A grid of 26 small maps on a white background titled "The captain's logbook." The top-left area contains the subtitle and source caption. The remaining panels show seabird observation locations in the Southern Ocean for 25 individual ship observers, ordered by total observations. J. Jenkins dominates with 6583 observations (1969–1988), his panel filled densely with blue dots scattered across Antarctic and subantarctic waters. N. Cheshire has 1462 observations (1975–1983). Subsequent rows show progressively fewer observations, down to observers with only 1–4 sightings in the final row. Each map covers approximately 65–180°E longitude and 20–75°S latitude, with a muted blue ocean and soft tan land masses. Observer name, total observations, and year range are shown above each panel. Caption reads "Source: Museum of New Zealand Te Papa Tongarewa · Graphic: Georgios Karamanis."

This week's #TidyTuesday dataset comes from the at-sea seabird records held by Te Papa Tongarewa, built largely from the handwritten logbooks of Captain J. Jenkins, who recorded 6583 bird sightings on Southern Ocean voyages from 1969 to 1988.

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

#RStats #dataviz

You could say it is a textbook example! 😆

#day17 of #30DayChartChallenge, Remake

A better version of day 13: bsky.app/profile/kara...

code: github.com/gkaramanis/3...

#RStats #dataviz

A line chart titled "Bonus-malus effect?" showing new EV and plug-in hybrid car registrations per 10,000 residents in Uppsala municipality from 2010 to 2024. The line hovers near zero until around 2013, then climbs slowly before accelerating sharply from 2018, when Sweden's bonus-malus policy introduced rebates for EVs and taxes on high-emission cars, highlighted by a blue-grey shaded band. Registrations peak at roughly 110 per 10,000 residents in 2022–2023, then fall back to around 80 in 2024 after the bonus was removed, leaving only the malus tax on high-emission cars, marked by a pale amber band. Source: SCB.

#day16 of #30DayChartChallenge, Causation

code: github.com/gkaramanis/3...

#RStats #dataviz

A scatter plot titled "A seasonal pattern" showing the relationship between average monthly temperature and Uppsala city bus ridership for 2024 and 2025. The x-axis runs from about −5°C to 20°C and the y-axis from roughly 1.2 million to 2.8 million monthly trips. A grey regression line slopes downward from upper left to lower right, indicating a negative correlation. Points are labeled with three-letter month abbreviations and colored by year: indigo for 2024 and amber for 2025. Cold winter months such as January and February cluster in the upper left with the highest ridership, while warm summer months, particularly July, which sits at around 20°C and below 1.5 million trips, fall at the lower right. The two years follow a very similar pattern. Source: UL Statistik and SMHI Open Data.

#day15 of #30DayChartChallenge, Correlation

code: github.com/gkaramanis/3...

#RStats #dataviz

A circle packing chart titled "Goods on the move" showing road freight loaded in Uppsala County by goods type in 2024, measured in thousand tonnes. Circles are color-coded by three categories shown in a top legend: amber for Logistics and mixed, indigo for Manufactured, and near-black for Raw and natural. The largest circle by far is Mining and quarrying at 3,215 thousand tonnes, in near-black. The next largest are Food and beverages at 1,329 (indigo), Removals and miscellaneous at 1,310 (amber), and Agriculture and fish at 1,233 (near-black). Further mid-sized circles include Wood, paper and print at 644, Transport support at 640, Non-metallic minerals at 547, Machinery and electronics at 492, and Mail and parcels at 490. Smaller circles for Coke and petroleum, Secondary raw materials, and a few others are also visible. Source: Eurostat, road_go_na_rl3g.

#day14 of #30DayChartChallenge, Trade

code: github.com/gkaramanis/3...

#RStats #dataviz

A bubble chart titled "Kids go their own way" with the subtitle "Share of journeys by mode and grade in Uppsala, 2021." The chart shows four transport modes, car, public transit, cycling, and walk, as columns, with school grades F-class through Year 6 as rows. Each cell contains a circle whose size and labelled percentage represent the share of journeys for that mode and grade. Car use (indigo circles) falls steadily from 36% in F-class to 11% by Year 6. Public transit use (amber circles) rises from 7% to 27% over the same range. Cycling (near-black circles) stays relatively stable between 27% and 33%. Walking (grey circles) peaks at 40% in Year 5 and drops to 30% in Year 6. The data come from a guardian survey of over 7,400 households. Source: Uppsala kommun, guardian survey.

#day13 of #30DayChartChallenge, Ecosystems (a stretch)

code: github.com/gkaramanis/3...

