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Rajo

@rajodm.bsky.social

MSc student in Epidemiology & Clinical Research #rstats | #dataviz

144 Posts185 Follower 270 Folgt

Frank Elavsky (he/him) ⌁@frank.computer · 2w ago

Big announcement: The final project of my thesis work, Skeleton: Visual Authoring of Non-visual Data Experiences, has now been accepted for publication at IEEE VIS! 🎉 🎉 🎉

Announcing: Skeleton 🩻, the culminating project of my PhD!

My final research project looked at the barriers that sighted practitioners face when authoring non-visual data experiences. We co-designed, built tooling, built a UI prototype, and ran a study.

frank.computer

David Schoch @schochastics.net · 4w ago

A side project I've been working on is public now: vellumverse, an #Rstats graphics stack built on a Rust backend. vellum sits where grid does but renders in Rust. vellumplot is the grammar on top and vellumwidget turns any plot into an interactive widget. Feedback welcome ☺️ github.com/r-vellum

Michael Caley @michaelcaley.bsky.social · 4w ago

I did it I wrote the article wish me luck Lionel Messi is the GOAT, Ronaldo is not, why just about every statistical analyst agress www.expectinggoals.com/p/messi-rona...

Why Messi keeps thriving as Ronaldo fades: The GOAT's always been the best

I'm not proud, or tired

expectinggoals.com

Rob Calver @robcalver.bsky.social · last mo.

I am giving away a free copy of the #BayesianWorkflow book by @statmodeling.bsky.social, @avehtari.bsky.social, @rmcelreath.bsky.social et al!! Please like, repost, and follow to enter. I will randomly draw the winner next Weds July 8. 😀 routledge.com/9780367490140 #RStats #DataScience #Bayesian

Rajo @rajodm.bsky.social · last mo.

A simple map for #TidyTuesday 2026 week 26 on Ireland shipwrecks. Code: github.com/rajodm/TidyT... #dataviz #rstats #ggplot2

Map of Ireland and surrounding waters on a dark blue bathymetric background, with 3,564 yellow-green points marking shipwreck locations from 1550 to 2017 clustered along the coastline and scattered across the continental shelf.

Timothée Giraud @rcarto.fosstodon.org.ap.brid.gy · last mo.

This new cheat sheet guides users on how to use OpenStreetMap data and related tools with R for: geocoding, routing, downloading base maps and datasets. You can download the PDF here: https://zenodo.org/records/20842874/files/cheatsheet_osm_r.pdf Many thanks […] [Original post on fosstodon.org]

Cheat sheet on how to use OpenStreetMap data and tools from R. Main packages are described.

Cheat sheet on how to use OpenStreetMap data and tools from R. A script is given as an example of how to use various packages.

Mickaël CANOUIL, Ph.D.@mickael.canouil.fr · 2mo ago

When tips and tricks from Cara Thompson, for better visualisation leads to making improvements to Gribouille in #Typst. Check out the talk materials, given yesterday at #RencontresR 2026. www.cararthompson.com/talks/rencon...

Line chart. Season (1 to 10) on the x-axis, number of creations on the y-axis (0 to 30). Three series marked by icons: chocolate, raspberry, and orange. Chocolate swings sharply between 19 and 30 creations across seasons 1 to 7 (the "Mary Berry years"), then drops to 12 to 15. Raspberry and orange stay low, between 4 and 13, tracking each other closely. Chocolate leads in every season except season 8, where orange briefly overtakes it.

Moritz Stefaner / Truth & Beauty @moritzstefaner.bsky.social · 2mo ago

✨ New project! ✨ Mapping the hidden infrastructure which connects to >70% of plants, extends root networks up to 100x and reaches a length of 1 BILLION times the distance to the sun 🤯 Arbuscular mycorrhizal fungi! Learn all about them here: a-hidden-infrastructure.spun.earth w/ @spun.earth 💚

A hidden infrastructure

Mapping Earth’s underground mycorrhizal fungal networks — the hidden infrastructure beneath our feet.

a-hidden-infrastructure.spun.earth

Emil Hvitfeldt @emilhvitfeldt.bsky.social · 2mo ago

Back with (yet another) quarto extension! Adding ways to create diagrams of different kinds and shapes using a unified syntax and styling Now providing the following types of diagrams pie, process, pyramid, matrix, hierarchy, venn, and more. emilhvitfeldt.com/post/quarto-... #quarto #slidecrafting

Announcing quarto-diagrams

quarto-diagrams is a new Quarto extension that adds a collection of circular and structured diagram styles.

emilhvitfeldt.com

Sebastian Hanika @sebhanika.bsky.social · 2mo ago

Josephine Rekers and I made a map! Our contribution to the new Geographica section in @tesg-journal.bsky.social Using both the pace and level of ageing, we highlight the "messy middle" of the urban–rural spectrum and the diverse regional ageing trajectories. doi.org/10.1111/tesg...

