Martin 2.0 @martinmuc

**Nicola Rennie** @nrennie@fosstodon.org · 7 Std.

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

#DataViz #RStats #ggplot2

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.

**Sharon Machlis** @smach@masto.machlis.com · 12 Std.

12 Std.

Sharon Machlis @smach@masto.machlis.com

Jazz up your ggplots:
‘Useful tricks to elevate your data viz via `ggplot` extension packages in R”
Custom themes, fonts, annotations, arrows & more
By the USGS
https://waterdata.usgs.gov/blog/ggplot-jazz/
#RStats #ggplot2 #ggplot #Dataviz

Jazz up your ggplots!waterdata.usgs.gov

**Nicola Rennie** @nrennie@fosstodon.org · 13 Std.

13 Std.

Nicola Rennie @nrennie@fosstodon.org

It's Day 9 of the #30DayChartChallenge, and the prompt is "Diverging"

Looking at % point change in wealth inequality between 2022 and 2023 in Europe
Made with D3
(Interactive version is large so text looks a little small in the screenshot!)

#Day9 #DataViz #D3

Diverging bar chart showing percentage point change in share of wealth of richest 1% between 2022 and 2023, with Austria most improved and Slovakia highest increase in inequality.

**Zack Labe** @ZLabe@fediscience.org · 1 T.

1 T.

Zack Labe @ZLabe@fediscience.org

My monthly #Arctic temperature graphics have just been updated through March 2025: https://zacklabe.com/arctic-temperatures/ #DataViz #SciComm #OpenScience #OpenData

Arctic TemperaturesZachary Labe

**Christian Gebhard** @basepair@scicomm.xyz · 1 T.

1 T.

Christian Gebhard @basepair@scicomm.xyz

Really looking forward to the upcoming workshop!
Together we’ll be discovering some exciting space ahead in datavisualization *mysterious teaser*

There’s still time to register!

#DataViz #Rstats #ggplot2 https://mastodon.social/@3xfactorial/114279473212804883

3xfactorial (@3xfactorial@mastodon.social)Mastodon

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

1 T.

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 #DataViz #tidyverse #r4ds

**Nullmuseum** @nullmuseum@hcommons.social · 1 T.

1 T.

Nullmuseum @nullmuseum@hcommons.social

Bald ist mein Buch fertig...

Kapitel 1 zur Transformation von Museen und zur parallelen Digitalisierung der Museen. Fallstudie SMB-digital 1990-2011

Kap. 2 zu Museen und Plattformkapitalismus

Kap. 3 zu semantischen Netzwerken (z.B. Auseinandersetzung mit Netzwerkvisualisierungen, 🢂Screenshot)

#museum #openglam #glam #dataviz #netzwerkvisualisierung #digitalarthistory #kunstgeschichte

Screenshot von Text:
Diese Bilderwolken sind durchaus als kritisches Instrument einsetzbar, wenn wir uns zum Beispiel fragen, welche Formen der Repräsentation quantitativ vorherrschen. Wir sehen sogar die Abwesenheit von anderen Repräsentationen durch die Lücken der Wolke. Die Bilderwolke ist kein Erkenntnismedium an sich, sondern erlaubt höchstens, sich die Macht der Sammlung im wahrsten Wortsinn vor Augen zu führen. Die Bilderwolken aber unkritisch als Vermittlungsmedien vorzustellen, wie es in vielen Projekten großer Museen passiert – als vermeintlich ‚neutraler‘ Überblick - zur Erkundung der Sammlungen, verharmlost hingegen die Macht der Sammlungen, die Macht der Repräsentation und der Deutungshoheit. Die ist nun nicht mehr explizit wie in einem Katalogtext oder Schild im Museum, sondern wird durch die Verarbeitung als Raumkoordinaten durch den auf Klassifizierungen trainierten Algorithmus paradoxerweise unsichtbar gemacht. Die Bilderwolke überlagert die Argumentationsweisen, die Ästhetik das Argument.

**Jeff Allen** @jamaps@mapstodon.space · 1 T. *

1 T. *

Jeff Allen @jamaps@mapstodon.space

postcard version of our Toronto bike share trip density map

#maps #dataviz #toronto #BikeTooter #biketo

network heat-map showing patterns of where people tend to ride bike share in Toronto

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

1 T.

Nicola Rennie @nrennie@fosstodon.org

It's Day 8 of the #30DayChartChallenge, and the prompt is "Histogram"

Another #RStats + Observable combination
Kept it simple, but figured out more about small multiples (facets), sorting categories, and colour palettes in Observable today!

#Day8 #DataViz #Observable

5 Histograms showing distribution of wealth inequality in 2023 per continent

**Sreedev Krishnakumar** @sreedevkkumar@journa.host · 1 T.

1 T.

Sreedev Krishnakumar @sreedevkkumar@journa.host

NSE-listed companies lost ₹14.3 lakh crore in market capitalisation on Monday. Today’s Number Theory looks at how Trump’s tariff threats — and global retaliation — triggered the selloff, and what past data tells us about such high volatility in the markets.