#RStats #dataviz

A small-multiple slope chart titled "Riding Uppsala" with the subtitle "Bus journeys declined in 2025." The chart contains twelve facets, one per calendar month, each showing an arrow from 2024 to 2025 representing the number of city bus trips made on UL (Upplands Lokaltrafik) in Uppsala. Amber arrows indicate months where ridership fell; indigo arrows indicate months where it rose. Ten of the twelve months saw declines: January dropped from 2.7 million to 2.5 million trips, February from 2.7 million to 2.4 million, and April had the steepest fall, from 2.7 million to 2.1 million. Only March and May showed marginal increases. Summer months have the lowest ridership overall, with July falling from 1.5 million to 1.3 million. Source: UL.

#day12 of #30DayChartChallenge, FlowingData

code: github.com/gkaramanis/3...

#RStats #dataviz

A grid of nine small charts on a warm off-white background titled "Are older things harder to fix?" Each panel shows smoothed repairability scores on the y-axis against item age at the time of repair on the x-axis, with the scale reversed so older items (up to 100 years) are on the left and newer items on the right. Lines are colored amber for electric and green for non-electric items. Panels are faceted by category: Bicycles, Clocks and alarm clocks, Computer equipment and phones, Display and sound equipment, Household appliances, Jewelry, Textile, Tools, and Toys. In household appliances, tools, and toys, the amber and green lines cross over across the age range. Clocks, textiles, and display and sound equipment show lower repairability scores among older items. Bicycles, computers and phones, and jewelry show little variation across the age range. Caption reads "Source: RepairMonitor · Graphic: Georgios Karamanis."

This week's #TidyTuesday dataset comes from RepairMonitor, which has been logging repairs at volunteer-run Repair Cafés worldwide since 2015. Are older things harder to fix? Depends on the category.

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

#RStats #dataviz

A scatter plot titled "Wheels & wealth in Uppsala..." with the subtitle "...mostly correlate, except for one district." The x-axis shows median net income in thousand kronor and the y-axis shows cars in use per capita. Each point represents one of Uppsala's residential districts, sized by population and coloured in indigo blue. The overall trend is positive, higher-income districts tend to have more cars per capita. Four groups are highlighted with amber hulls: "Student areas" (Studentstaden and Västra Flogsta) sit at low income and low car ownership; "6 peripheral areas" (Stadens omland) cluster in the mid-to-high income and mid-to-high ownership range; "Highest income" (Gamla Gottsunda-Vårdsätra-Vreta) is at the far right with high income but moderate ownership; and "Kåbo-Norra Rosendal" is the clear outlier with middle income but by far the highest cars per capita at around 0.85, well above the trend. Source: Statistics Sweden, cars 2025, income 2024.

#day9 of #30DayChartChallenge, Wealth

code: github.com/gkaramanis/3...

#RStats #dataviz

Thanks! 🙏

A radial bar chart titled "Uppsala's bus clock" with the subtitle "Departures per hour, weekday vs weekend." Hours of the day (0:00 to 23:00) are arranged clockwise around a circle. For each hour, two bars extend outward: orange for weekday and blue for weekend departures. Weekday bars are substantially longer, peaking at 7:00 with 3,145 average departures, with a second peak at 15:00 (3,120). The overnight trough bottoms out at 2:00 with 56 departures. Weekend bars are much shorter and more evenly distributed, peaking mid-morning around 10:00–11:00 with around 680 departures and dropping to 56 at 4:00. Source: UL GTFS data, 4–30 April 2026.

#day8 of #30DayChartChallenge, Circular

code: github.com/gkaramanis/3...

#RStats #dataviz

A two-panel chart titled "Uppsala emissions down" with the subtitle "Change in total and breakdown by sector." The upper panel is a line chart showing the percentage change in Uppsala's total greenhouse gas emissions relative to 1990, from 1990 to around 2023. Emissions rose slightly through the 2000s before falling sharply, reaching −44% by 2023. The lower panel is a stacked area chart showing absolute emissions in kilotons by sector over the same period. At its peak around 2010, total emissions were close to 1100 kt and almost halved by 2023 to 550 kt. Electricity and heat (orange) is the largest sector and has declined the most; Transport (indigo), Agriculture (grey), and Other (light grey) make up the rest. Source: Nationella emissionsdatabasen, SMHI.

#day7 of #30DayChartChallenge, Multiscale

code: github.com/gkaramanis/3...

#RStats #dataviz

Pushed the data now, thanks!

Thank you!

