Georgios Karamanis
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karaman.is
Georgios Karamanis
@karaman.is
2.6K followers 180 following 280 posts
Dataviz designer, psychiatrist, PhD student

https://karaman.is
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karaman.is
For this week's #TidyTuesday a faceted scatterplot showing TB case notification rate vs mortality rate by WHO region in 2023.

Code: github.com/gkaramanis/t...

#RStats #dataviz
A faceted scatter plot showing tuberculosis (TB) case notification rate (new, relapse, and unknown previous treatment cases per 100,000 population per year) and TB mortality rate (deaths per 100,000 population per year) by WHO region for 2023. Each facet represents a WHO region, with countries displayed as points sized according to population. Labeled countries are those with the highest case notification rates, mortality rates, or population sizes. The Western Pacific and African regions have the highest case notification rates, accounting for nearly 70% of global reported TB cases. Mortality rates are notably high in several African countries, indicating ongoing challenges with TB diagnosis and treatment access worldwide. Overall, case notification rates show a slight increase from 2022, while global TB deaths have decreased by about 5%.
November 16, 2025 at 12:55 PM
karaman.is
I visualized the Flint water crisis data for this week's #TidyTuesday showing how sample exclusions masked lead contamination.

Code: github.com/gkaramanis/t...

#RStats #dataviz
Three horizontal beeswarm plots showing lead concentrations in water samples from Flint, Michigan, measured in parts per billion (ppb). Each plot displays individual water samples as dots along the x-axis. A shaded grey area extends from 0 to 15 ppb, marking the federal action level threshold. A dashed dark red line marks the 90th percentile for each dataset. Grey dots indicate samples below the 90th percentile, while bright red dots indicate samples at or above the 90th percentile. The top panel, labeled "Official data (with exclusions)," shows 69 samples after Michigan officials removed two "outlier" samples. The 90th percentile line sits at 11.4 ppb, below the 15 ppb federal action level. Most samples cluster between 0 and 20 ppb, with a few extending beyond 40 ppb. The middle panel, labeled "Official data (complete)," displays all 71 samples including the two removed samples. The 90th percentile line rises to 18 ppb, now exceeding the federal action level. The distribution is similar but shows higher values in the upper range, with samples extending past 100 ppb. The bottom panel, labeled "Citizen science data," presents 271 samples collected by Virginia Tech researchers and Flint residents. The 90th percentile line reaches 26.6 ppb, substantially above the federal action level. This dataset shows a wider spread with more high-value samples, including several exceeding 100 ppb, revealing significantly worse contamination than official reports suggested.
November 10, 2025 at 6:46 PM
karaman.is
Day 5 of #30DayMapChallenge, Earth

Nature Index 2025 for countries/territories

Code: github.com/gkaramanis/3...

#dataviz #spatial #Rstats #map #science #research
Map of the world showing countries shaded by their share of articles published in scientific journals, according to the Nature Index for the period August 1, 2024, to July 31, 2025. Countries with higher shares are shown in darker colors. The five countries with the highest shares are labeled with their names and values (China, 36 826.66; United States of America, 21 980.49; Germany, 4 916.4; United Kingdom, 3 985.63; Japan, 3 344.12). The map uses a Van der Grinten IV projection and includes a legend for share values (log scale). The background is light gray, and the map has a minimalist design.
November 8, 2025 at 2:52 PM
karaman.is
Day 4 of #30DayMapChallenge, My data

Maps showing the locations of affiliations for me and my coauthors across six of our research papers.

Code: github.com/gkaramanis/3...

#dataviz #spatial #Rstats #map #science #research
A grid of small maps, each representing the geographic locations of affiliations for the author and coauthors of six research papers. Each map highlights a specific region with bright orange star-shaped markers, indicating the locations of the affiliations. The maps are cropped to focus on the relevant areas. The background is light gray, and the maps feature white landmasses with gray borders. Captions below each map display the title and publication year of the corresponding paper.
November 5, 2025 at 6:12 AM
karaman.is
Day 3 of #30DayMapChallenge, Polygons
Uppsala University, founded in 1477, is the oldest university in the Nordic countries. Here are the 30 buildings marked as 'university' and labeled with a name on OpenStreetMap

Code: github.com/gkaramanis/3...