Map of Sweden titled "Subnational Population Ageing in Sweden, 1988–2023". The figure presents the results of a sequence analysis combining both the level and pace of population ageing in Swedish municipalities.

Ageing trajectories are grouped into four clusters: Stable Young (blue), Delayed Ageing (light orange), Accelerated Ageing (dark orange), and Old & Ageing (dark purple). Sequence plots explain the classification. In these plots, colour hue indicates the level of ageing (blue = younger, orange = intermediate, purple = older populations), while shading indicates the pace of ageing (light = de-ageing, medium = slow ageing, dark = fast ageing).

The map shows clear spatial variation in ageing trajectories. Municipalities around Stockholm are predominantly classified as Stable Young, while many municipalities in northern Sweden fall into the Accelerated Ageing or Old & Ageing clusters. Southern Sweden contains a mix of Delayed and Accelerated Ageing trajectories.

A bar chart compares the four ageing clusters with conventional urban–rural categories. While large cities are predominantly Stable Young and rural municipalities are more often Old & Ageing, medium-sized and small cities are distributed across all four clusters. This highlights substantial variation within the urban–rural spectrum and suggests that regional ageing patterns cannot be fully understood through a simple urban–rural divide.

Rajo @rajodm.bsky.social · 2mo ago

A look at maternity leave across 21 European countries in 2024 for #TidyTuesday week 22 Data: European Parenting Leave Policies Code: github.com/rajodm/TidyT... #dataviz #rstats #ggplot2

Horizontal bar chart titled "European Maternity Leave in 2024: Who Gives the Most Time?" showing mandatory (solid dark green) and voluntary (striped) maternity leave duration in weeks, before and after birth for 21 European countries. Italy (22 weeks, 9 before birth and 13 after birth) and Poland (20 weeks postpartum) lead in mandatory leave. Ireland offers the longest total postpartum leave at up to 40 weeks when voluntary leave is included. Lithuania and Estonia have no mandatory leave.

Rajo @rajodm.bsky.social · 2mo ago

Here's my contribution for the #dataviz trend on palindromic place names: A map showing the palindromic places in Madagascar according to GeoNames.org. The code used for the map is based on @ansgarw.bsky.social #rstats code: github.com/bydata/rando... #ggplot2

A map of Madagascar showing 9 palindromic places names (spelled the same way backward as forward) according to GeoNames.org data. Five out of nine share the same name: "Anena"

Mickaël CANOUIL, Ph.D.@mickael.canouil.fr · 2mo ago

Showcasing Gribouille (Grammar of Graphics for #Typst) with #TidyTuesday

Two stacked-area panels of renewable energy by source, 1990 to 2010. Vietnam's traditional biomass band shrinks and its renewable share falls from 76% to 35%, while Germany's modern bioenergy and wind and solar grow and its share rises from 2% to 11%.

Information is Beautiful @infobeautiful.bsky.social · 3mo ago

Africa's electricity access, country by country. Some leaps. Some crawls. One notable slide backwards. But a massive shift over just 10 years. source: World Bank by reddit user cavedave

Small multiples boxed cartogram titled 'African Access to Electricity, 2012 vs 2022' showing slope charts for each African country. Each chart displays the percentage of population with electricity access in 2012 and 2022, with blue shading for gains and red for losses. North African countries lead with near-universal access (Morocco 96→100, Algeria 100→100, Tunisia 100→100, Egypt 100→100). Notable gains include Kenya (38→76), Ethiopia (55→8→55→65 area), and Rwanda (15→51). Libya is a rare loss, dropping from 100 to 79. Many sub-Saharan countries remain low but improving, such as Chad (8→12), South Sudan (3→8), and DR Congo (29→47). Mauritius (99→100) and Seychelles (100→100) have full or near-full access. Source: World Bank, World Development Indicators.

