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
It's time for a #Measles dashboard update:
https://public.tableau.com/app/profile/ari.skinner/viz/MeaslesUSA2025/NavandOverview
The landing page now has a histogram AND a national map, capturing statewide totals. This is especially valuable since some states aren't including county data, or are including divisions like regions, which can't be captured on the cases-by-county map.
This project was constructed from local and state data first: I don't pull from CDC's national totals, but I do check my data against them frequently. Wherever local and state data aren't available, I use news articles. Every entry includes a source link in the cases-by-county table.
2025 #30DayChartChallenge | day 02 | comparison | slope
.: https://stevenponce.netlify.app/data_visualizations/30DayChartChallenge/2025/30dcc_2025_02.html
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#rstats | #r4ds | #dataviz | #ggplot2
It's Day 2 of the #30DayChartChallenge, and the prompt is "Slope"
Re-using yesterday's data from Our World in Data on wealth distribution
Slope chart looking at change over 200 years
Chart made with Observable
#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
Quarto + #RStats + Observable =
New blog post from me about:
What is Observable?
Why should R users care?
How do you use both together to make interactive charts?
The New York Times' classic #dataviz made in *Flash* are back online - thanks to some kind of tech magic. Via @flowingdata
https://flowingdata.com/2024/01/10/nyt-flash-based-visualizations-work-again/
It's Day 1 of the #30DayChartChallenge, and the prompt is "Fractions"
Data from Our World in Data on wealth distribution
Data wrangling in #RStats
Waffle plot made with Observable
For #Day1 of #30DayChartChallenge, I tackled comparing proportions over time. Here’s what I came up with:
Code: github.com/gnoblet/30Da...
#rstats #dataviz #ggplot2 cc @30daychartchall.bsky.social
RE: https://bsky.app/profile/did:plc:7ebnmsusl3r2uuaf24igiazh/post/3llqfkva5r22g
Today starts the #30DayChartChallenge, happy times for #dataviz lovers!
I recently joined the Health Foundation. So this year (as time allows) I’ll post a mix of visualisations about health topics made in Flourish (our main charting library) + fun stuff I learnt to make in #python and #D3.
Grâce à l'API de #Mastodon et un scraping #python une visualisation des mot-dièses associés à #AAFRennes2025 corpus de 169 pouets depuis 2023. (bon maintenant il y en a un de plus). @archivistodon #Archives #Dataviz
Here's my first contribution to the #30DayChartChallenge 2025. Horrifying statistics about misinformation! But also hot tips to cope!
Four in five of us (adults in Australia) reckon: "The spread of misinformation on social media needs to be addressed."
And that "People need to be taught how to identify misinformation."
So we're starting there! This is the SIFT method:
S: Stop. Don't read a post until you know where the info is coming from. And stop if you're overwhelmed.
I: Investigate the source. Maybe hover over their social media profile. See what Wikipedia says.
F: Find better coverage. Before sharing, check if other websites (reputable ones) say the same thing.
T: Trace claims, quotes, and media to the original context. Check the date. Try reverse image search to see where pics came from. Read full quotes, not just ragebait headlines.
Promising 4-year, fully-funded PhD position in Architecture and Data Visualization at TU Delft – explore sensor data, design impacts, and ecology.
Apply by 15 Apr 2025!
I would like to have either a mirror or an automatic download (every few hours) of a public #Tableau workbook.
All download options are enabled
Does anyone have an idea?
#Data #DataViz #SafeguardingResearch
It's almost April, and that means it's nearly time for the #30DayChartChallenge!
I'm not yet sure how many days I'll end up doing, but my aims are:
Spend time learning more Observable and D3
Reuse datasets and visualise them different ways
Use more text and annotations in charts
It's a rainy Sunday, and so I spent a lot of time futzing around with a high-quality version of the #MadisonWI DSM 3D render. 5000x5000px, 128 samples in #Rayshader. This was about as large as I could get it without crashing #RStats. #DataViz
Folks who #website: I'm trying to create a slice'n'dice-able #data #table -- somewhat like https://instances.vantage.sh/ with the per-column client-side search/constraint/etc. FWIW my data's a discrete JSON file.
I'm allergic to JavaScript insofar as I have zero idea what I'm doing with it (and *can't* do anything with it, myself) but will happily copy'n'paste it as needed.
Got any pointers? #websites #HTML #datadriven #javascript #js #webdev #WebDesign #WebDevelopment #dataviz
Mardi, les nouveaux députés sont entrés au Bundestag allemand. J'ai profité de cette occasion pour appliquer le principe de ma dataviz à d'autres pays en commençant par l'Allemagne. Le site est également désormais multilingue !
http://legislatures.vercel.app/fr/germany
La question que je me pose est devrais-je remonter au delà de 1949 ? 1919 ? 1871 ?
En tout cas j'ai prévu de faire la RDA prochainement, sur une page à part.
I discovered very high resolution DSM data for Madison: https://geodata.wisc.edu/catalog/67d0518f-d029-4d8f-a8ac-41d9138fb30d Throw it into #rayshader and you can produce pretty things! Add some aerial photo data from the county (https://gis-countyofdane.opendata.arcgis.com/pages/imagery-download) and you can make even more pretty things. The resolution is amazing.