Christian Lawson-Perfect @christianp

5 posts5 participants0 posts today

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

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/114376279976367936

#RStats #PyData #JuliaLang

**Nicola Rennie** @nrennie@fosstodon.org · 1d

Nicola Rennie @nrennie@fosstodon.org

For this week's #TidyTuesday data about car crashes in the USA, I decided to take the simple approach of plotting every data point.

Jittered scatter plot made with #ggplot2
Over 1.3 million points drawn
Noticeable reduction after 2008 (ish)

Code: https://github.com/nrennie/tidytuesday/tree/main/2025/2025-04-22

A calendar showing fatal car crashes in the United States from 1994 to 2017. Each row represents a year and each column represents a day of the year, from January to December. Darker purple squares indicate days with a higher number of fatalities, revealing seasonal patterns and spikes across years.

#RStats #DataViz

**Jon Harmon** @jonthegeek@fosstodon.org · 2d

Jon Harmon @jonthegeek@fosstodon.org

Curator: @jonthegeek
https://DSLC.io welcomes you to week 16 of #TidyTuesday! We're exploring Fatal Car Crashes on 4/20!

https://tidytues.day/2025/2025-04-22
https://osf.io/preprints/osf/tzcsy_v1

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.

Two plots entitled Daily Mean Fatality Count, 1992-2016, and Daily Mean Fatality Count in April, 1992-2016. The top plot shows fatalities on the y-axis, and day of year on the x-axis. April 20 is marked with a dashed line, and does not appear to be significantly higher than other days of the year. Fatalities are much higher on January 1st, and generally higher in the months following April than at the beginning of the year. The second plot shows fatalities by day of the year within the month of April. The 20th (day 110 in the year) is approximately in the middle of fatality counts for April. Error bars on both plots are noted as representing 95% bootstrapped confidence intervals. Both plots were generated using code provided by @Rmadillo on GitHub.

#RStats #PyData #JuliaLang

**Dan Oehm** @danoehm.bsky.social@bsky.brid.gy · 2d

Dan Oehm @danoehm.bsky.social@bsky.brid.gy

#TidyTuesday week 15: Base R Penguins Code github.com/doehm/tidytu... Gallery github.com/doehm/tidytues #dataviz #Rstats #ggplot2

**Steven Ponce** @sponce1@graphics.social · Apr 16

Apr 16

Steven Ponce @sponce1@graphics.social

#TidyTuesday – 2025 W15 | Base R Penguins
.
: https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2025/tt_2025_15.html
.
#rstats | #r4ds | #dataviz | #ggplot2

A scatterplot showing bill dimensions (length vs. depth in mm) for three penguin species with density contours. The plot clearly displays three distinct clusters: Adelie penguins (orange, n=152) with shorter, deeper bills centered around 40mm length; Chinstrap penguins (blue, n=68) with medium-length bills around 49mm and greater depth; and Gentoo penguins (green, n=124) with longer, shallower bills around 48mm length and 15mm depth. Diamond markers indicate species means.

**Nicola Rennie** @nrennie@fosstodon.org · Apr 16

Apr 16

Nicola Rennie @nrennie@fosstodon.org

A quick plot for #TidyTuesday this week - celebrating the addition of the `penguins` data into base R I used {ggdist} to visualise the distribution of body weights with four different chart types in one!

I couldn't quite decide whether I prefer the light or dark version

Code: https://github.com/nrennie/tidytuesday/tree/main/2025/2025-04-15

Three box plot/density plot/rainfall plots showing body weight for three penguin species, with Gentoo significantly higher. Colours also show density, and species. Background is light with dark text.

#RStats #DataViz #ggplot2

**DataScienceLearningCommunity** @DSLC@fosstodon.org · Apr 15

Apr 15

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/114336585969522119

#RStats #PyData #JuliaLang

**Fonti Kar** @fontikar@fosstodon.org · Apr 15

Apr 15

Fonti Kar @fontikar@fosstodon.org

My #rstats friends - R-Ladies Canberra x Melbourne x Sydney are thrilled to bring you a #TidyTuesday event!

Come along, connect with the community + stretch your data muscles All coding experience levels are welcome!

: Tue May 6
: 1:00 PM AEST
: bit.ly/42rFX2D

We can't wait to see you there!

**Jon Harmon** @jonthegeek@fosstodon.org · Apr 14

Apr 14

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

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

**Nicola Rennie** @nrennie@fosstodon.org · Apr 9

Apr 9

Nicola Rennie @nrennie@fosstodon.org

For this week's #TidyTuesday, we're looking at healthcare efficiency in the USA I wanted to create a very minimalist data-art plot, with tooltips that give more information

Map grid from {geofacet}
Interactive tooltips with {ggiraph}
Styling with CSS

A square tile map of the United States shows how timely and effective emergency medical care is for stroke symptoms. Each square represents a U.S. state, shaded in varying tones of purple to indicate the percentage of stroke patients who received brain scan results within 45 minutes of arrival, between April 2023 and March 2024. The national average is 66%. A tooltip highlights New Mexico with 41%, noting this is below the national average. Data is from the Centers for Medicare and Medicaid Services, and the graphic is by @nrennie.

#DataViz #RStats #ggplot2

**DataScienceLearningCommunity** @DSLC@fosstodon.org · Apr 8

Apr 8

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

**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

**Nicola Rennie** @nrennie@fosstodon.org · Apr 2

Apr 2

Nicola Rennie @nrennie@fosstodon.org

We're looking at Pokemon data for #TidyTuesday this week!

Stream plot showing speed and colour using {ggstream}
Image added with {ggimage}
Aiming for a minimalist, fun, and arty chart

Code: https://github.com/nrennie/tidytuesday/tree/main/2025/2025-04-01

Stream chart showing number of pokemon of different colour and the speeds they have

#RStats #DataViz #ggplot2

**Tan G.** @tangandhara.bsky.social@bsky.brid.gy · Apr 1

Apr 1

Tan G. @tangandhara.bsky.social@bsky.brid.gy

#30DayChartChallenge - Day 1: Fractions Everyone's talking about Trump and tariffs but how much longer do we have to put up with his crap? Sadly, we're just under 5% of the way through so have a long way to go. #rstats #dataviz #TidyTuesday

The Orange Peril
"How much of the Trump presidency do we have left?"
"We've survived 4.9% of Trump 2.0"
"But there's still 95.1% of Trump 2.0 remaining"

**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 · 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.

**David** @dmendsev@pixelfed.social · Mar 31

Mar 31

David @dmendsev@pixelfed.social

Week 13 of #tidytuesday. #pokemon. I was aiming to show how specific type of pokemons get stronger or weaker in each generation but not super convinced of the result
#rstats