#dataviz #spatial #Rstats #science #research
Visualization of Uppsala University buildings in Sweden. Each building is represented as a polygon, highlighted in orange with black borders, overlaid on a grey map of surrounding structures. The title 'Uppsala University buildings' is centered at the top, and the caption reads 'Source: OpenStreetMap · Graphic: Georgios Karamanis'. The layout features 30 panels, each focusing on a specific building.
November 3, 2025 at 9:08 PM
karaman.is
Day 2 of #30DayMapChallenge, Lines

Uppsala University researchers have collaborated with hundeds of research institutions worldwide. More than 14,000 publications have been co-authored with Karolinska Institutet alone.

Code: github.com/gkaramanis/3...

#dataviz #spatial #Rstats #science #research
A world map in Robinson projection showing Uppsala University's research collaboration network. The map highlights countries containing the top 100 institutions that have co-authored publications with Uppsala University. Red points mark each collaborating institution, with point size proportional to the number of co-authored works. The top collaborating institutions per continent are labeled, including their collaboration counts. The most frequent collaborators include Karolinska Institutet in Europe with 14 598 publications, Lund University with 6 971, Stockholm University with 6 107, and Centre National de la Recherche Scientifique with 5 316. In North America, top partners include the United States Department of Energy with 2 335 publications, Harvard University with 1 976, and Stanford University with 1 517. In Asia, the Chinese Academy of Sciences leads with 1 847 publications, followed by Peking University with 847. The University of Melbourne represents Oceania with 822 publications. Countries with collaborations are shown in white against a light gray background.
November 2, 2025 at 7:05 PM
karaman.is
I created a heatmap for this week's #TidyTuesday showing UK literary prize demographics with data from @post45data.bsky.social. White British authors account for 61% of winners vs. 46% shortlisted. Men win 56% vs. 46% shortlisted.

Code: github.com/gkaramanis/t...

#RStats #dataviz
A heatmap showing gender and ethnic representation in UK literary prizes, split into two panels for shortlisted authors and winners. The visualization displays counts across ethnicity categories (African, Asian, Black British, Caribbean, Irish, Jewish, Non-UK White, Non-White American, and White British) on the y-axis and gender categories (Man, Non-binary, Transman, and Woman) on the x-axis. Each cell shows the count with white text on a colored background, where darker colors indicate higher counts. White British men show the highest counts in both panels (120 shortlisted, 149 winners), followed by White British women (123 shortlisted, 105 winners). Non-UK White authors also show substantial representation (39 men and 87 women shortlisted; 40 men and 32 women winners). Most other ethnic groups show single-digit counts, with several cells having zero representation. The data reveals that White British authors increase from 46% of shortlisted to 61% of winners, while women decrease from 54% of shortlisted to 43% of winners.
November 2, 2025 at 5:11 PM
karaman.is
Day 1 of #30DayMapChallenge, Points

There are almost 120,000 research organizations, in more than 17,000 locations, registered in the Research Organization Registry @researchorgs.bsky.social

#Rstats #dataviz #spatial #map #science #research
A world map in a Robinson projection showing the locations of research organizations registered in the Research Organization Registry (ROR). Countries are outlined in light gray, excluding Antarctica. Points on the map represent the number of organizations at each location, with larger and darker points indicating higher numbers. Labels for locations with 300 or more organizations are displayed, such as city names, in dark text with a white background. The map has a clean, minimalistic design with a white background and a gradient color palette for the points. The title reads 'Research organizations of the world,' and the subtitle explains that the size of the points corresponds to the number of organizations in each location.
November 1, 2025 at 12:41 PM
karaman.is
#Makingof of this week’s #TidyTuesday
October 26, 2025 at 6:56 PM
karaman.is
For this week's #TidyTuesday, rainfall from 12 UK weather stations 2012-2024. I’ve been wanting to try the idea of using letter heights to show data for some time, now possible thanks to {flexfont} by @coolbutuseless.fosstodon.org.ap.brid.gy

Code: github.com/gkaramanis/t...

