you to week 15 of #TidyTuesday! We're exploring Base R Penguins!

https://tidytues.day/2025/2025-04-15
https://zenodo.org/records/14902740

Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md

TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results!
TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club!

How to Participate
Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data.
Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data.
Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language.
Share your output and the code used to generate it on social media with the #TidyTuesday hashtag.

Scatterplot titled 'Flipper and bill length' showing the relationship between flipper length (x-axis, in mm) and bill length (y-axis, in mm) for three penguin species at Palmer Station LTER. Adelie penguins are represented by orange circles with a slight positive trend line. Chinstrap penguins are shown with purple triangles, clustering higher on the bill length axis and a steeper trend line. Gentoo penguins are shown with dark green squares, positioned farther right along the flipper length axis, with their own upward trend line. A legend at the bottom right indicates the color and shape used for each species. The image is from the palmerpenguins R package.

#RStats #PyData #JuliaLang

**Steven Ponce** @sponce1@graphics.social · 17h

17h

Steven Ponce @sponce1@graphics.social

A lollipop chart showing NBA player combinations organized by playstyle groups (Offensive-Minded, Developing Chemistry, Two-Way Elite, and Defensive-Minded). Each horizontal line represents a player pair with team affiliations in parentheses, extending to points indicating their win percentage. The Offensive-Minded category tops the chart with the highest win rates (up to 90%), dominated by New York Knicks players. Colors differentiate the playstyle groups: yellow for Offensive-Minded, blue for Developing Chemistry, red for Two-Way Elite, and purple for Defensive-Minded. The visualization demonstrates which player relationships produce the most wins across different playing styles and teams.

**Steven Ponce** @sponce1@graphics.social · 1d

Steven Ponce @sponce1@graphics.social

A scatter plot showing the relationship between NBA players' defensive contributions (steals plus blocks per game) and 3-point shooting percentages. Four distinct clusters identified through K-means clustering reveal player archetypes: Two-Way Stars (upper right), Defensive Specialists (upper left), Offensive Specialists (lower right), and Role Players (lower center). Notable players like Victor Wembanyama stand out as elite two-way performers. Dashed lines indicate league averages for both metrics, creating quadrants with annotations describing each player archetype's characteristics.

**Steven Ponce** @sponce1@graphics.social · 2d

Steven Ponce @sponce1@graphics.social

A line graph showing Empirical Cumulative Distribution Functions (ECDF) of Annual Average Daily Traffic across ten California counties. The x-axis shows traffic volume from 100 to over 100,000 vehicles on a logarithmic scale. Horizontal dashed lines mark the 25th, 50th, and 75th percentiles. Urban counties like Los Angeles (LA) and Orange (ORA) show curves shifted right, indicating higher traffic volumes. In contrast, rural counties like Tulare (TUL) show curves shifted left, indicating lower traffic volumes.

**Steven Ponce** @sponce1@graphics.social · 3d

Steven Ponce @sponce1@graphics.social

A dotplot showing the distribution of assist-to-turnover ratios for NBA teams in the 2024 season. Teams are sorted vertically by median ratio, with Jazz at the top and Celtics at the bottom. Purple circles represent players, with larger circles indicating more players with that specific ratio value. Most players cluster between ratios of 1.0-2.5. Alternating gray background stripes highlight each team row. A vertical dashed line marks the league median.

**Steven Ponce** @sponce1@graphics.social · 4d

Steven Ponce @sponce1@graphics.social

Ridge plot showing the distribution of offensive rebounding ratios across NBA positions. Multi-modal patterns are visible, with annotations highlighting different player types: Defensive-focused and Balanced Power Forwards, Perimeter and Inside Forwards, and Traditional and Offensive-focused Centers. Centers show highest ratios around 0.4, while guards have lower ratios centered around 0.2.

