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#dataviz

28 posts25 participants1 post today

**Growth In Real Household Income Slows In The First Quarter Of 2025**

"_On the other hand, the United Kingdom and Germany recorded declines in real household income per capita (-1.3% and -0.4%, respectively), as consumer price inflation eroded nominal income growth (Figure 2), while real GDP per capita expanded (0.5% and 0.3%, respectively)._"

🔗 oecd.org/en/data/insights/stat.

#Data #DataViz #Statistics #Income #Inflation #Economy #Economics #OECD @economics

There's just a few weeks to go until RSS Conference! I'm excited to speaking in the accessibility in official statistics session, organised by Clare Griffiths for the RSS Official Statistics Section 📊

📅 Thursday, 4th September 2025, 13:40 - 15:00
📍 RSS Conference, Edinburgh
🎤 Also speaking are @cararthompson, Olivia Box Power, and Elliot Bridges

It'll be an interactive session, so bring your accessibility questions and problems!

Recent @DSLC club meetings:

:rstats: Fundamentals of Data Visualization: & Chapter 7 Visualizing distributions: Histograms and density plots youtu.be/4Hm6nK-oOMY #RStats #PyData #DataViz

From the @DSLC :rstats:​chives:

:rstats: ISLR: Linear Regression youtu.be/gxbBSpvw2zQ #RStats

:rstats: R para Ciencia de Datos Club de Lectura: Capítulos 22 y 23: Modelos-Parte 1 youtu.be/EnHoVzJJ02c #RStats

Visit dslc.video for hours of new #DataScience videos every week!

I'm really looking forward to WOMBAT 2025 (Workshop Organised by the Monash Business Analytics Team) in Melbourne next month!

I'm excited to be giving the keynote where I'll be talking about designing data visualisations for decision making 📊

This week's #TidyTuesday looks at data from Our World in Data on the Gini coefficient (a measure of income inequality) before and after tax 📊

I quite like this style of small multiple chart when there are lots of categories - a zoomed in version with more explanation, then more minimalist versions for the smaller versions. It helps avoiding too much clutter, whilst still giving the extra information users need!

Code: github.com/nrennie/tidytuesday

Continued thread

Raj's dashboard, updated yesterday, shows Stratus XFG overtaken by child XFG.2; PQ.2 as standout child of Nimbus NB.1.8.1 / PQ; and LP.8.1 long ago overshadowed by LP.8.1.1/ NY.

GISAID data for the most recent fortnight is dominated by submissions from New York (with all of 92 sequences—one more than ten days ago), followed by California (26—ten more), Florida (17) and Colorado (16).

#CDC's most recent Friday dataset, updated Tuesday June 24, showed Nimbus taking plurality, with Stratus XFG family also gaining share.

FDA vaccine target LP.8.1, dominant since March, plateaued in April. June saw Nimbus NB.1.8.1 / PQ, scion of "razor-blade throat" XDV, push LP.8.1 out of majority.

#ThisIsOurPolio #variants #CovidIsNotOver #dataviz #datavis

🧩 [r_tip] - ¿Querés que tus visualizaciones cobren vida?

Con el paquete {gganimate} podés crear animaciones sobre gráficos ggplot2 y mostrar transiciones, evolución temporal o cambios por categoría.

✔️ Extiende ggplot2 con funciones intuitivas (transition_*, enter_*, exit_*)
✔️ Ideal para storytelling con datos en presentaciones o redes
✔️ Compatible con gifski, transformr y temas personalizados

🔗 gganimate.com/
✍️ @thomasp85

As a data scientist with a background in hard science, Kirk Borne often reminds me of the importance of robust data. His advice today is a great pro-tip for fellow materials researchers:

"Don't just plot your data; visualise the uncertainty! Using tools like #Seaborn can add confidence intervals to your graphs, making your findings more robust. This simple step adds credibility and clarity to your results."