#RStats #dataviz
A data visualization showing median annual rainfall at UK weather stations from 2012 to 2024. The chart displays twelve weather stations (Ballypatrick Forest, Bradford, Camborne, Cardiff Bute Park, Chivenor, Dunstaffnage, Eskdalemuir, Hurn, Lerwick, Newton Rigg, Stornoway Airport, and Tiree) arranged in two columns. For each station, the years 2012-2024 are shown along the x-axis, with rainfall amounts in millimeters on the y-axis (ranging from 0 to 200+ mm). Eskdalemuir recorded the highest rainfall (213.3 mm in 2020), while 2022 was notably dry across most stations. Each station's name is visualized by repeating its letters across the years, with letter height corresponding to that year's median rainfall. The most recent complete station name appears in dark blue, while earlier repetitions are shown in light blue. Blue bars at the bottom of each panel represent the year markers. A horizontal red line at the top of each panel indicates the maximum rainfall recorded for that station during the period.
October 26, 2025 at 2:30 PM
karaman.is
For this week's #TidyTuesday, I explored global differences in severe food insecurity between women and men. In 78 countries, women face higher rates, with the largest gaps seen in Pakistan and Afghanistan.

Code: github.com/gkaramanis/t...

#RStats #dataviz
Dot and rug plot with colored background bars showing the difference in prevalence of severe food insecurity between women and men across countries, ordered by difference. Each country is represented by a black point along the y-axis, with the x-axis showing the difference in percentage points. Vertical background bars are colored on a gradient from green to purple, indicating the value of the difference: purple for countries where women have higher rates, green for countries where men have higher rates. Rugs above the plot highlight positive and negative differences. Country names are labeled for the largest differences. For example, women have higher rates in countries such as Pakistan, Afghanistan, and Peru, while men have higher rates in countries including Jamaica, Libya, and Djibouti.
October 19, 2025 at 1:47 PM
karaman.is
For this week's #TidyTuesday, EuroLeague basketball club championships from 1958 to 2024, across four competition formats. Used Wikipedia data instead of the provided dataset 😅

Code: github.com/gkaramanis/t...

#RStats #dataviz
A horizontal tile plot showing the top 10 EuroLeague basketball clubs by championships from 1958 to 2025. Each club is displayed in a separate row, with colored tiles marking years won and gray tiles marking runner-up years. The x-axis shows years from 1960 to 2025, grouped by competition format: FIBA European Champions Cup, FIBA European League, FIBA EuroLeague, and EuroLeague (ECA). Real Madrid leads with 11 titles and 10 runner-up finishes. Darker tile shades indicate more cumulative titles. The plot background is light gray, with club names and title counts on the left.
October 12, 2025 at 2:33 PM
karaman.is
For this week's #TidyTuesday, crane migration at Lake Hornborga, Sweden, from 2002 to 2024

Code: github.com/gkaramanis/t...

#RStats #dataviz
A set of bar charts showing the number of cranes observed at Lake Hornborga in Sweden from 2002 to 2024. The left panel displays daily counts for March and April, revealing a clear seasonal peak in crane numbers in late March and early April each year, followed by a decline. The right panel shows weekly counts for August to October, with lower and more variable numbers, indicating that most cranes have already migrated by this period. The data include the date, number of observations, comments, and indicators for weather disruptions. A map highlights the location of Lake Hornborga and Sweden
October 5, 2025 at 2:52 PM
karaman.is
For this week's #TidyTuesday, the top 16 chess players for August and September

Code: github.com/gkaramanis/t...

#RStats #dataviz
A chess-themed plot compares the top 16 FIDE-rated chess players for August and September 2025. Each player is represented by a chess piece icon on a stylized board, with August pieces in black and September pieces in white. Diagonal lines connect each player's position from August to September, showing changes in rank. The top six names—Magnus Carlsen, Hikaru Nakamura, Fabiano Caruana, Praggnanandhaa R, Erigaisi Arjun, and Gukesh D—remained unchanged in both months. The top three players are Magnus Carlsen (2 839), Hikaru Nakamura (2 807), and Fabiano Caruana (2 784). Player labels include rank, name, and rating. The plot title is "FIDE chess player ratings".
September 28, 2025 at 9:17 AM
karaman.is
For this week's #TidyTuesday, pasta carbs and fat. Inspired by @cborstell.bsky.social's plot bsky.app/profile/cbor...

Code: github.com/gkaramanis/t...