Read today's Number theory on HT app: https://www.hindustantimes.com/editors-pick/number-theory-how-global-mayhem-affected-indian-markets-101744077492303.html

@mastodonindians #MastIndia #Markets #Sensex #NSE #DataViz #TrumpTariffs #Tariffs

How global mayhem affected Indian markets

Byline: Sreedev Krishna Kumar

Asian and European stock markets tumbled on Monday amid mounting investor fears of a global recession, driven by intensifying trade tensions sparked by Donald Trump’s tariffs. With major economies showing no signs of backing down, further market volatility is expected. The following charts examine how the crash unfolded and what history tells us about periods of extreme market turbulence.

(Please click on the link in the next to read the full text on HT app as it is too long to be copied and pasted here)

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

2 T.

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

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds

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.

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

**Derek Law** @GIS_Bandit@mastodon.world · 2 T.

**The Xylom** @thexylom@journa.host · 2 T.

2 T.

The Xylom @thexylom@journa.host

Check out the most recent estimates of Georgia's climate attitudes by the Yale Program on Climate Change Communication and the George Mason University Center for Climate Change Communication, visualized by @alexip718.

In a collaboration between The Xylom, Atlanta Community Press Collective, and 285 South, Alex Music looks into how doctors can be an effective source of reliable climate information for conservatives and immigrants:

https://www.thexylom.com/post/the-fifth-vital-sign-atlanta-doctors-are-talking-climate-change-with-patients
#georgia #climate #dataviz #news

Yale 2024 Climate Opinion Map by metro area with Headline:

Despite Fulton and Dekalb Counties, Atlanta Metro and Georgia Lags Behind Nation in Recognizing Climate Change

Story by Alex Music
Visuals by Alex Ip

Map of Georgia's counties, shaded by difference from national average (%), most scientists think global warming is happening.

Map of Georgia's counties, shaded by difference from national average (%), has personally experienced the effects of global warming.

Map of Georgia's counties, shaded by difference from national average (%), global warming is mostly caused by human activities.

**Möph** @M@nerdculture.de · 2 T.

2 T.

Möph @M@nerdculture.de

Dataviz aus der Hölle

Können wir bitte endlich 3D Balkendiagramme endgültig abschaffen?
Ich meine wir haben 2025 und die Dinger waren NOCH NIE geeignet um irgendetwas zu visualisieren.
Habe eben eine Präse mit 20 dieser Diagramme gesehen. Das hier ist noch eins der Besseren.
Bei manchen wurden die hinteren Balken durch die vorderen komplett verdeckt.

#Dataviz #Datavisualization #Datavis #Datavisualisation

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

2 T.

Nicola Rennie @nrennie@fosstodon.org

It's Day 7 of the #30DayChartChallenge, and the prompt is "Outliers"

Data wrangling in #RStats
Scatter plot made with Observable
Static tooltips for annotations (+ dynamic tooltips for exploring)

#Day7 #DataViz #Observable

Scatter plot of time against % of income share, with Malawi highlighted in 1997 as being over 60%.

**naturepoker** @naturepoker@genomic.social · 3 T.

3 T.

naturepoker @naturepoker@genomic.social

Does anyone know of a good tanglegram/cophylogram generator in Python? The only option I see is pretty minimal - not really up to par against the R version in features or visual quality.

#phylogenetics #dataviz #bioinformatics

**Nicola Rennie** @nrennie@fosstodon.org · 3 T.

3 T.

Nicola Rennie @nrennie@fosstodon.org

It's Day 6 of the #30DayChartChallenge, and the prompt is "Florence Nightingale (theme day)"

Chart styled based on her iconic Rose Diagram using #RStats
Curved text with {geomtextpath}
Custom facet layout with {ggh4x}

#Day6 #DataViz

Version of Nightingale's Rose diagram showing wealth inequality between 1820 and 2020

**Helena Klara Jambor** @helenajambor@mastodon.social · 4 T.

4 T.

Helena Klara Jambor @helenajambor@mastodon.social

The story of #ComicSansMS!
First, cute, then #typography from hell ("worst font in the world", e.g. https://webdesignerdepot.com/10-most-hated-fonts-of-all-time/)... now: renaissance!, almost cute again!

#Wonderful #history #WeekendRead #DataViz

https://microsoft.design/articles/comic-sans-and-the-art-of-imperfection/

The 10 Most Hated Fonts of All TimeWeb Designer Depot

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

4 T.

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.

**Nicola Rennie** @nrennie@fosstodon.org · 4 T.

4 T.

Nicola Rennie @nrennie@fosstodon.org

It's Day 5 of the #30DayChartChallenge, and the prompt is "Ranking"

Bump chart made with Plotnine in #Python
I'm not totally happy with this one (too many colours and categories), but I figured out some text wrapping and label issues in Plotnine in the process

#Day5 #DataViz

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