**Steven Ponce** @sponce1@graphics.social · 5d

Steven Ponce @sponce1@graphics.social

A diverging bar chart titled "NBA 2023-24: Players with the Highest and Lowest Impact" showing Plus/Minus statistics for NBA players. The horizontal bars extend right (green) for positive impact and left (red) for negative impact. Nikola Jokić leads with +682, while Miles Bridges has the lowest at -633. The visualization includes 50 players who played minimum 15 minutes per game for at least 40 games.

**DataScienceLearningCommunity** @DSLC@fosstodon.org · 6d

DataScienceLearningCommunity @DSLC@fosstodon.org

It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io/join (find the #chat-tidytuesday channel)!

RT @jonthegeek https://fosstodon.org/@jonthegeek/114297010745251048

#RStats #PyData #JuliaLang

**Steven Ponce** @sponce1@graphics.social · 6d

Steven Ponce @sponce1@graphics.social

A histogram showing the distribution of points per game for NBA players in the 2023-24 season, comparing starters versus bench players. Bench players (orange bars) are concentrated at lower scoring ranges with a mean of 5.3 PPG, while starters (blue bars) show a broader distribution with higher scoring averages and a mean of 14.5 PPG. Vertical dashed lines indicate the mean values for each group.

**Jon Harmon** @jonthegeek@fosstodon.org · Apr 7

Apr 7

Jon Harmon @jonthegeek@fosstodon.org

Curator: @jonthegeek
https://DSLC.io welcomes you to week 14 of #TidyTuesday! We're exploring Timely and Effective Care by US State!

https://tidytues.day/2025/2025-04-08
https://www.visualcapitalist.com/mapped-emergency-room-visit-times-by-state/

Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md

Infographic titled 'Emergency Room Visit Times by State' from the Visual Capitalist, showing a map of the U.S. with each state color-coded based on average ER visit times, ranging from 1 hour 50 minutes for North Dakota to 5 hours 14 minutes for the District of Colombia. At the top, diverse individuals are seated in a waiting room. The source is the U.S. Centers for Medicare & Medicaid Services, 2024. More details about the graphic are available at https://www.voronoiapp.com/healthcare/People-in-DC-Spend-Over-5-Hours-On-Average-In-the-Emergency-Room--3590

#RStats #PyData #JuliaLang

**Steven Ponce** @sponce1@graphics.social · Apr 7

Apr 7

Steven Ponce @sponce1@graphics.social

A boxplot showing field goal percentage distribution across NBA teams for the 2023-24 season. Teams are ordered vertically by median percentage, with Indiana at the top. Statistical outliers are highlighted as red dots. A dashed blue vertical line indicates the league mean FG%. The chart reveals which teams have more consistent shooting performance versus those with extreme outlier games.

**Steven Ponce** @sponce1@graphics.social · Apr 6

Apr 6

Steven Ponce @sponce1@graphics.social

A Florence Nightingale-inspired rose diagram comparing shooting efficiency metrics (Field Goal %, 3-Point %, Free Throw %, and True Shooting %) among three NBA stars: Joel Embiid (red), Nikola Jokic (blue), and Stephen Curry (teal). The diagram highlights Curry's superior free throw percentage (92.3%), Jokic's leading field goal percentage (57.8%) and true shooting percentage (64.7%), and Curry's top 3-point percentage (40.6%).

**Steven Ponce** @sponce1@graphics.social · Apr 5

Apr 5

Steven Ponce @sponce1@graphics.social

A bump chart showing GDP ranking changes from 1960-2020 for major economies. China (in bold red) started at 5th place in 1960, dropped to 8th by 1980, began rising after joining the WTO (highlighted in pink), and reached 2nd place by 2020. The US remains consistently in 1st place throughout the period, while Japan and other economies show various ranking changes. GDP values in trillion USD for 2020 are displayed.