Georgios Karamanis @karaman.is · 3mo ago

This week's #TidyTuesday is about twin cities. I built a scrollytelling map about Rio de Janeiro's 93 sister city agreements Made with Quarto and Closeread Interactive: 019e2679-54db-2e9a-2e03-8bbc8b92210f.share.connect.posit.cloud Code: github.com/gkaramanis/t... #RStats #dataviz

Mickaël CANOUIL, Ph.D.@mickael.canouil.fr · 3mo ago

One Quarto source. A deck and a report. Quarto Cascade repeats the heading chain on every `---` (including `---` nested inside a Div). github.com/mcanouil/quarto-revealjs-cascade #Quarto #QuartoPub #Slidecrafting #RevealJS

Teun van den Brand @teunbrand.bsky.social · 3mo ago

I'm please to celebrate that legendry 0.3.0 has hit the streets on CRAN 🎉 Legendry is a ggplot2 extension that lets you draw more guides. Read about all the guide goodness in this minor update here: teunbrand.github.io/teunbrand_bl... #rstats #ggplot2

Symbolic update – Blog | Teun van den Brand

The latest and greatest in guide fashion.

teunbrand.github.io

David Hodge @davidhodge931.bsky.social · 3mo ago

Part 1 of 5: Introducing a complete rethink and rewrite of #ggblanket. The original goal of simplifying no longer made so much sense what with llms. So I refocused it on the design aspect: provide a way to produce consistent publication quality plots with minimal effort. #rstats

Rajo @rajodm.bsky.social · 3mo ago

Explored Italian industrial textile production for #TidyTuesday week 18 Code: github.com/rajodm/TidyT... #dataviz #rstats #ggplot2

Two marimekko charts showing Italian industrial textile production by fiber type from 1934-1985, separated into yarn (top) and textiles (bottom). Cotton in yellow consistently represents the largest share with flock in brown and other fibers in purple making up smaller portions.

Rajo @rajodm.bsky.social · 3mo ago

Inline outputs for #Quarto documents in #Positron are finally here!

Screenshot of Posit's Positron IDE showing a Quarto markdown file with code chunk output displayed inline beneath the code

Rajo @rajodm.bsky.social · 3mo ago

Since the RSF World Press Freedom Index 2026 is out, here's an update of my Day 6 entry, for #30DayChartChallenge #Day17 - Remake Code: github.com/rajodm/30Day... #dataviz #rstats #ggplot2

Small multiples slope chart of Reporters Without Borders Press Freedom Index scores for African countries, comparing 2025 to 2026. A table at the bottom right of the chart shows that only 24 (45.3%) of 53 countries showed improvement compared to 2025, the score remained the same as in 2025 for 7 (13.2%) countries, and the score decreased for 22 (41.5%) countries.

Rajo @rajodm.bsky.social · 3mo ago

#30DayChartChallenge #Day24 Timeseries - South China Morning Post P. vivax parasite rate surveys across Asia reported in the Malaria Atlas Project Code: github.com/rajodm/30Day... #dataviz #rstats #ggplot2

Bubble chart showing Plasmodium vivax malaria parasite rate (PR) from surveys reported in the Malaria Atlas Project across 21 Asian countries from 1985 to 2018. Each bubble represents a survey with size indicating the number of people examined and colour indicating the weighted mean parasite rate on a yellow-to-dark-purple scale (0 to 0.26). India and Indonesia have the most surveys (28 and 27 respectively) with consistent coverage across all years. Notable annotations highlight the largest survey in Afghanistan in 2005 (40,200 persons), the highest parasite rate in China (0.26 in 2002), a PR of 0.25 in the Philippines in 1991, and a 1995 India survey of nearly 17,000 people with a PR of 0.12.

Manasseh @manasseh6.bsky.social · 4mo ago

Global Health Spending for #TidyTuesday, week 16. #Rstats #Dataviz #ggplot2

Rajo @rajodm.bsky.social · 4mo ago

#30DayChartChallenge #Day18 UNICEF data Malnutrition takes different forms across income levels. Among children under 5, stunting remains alarmingly high while overweight keeps slowly rising. Code: github.com/rajodm/30Day... #dataviz #rstats #ggplot2

Line chart showing trends in overweight and stunting prevalence among children under 5 from 2000 to 2024, split horizontally into four panels by country income group (from left to right: high, upper middle, lower middle, and low income) and vertically into overweight on top and stunting below. Overweight prevalence (top row, grey) remain low across all income groups with a slight upward trend. Stunting prevalence (bottom row, red) are much higher in lower middle and low income countries but have declined substantially over the period. Each panel shows individual country lines in the background and a bold line representing the group average.

