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
2025 #30DayChartChallenge | day 02 | comparison | slope
.: https://stevenponce.netlify.app/data_visualizations/30DayChartChallenge/2025/30dcc_2025_02.html
.
#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
The ever popular Stamen Toner and its Lite variation are perfect for showcasing your data.
In this example, we've overlaid OpenStreetMap's parks in San Francisco.
See all the styles we have waiting for you: https://stadiamaps.com/products/maps/map-styles/?utm_campaign=styles_stamen_toner_lite&utm_content=san_francisco_parks#stadia-stamen&utm_source=mastodon&utm_medium=social
#30DayChartChallenge let's go! This #dataviz was for a bit of #Python practice, and I could *not* have sorted out the non-linear gradient for 1 > n > 0 without #claudeai. Made with #seaborn and patience #FractionArt #ColorfulMath #PythonDataViz #FractionFunhouse
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/
la production annuelle par pays en TWh mise à l'échelle dans une carte.
Affiche dans l'espace d'accueil de la centrale électronucléaire de #Nogent Sur Seine.
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
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
After months of decline, Indian markets finally rebounded in March, bringing the BSE Sensex close to its end-2024 levels. So does this mean India's stock market winter is finally over? Today's Number Theory breaks it down.
Read on HT app: https://www.hindustantimes.com/editors-pick/number-theory-is-indias-stock-market-winter-finally-over-101743477369415.html
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
OpenHistoricalMap and open source software let you tell stories in the proper historical context:
https://mastodon.social/@CharliePlett/114247969119307235
Learn how to incorporate OHM into your own project:
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.
#Measles dashboard update:
https://public.tableau.com/app/profile/ari.skinner/viz/MeaslesUSA2025/NavandOverview
Large spike in cases this week - in Texas, where the outbreak is spreading to more communities and growing in number; but also in nearby states like Kansas and Oklahoma. Some states' numbers don't show up in the CDC data: these figures were pulled from each state's page.