An experimental chart titled "Cold months fill the buses" with the subtitle "Bus ridership vs. temperature in Uppsala." Twelve center-aligned bars, one per month, are stacked vertically and arranged so the year wraps from June at the top through January in the middle to July at the bottom. Because the bars extend symmetrically from a central axis rather than from a baseline, the chart forms a leaf-like silhouette. Bar length encodes monthly bus ridership and bar color encodes average temperature: orange for warm months and indigo-blue for cold ones. Winter months such as January are longer, showing that Uppsala residents ride the bus more when it is cold. Source: UL and SMHI, 2024–2025 averages

#day5 of #30DayChartChallenge, Experimental

code: github.com/gkaramanis/3...

#RStats #dataviz

Absolutely not! 🙂

A slope chart titled "Uppsala trains on track" with the subtitle "More running, more on time." Two lines connect 2024 and 2025. The blue line shows the share of trains operated: 98% in 2024, rising to 98.5% in 2025. The orange line shows the share arriving within 5 minutes of schedule: 84.6% in 2024, rising to 87.1% in 2025. Source: Trafikanalys.

#day4 of #30DayChartChallenge, Slope

code: github.com/gkaramanis/3...

#RStats #dataviz

A mosaic chart titled "Roads and cycle paths." Two columns, bicycle and car, divided into rows by maintainer type (Private, Municipal, State). The car network dominates: Municipal roads account for 3 488 km, State roads 941 km, and Private roads 562 km. The bicycle network is far smaller: Municipal 446 km, State 47 km, Private 42 km. Source: NVDB, 2025.

#day3 of #30DayChartChallenge, Mosaic

code: github.com/gkaramanis/3...

#RStats #dataviz

*In 2025

A pictogram chart titled "New cars in Uppsala County." Five bars made of car icons, one bar per make, each icon representing 10 registrations. Volkswagen leads with 1 045 registrations (roughly 104 icons, shown in indigo), followed by Toyota (899, saffron), Volvo (881, saffron), Kia (780, grey), and Skoda (639, grey). The makes are labelled in bold to the top left of each bar with their exact count. Source: Mobility Sweden, 2025.

#day2 of #30DayChartChallenge, Pictogram

code: github.com/gkaramanis/3...

#RStats #dataviz

Donut chart titled "How Uppsala County moves" showing share of distance traveled by mode in 2024. Car dominates at 70.8% (dark blue), followed by public transit at 19.7% (amber), other at 5.5% (light grey), walking at 2.2% (dark grey), and cycling at 1.9% (medium grey). Source: Sveriges Miljömål, Graphic: Georgios Karamanis

#day1 of #30DayChartChallenge, Part-to-Whole

code: github.com/gkaramanis/3...

#RStats #dataviz

Thank you!

A grid of small charts on a light grey background titled "Nova Scotia's Ocean Pulse." Rows represent years and columns represent months. Each panel shows ocean depth as concentric rings (shallower on the outside, deeper toward the centre) and mean water temperature as color using a green-yellow-red diverging palette. Summer months show warmer temperatures in the outer (shallow) rings fading to cooler temperatures at the centre. Winter months are predominantly cooler throughout. A small legend in the upper left explains that depth increases inward. Subtitle reads "Seven years of daily coastal temperature measurements at depths of 2, 5, 10, 15, 20, 30, and 40 metres, from the Centre for Marine Applied Research." Caption reads "Source: Centre for Marine Applied Research · Graphic: Georgios Karamanis."

This week's #TidyTuesday dataset is seven years of daily ocean temperature measurements from Nova Scotia's coastline, recorded at depths down to 40 metres by the Centre for Marine Applied Research

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

#RStats #dataviz

A horizontal bar chart on a light grey background showing how many digits of pi are needed for different purposes, on a log scale. Bars are light blue except the TidyTuesday dataset bar, which is orange. From top to bottom: Everyday math (5), Voyager 1 trajectory with error less than a finger width (16), Observable universe circumference within one hydrogen atom (38), Max any practical science ever needs (100), This TidyTuesday dataset (1 million), Google world record by Emma Haruka Iwao in 2019 (31.4 trillion), Guinness World Record by KIOXIA and Linus in 2025 (300 trillion), Unofficial record by StorageReview in 2025 (314 trillion). Each bar is labeled with its value. Title reads "HOW MANY DIGITS OF PI DO WE NEED?"

This week's #TidyTuesday dataset is a million digits of π, which is far more than anyone will ever use. The plot shows how many digits we actually need. Spoiler: science caps out way before the computers do

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

#RStats #dataviz

Another week, another Sims 4 CC update!

A laptop with blurry #Rstats hex stickers and @kjhealy.co's #dataviz book (first edition!) with a broken texture, both works in progress. Textures are hard 😅

It's been some time since I shared a making of video! Here is one for last week's #TidyTuesday