Rajo @rajodm.bsky.social · 4mo ago

2 days late and maybe not literally about trade, but here's my entry for #Day14 of the #30DayChartChallenge Relationships - Trade: The trade-off between access and use of insecticide-treated nets across African countries Code: github.com/rajodm/30Day... #dataviz #rstats #ggplot2

Dumbbell plot comparing insecticide-treated net (ITN) access and use across 40 African countries in 2024, ordered by use rate. Each country has two dots connected by a line (blue for use and red for brown). Countries at the top such as Burkina Faso, Gambia, Niger and Malawi have the highest use rates (above 96.5%), while Ethiopia, Nigeria, and Eritrea have the lowest (lower than 73%). Notable annotations highlight Niger's high ITN adoption, Togo's 85% access rate as the highest in Africa, Gabon's very low coverage of around 10%, and a cluster of low-coverage countries including Ethiopia, Nigeria, Eritrea, Angola, Djibouti, Somalia, Mauritania, and Madagascar highlighted in orange.

Rajo @rajodm.bsky.social · 4mo ago

A beeswarm plot of Plasmodium falciparum malaria incidence by country, among countries with detected cases (2024) for #30DayChartChallenge #Day12 theme day - FlowingData Code: github.com/rajodm/30Day... #dataviz #rstats #ggplot2

Beeswarm plot showing Plasmodium falciparum incidence rates per 1,000 people across countries in 2024 on a dark background. Each dot represents a country colored on a gradient from blue (low incidence) to red (high incidence). A large cluster of blue dots sits near zero, representing the majority of countries with negligible Plasmodium falciparum transmission. The median line is at 52.38 cases per 1,000. Benin is highlighted as the highest-burden outlier at 364.52 cases per 1,000.

Louis M Penrod @louismpenrod.bsky.social · 4mo ago

#30DayChartChallenge #Day13 – Ecosystems. Well, a digital ecosystem. Radial plots of the relative abundance of monsters in the Stardew Valley mines per zone. Each zone has its unique "ecosystem" composed of different organisms that appear at different rates. #DataViz #Rstats

Four radial bar charts arranged vertically, each representing one zone of the Stardew Valley mines: Brown, Gray, Frozen, and Lava. Each chart shows the relative frequency of monster types found in that zone, with bars radiating outward from the center. A pixel art image of each monster type sits at the tip of its corresponding bar. An example level from the game shown next to each plot. The charts reveal how the monster community composition shifts as you descend deeper into the mines.

Rajo @rajodm.bsky.social · 4mo ago

#30DayChartChallenge #Day11 Distributions - Physical How long is the walk to the nearest healthcare facility in Madagascar? Code: github.com/rajodm/30Day... #dataviz #rstats #ggplot2 #tmap

Combined 1x1 km raster map (left) and bar chart (right), titled "The long walk to care" showing the distribution of walking travel time to the nearest healthcare facility in Madagascar (2020). The map uses a yellow to dark teal colour scale to show travel times across the country. The bar chart shows that the largest share of the population lives between 60 and 180 minutes (walking time) from a facility, followed by those between 180 and 600 minutes.

Rajo @rajodm.bsky.social · 4mo ago

Just a remake of the day 9 map on ITN access and use in Nigeria with a Lego style for #30DayChartChallenge #Day10 Code: github.com/rajodm/30Day... Source of inspiration: r-graph-gallery.com/web-chorople... (by @bjnnowak.bsky.social) #dataviz #rstats #ggplot2

Bivariate choropleth map of Nigeria showing insecticide-treated net (ITN) access and use in 2024 with a lego style. Northern states show the highest access and use (orange), while southern coastal states show the lowest (purple and blue). A 4×4 colour legend encodes the two dimensions: ITN access on the x-axis (16.7%-82.0%) and ITN use on the y-axis (9.2%-65.9%).

Cédric Scherer @cedricscherer.com · 4mo ago

New lesson live 🚀 Before starting to talk about #maps with #ggplot2, we cover "Spatial Data". 🧱 What are the building blocks? 🌉 What is the SF revolution? 🍊 How to peel an orange? (Wait, what?!) Curious to learn more? This lesson is freely available 👐 www.ggplot2-uncharted.com/module5/spat...