#RStats #dataviz
This scatter plot shows how 54 pasta dishes from around the world compare in their carbohydrate and fat content per serving. Each point represents a pasta dish, colored by the country or cuisine it comes from, positioned on a grid where the x-axis shows normalized carbohydrate content (0 to 1) and the y-axis shows normalized fat content (0 to 1). The data is normalized against 2 200 recipes of different dish types in the dataset. The plot is divided into four quadrants by dashed lines at the 0.5 mark on both axes, with directional labels indicating "High carb" (right), "Low carb" (left), "High fat" (top), and "Low fat" (bottom). Most pasta dishes cluster in the lower-right quadrant, indicating they tend to be higher in carbs but lower in fat. Notable outliers are labeled with dish names and their countries of origin, including dishes like "Copycat Chicken Fritta" from Italy (highest carb content), "Creamy Chicken Pasta" from Cajun and Creole cuisine (highest fat content), and "Lemon Chicken Orzo Soup" from Greece (lowest fat content).
September 21, 2025 at 11:57 AM
karaman.is
For this week's #TidyTuesday, a visualization showing how more and more countries allow visa-free travel to most of the world's destinations

Code: github.com/gkaramanis/t...

#RStats #dataviz
A density plot showing the distribution of visa-free destinations accessible by country passports in 2006 versus 2025. The horizontal axis shows the number of visa-free destinations (0 to 200), while the vertical axis shows probability density. Two prominent curves are displayed: a burgundy curve for 2006 data peaks sharply around 25 destinations, indicating most countries' passports provided access to relatively few places without visas. A blue curve for 2025 data shows a much flatter, broader distribution with a peak around 180 destinations, demonstrating that significantly more passports now provide access to most of the world's destinations. Multiple faint gray curves in the background represent the years between 2006 and 2025, showing the gradual transition. Two text annotations explain that in 2006 most countries' passports provided access to only a few destinations, while in 2025 significantly more passports give access to most of the world's destinations.
September 12, 2025 at 12:51 PM
karaman.is
For this week's #TidyTuesday, hex grid maps showing seasonal shifts in frog observations across Australia

Code: github.com/gkaramanis/t...

#RStats #dataviz
Faceted map of Australia showing hexagonal grids colored by the number of frog observations from the FrogID project in 2023. Each facet represents a combination of frog tribe and season (Summer, Autumn, Winter, Spring). The color intensity of each hexagon indicates the count of observations, with labels marking the hexagon with the highest count per frog tribe and season. The map background is light gray, and the legend at the bottom explains the color scale for the number of observations.
September 7, 2025 at 4:13 PM
karaman.is
For this week’s #TidyTuesday I looked at summer Billboard Hot 100 number one songs. Since the 90s fewer song debut at #1 in summer but those that do tend to stay at the top for more weeks

Code: github.com/gkaramanis/t...

#RStats #dataviz
Bar chart and heatmap showing trends in Billboard Hot 100 number one songs during summer months (June, July, August) from 1960 to 2024. The top panel displays the number of summer number one songs per decade, with annotations for average weeks at number one. The bottom panel is a heatmap of individual songs by year and week, colored by total weeks at number one. Fewer songs reach number one in summer since the 1990s, but those that do spend more weeks at the top.
August 31, 2025 at 11:24 AM
karaman.is
Explore Scotland’s tallest Munros and Munro tops with this week’s #TidyTuesday

Code: github.com/gkaramanis/t...

#RStats #dataviz
The plot displays the 20 highest Munros and Munro tops in Scotland. The main chart is a vertical bar plot showing mountain names and their heights in meters and feet, with striped bars indicating Munro tops. The tallest peak, Ben Nevis, is highlighted in both meters and feet. An inset map of Scotland shows the geographic locations of all Munros, with Ben Nevis marked in red and labeled.
August 24, 2025 at 1:41 PM
karaman.is
Explore extreme weather attribution studies with a Shiny app for this week's #TidyTuesday

App: karamanis.shinyapps.io/ExtremeWeath...
Code: github.com/gkaramanis/t...