**Steven Ponce** @sponce1@graphics.social · Apr 4

Apr 4

Steven Ponce @sponce1@graphics.social

Treemap visualization titled 'Preserving Public Health Knowledge: CDC Dataset Categories at Risk' showing the distribution of archived CDC datasets by category. The largest categories are NNDSS (293 datasets, 23.3%) and NCHS (184 datasets, 14.6%), which together represent over a third of all preserved data. Other significant categories include Vaccinations (78 datasets), Public Health Surveillance (68 datasets), and 500 Cities & Places (57 datasets). Smaller categories include Policy, Funding, and Health Statistics. A color gradient from light orange to dark purple indicates dataset size from smallest to largest.

**Steven Ponce** @sponce1@graphics.social · Apr 3

Apr 3

Steven Ponce @sponce1@graphics.social

A circular heatmap showing San Juan's monthly temperature patterns from 2014-2024. The visualization arranges months in a circle with years radiating outward. Temperature is displayed through a purple-to-yellow color gradient, with cooler winter temperatures (December-February) in purple and warmer summer temperatures (July-September) in yellow. The pattern reveals San Juan's consistent tropical seasonal cycle.

**Steven Ponce** @sponce1@graphics.social · Apr 2

Apr 2

Steven Ponce @sponce1@graphics.social

A slope chart showing internet adoption rates across age groups from 2000 to 2024. The 65+ age group shows the steepest slope, rising from 14% to 90%, dramatically narrowing the gap with younger groups. Other age groups (18-29, 30-49, and 50-64) all reached nearly 99% adoption by 2024, despite starting at different levels (70%, 61%, and 46%, respectively).

**DataScienceLearningCommunity** @DSLC@fosstodon.org · Apr 1

Apr 1

DataScienceLearningCommunity @DSLC@fosstodon.org

It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io/join (find the #chat-tidytuesday channel)!

RT @jonthegeek https://fosstodon.org/@jonthegeek/114257310205493006

#RStats #PyData #JuliaLang

**Steven Ponce** @sponce1@graphics.social · Apr 1

Apr 1

Steven Ponce @sponce1@graphics.social

A diverging stacked bar chart comparing scurvy treatments from 1757. Only citrus shows 100% of patients with improvement (50% none, 50% mild symptoms), while all other treatments show moderate to severe symptoms. Dilute sulfuric acid shows 50% mild improvement. The chart demonstrates why citrus was the only effective treatment for scurvy.

**Steven Ponce** @sponce1@graphics.social · Mar 31

Mar 31

Steven Ponce @sponce1@graphics.social

#TidyTuesday – 2025 W13 | Pokemon
.
: https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2025/tt_2025_13.html
.
#rstats | #r4ds | #dataviz | #ggplot2

A beeswarm plot showing speed distribution across Pokémon types. Types are ordered by average speed, with Flying and Electric types at the bottom (fastest) and Rock near the top (slowest). Purple diamonds mark the mean speed for each type, and a vertical dashed line at 100 indicates the "Fast" threshold. Most Pokémon fall between 50-100 speed, with outliers reaching up to 150.

**Jon Harmon** @jonthegeek@fosstodon.org · Mar 31

Mar 31

Jon Harmon @jonthegeek@fosstodon.org

https://DSLC.io welcomes you to week 13 of #TidyTuesday! We're exploring Pokemon!

https://tidytues.day/2025/2025-04-01
https://medium.com/@hanahshih46/pokemon-data-visualization-and-analysis-with-r-60970c8e37f4

Submit a dataset! https://github.com/rfordatascience/tidytuesday/blob/main/.github/CONTRIBUTING.md

Image shows faceted scatterplots of pokemon dataset. Attack is on the x-axis, and defense is on the y-axis. The primary pokemon color is indicated with the color of the points, and the charts are faceted by pokemon type. The breakdown highlights a somewhat linear relationship between attack and defense for most pokemon types. For the most part, they are correlated, with defense and attack increasing together. There is less variance between the two variables when type is "dragon", "electric", or "normal". Noticeable types that break this trend are "rock" type pokemon. In addition, there are a few outliers, such as a "bug" type with a near-zero attack and defense above 200 hp.

#RStats #PyData #JuliaLang

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