#RStats #dataviz
Screenshot of an interactive Shiny app displaying a world map with country boundaries. Countries are shaded in varying colors based on the number of extreme weather attribution studies. A draggable control panel on the right shows details for a selected country, including event types, study summaries, and publication years. The app includes a table tab that lists all studies. The data is sourced from Carbon Brief's tracking of attribution studies, which analyze the influence of climate change on extreme weather events.
August 17, 2025 at 12:11 PM
Reposted by Georgios Karamanis
emilhvitfeldt.bsky.social
some light teasing for an upcoming quarto revealjs plugin I have been working on
August 12, 2025 at 7:03 PM
karaman.is
Income inequality for this week's #TidyTuesday. How do countries redistribute income through taxes and transfers?

Code: github.com/gkaramanis/t...

#RStats #dataviz
A horizontal line chart showing income inequality before and after government redistribution across 30 countries, organized by world regions. Each horizontal line represents one country, starting from market income inequality (right side) and ending at disposable income inequality after taxes and transfers (left side). The x-axis shows Gini coefficients from 0.2 to 0.7, where higher values indicate more inequality. Countries are grouped into regions: Europe with 20 countries, North America (3), Asia (2), and one each from Oceania, South America, and Africa. The lines are colored by the ratio of redistribution effectiveness, with darker colors indicating countries that achieve greater inequality reduction. Notable patterns include: Belgium achieves the most dramatic reduction, cutting inequality nearly in half from 0.49 to 0.26. In contrast, Dominican Republic shows minimal change from 0.52 to 0.52 (rounded). European countries generally show stronger redistribution effects than other regions. South Africa has both the highest initial inequality (0.71) and final inequality (0.62) despite some redistribution. Most countries reduce inequality to some degree, but the magnitude varies significantly even among countries with similar starting inequality levels.
August 10, 2025 at 1:04 PM
Reposted by Georgios Karamanis
tvaziri.com
unmute
August 4, 2025 at 5:28 PM
karaman.is
Something different for this week's #TidyTuesday, looking at Netflix's creative charting, as spotted by @nrennie.bsky.social

I measured the actual bar lengths from Netflix's H1 2025 engagement report and compared them to what they should be based on view counts.

#RStats #dataviz
A horizontal bar chart recreating Netflix's top 10 movies from H1 2025, overlaid on the original report image to reveal visual discrepancies. Red outlined bars show the proportionally correct lengths based on actual view counts, with "Back in Action" leading at 165M views. The overlay demonstrates how Netflix's original bars don't accurately represent the data proportions, with several movies appearing visually larger than their view counts warrant. A horizontal bar chart recreating Netflix's top 10 shows from H1 2025, overlaid on the original report image to expose proportional inaccuracies. Red outlined bars display the correct visual proportions based on actual view counts, with "Adolescence: Limited Series" leading at 145M views. The comparison reveals how Netflix's original visualization misleads viewers about the relative performance differences between shows. A dual-panel scatter plot analyzing Netflix's bar chart accuracy. The left panel shows Movies and right panel shows Shows, both plotting actual measured bar lengths (y-axis, in pixels) against view counts (x-axis). Purple points represent Movies, teal points represent Shows. Dashed lines show proportionally correct bar lengths. Movies show larger deviations from the expected line, with several points well above it, while Shows generally follow the expected line more closely. Point labels identify specific titles.
August 3, 2025 at 1:26 PM
karaman.is
A Shiny app for last week's #TidyTuesday. Explore and learn about selected NYC subway artworks

App: karamanis.shinyapps.io/New_Yorks_Un...
Code: github.com/gkaramanis/t...

#RStats #dataviz
Screenshot of 'New York's Underground Gallery' interactive web application showing MTA subway art locations. The interface features a large title at the top, followed by a control panel with small clickable buttons for notable artworks including 'Wall-Slide', 'Subway Portraits', 'Blueprint for a Landscape', and others, with a red 'CLEAR' button. The main content area displays a map of New York City subway lines on the left side with purple circular markers indicating artwork locations, and a detailed artwork viewer panel on the right side titled 'ARTWORK DETAILS' with a purple gradient header. The right panel shows information for a selected artwork including an image placeholder, artwork title, artist name, station location, metadata such as date and medium, and a description. The interface uses a modern design with Space Grotesk and Inter fonts, purple and blue accent colors, and a clean white background. A dark footer at the bottom credits data sources including MTA Arts & Design Collection and NYC OpenData, and lists the creator as Georgios Karamanis.
July 28, 2025 at 11:45 AM