@sara-altman.bsky.social and I recently got together to compare Claude Code and Posit Assistant for data analysis with a recent #TidyTuesday release! The recording is now live on YouTube: www.youtube.com/watch?v=7GI6...
It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io
#RStats #PyData #JuliaLang #RustLang #DataViz #DataScience #DataAnalytics #data #tidyverse #DataBS
New Zealand map with recorded points of seabird observations; faceted by years of 1969 and 1975-88.
My submission for #TidyTuesday, Week 15 on Bird Sightings at Sea. I plot recorded points within 100km from coastal lines.
Code: github.com/mitsuoxv/tid...
Timeline bubble chart showing observations of different penguin types off the coast of New Zealand from 1969 to 1990. Adelia, Emperor, and Fiordland crested have only been seen a few times, but there are regular sightings of Little penguins.
For this week's #TidyTuesday data on sea bird sightings, there was an obvious choice for which type of bird to focus on - penguins! π§
π Bubble timeline made with #RStats
π¨ Colours inspired by {palmerpenguins}
π Annotations added with {cowplot}
#DataViz #ggplot2
#TidyTuesday week 15: Bird Sightings at Seaππ¦
I built this bird swarm visualization using #D3js
I explored how sightings cluster across cloud type conditions and turn the data into a drifting swarm of bird marks.
#DataViz
#TidyTuesday this week looked at bird sightings at sea. I chose to explore the observers' relationship with the "Navigators", a role according to their MΔori roles. π github.com/afrikaniz3d-...
#DataViz #RStats #DataVisualization #ECharts4R #Quarto Open to freelance data viz/reporting work
For #tidytuesday week 2026-03-31, looking at coastal ocean temperatures in Nova Scotia, I was mesmerized by the seasonal pattern displayed in my initial geom_point exploration plot that I had to keep it. Temperature generally goes down with depth.
#rstats #dataviz #ggplot2
Exploring the Milan-Cortina 2026 Olympic schedule for #TidyTuesday βοΈβΈοΈβ·οΈ
I looked at how different sports allocate officially scheduled sessions between training and competition.
πCode: github.com/Lexi711State...
Bird Sightings in the Tasman Sea, New Zealand and Australian waters (1969β1990) for #TidyTuesday, week 14.
#30DayChartChallenge | Flowingdata
#Rstats #Dataviz #ggplot2
Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash.
TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results! TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club! How to Participate Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data. Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language. Share your output and the code used to generate it on social media with the #TidyTuesday hashtag.
Screenshot of an interactive visualization summarizing bird sightings. At top, a zoomed out world map displays record density with thousands of observations intensely clustered in specific grid cells within the Southern Ocean. At bottom left, a temporal histogram starts with about 1000 records in 1969, no data for 1970 to 1974, then counts that peak at over 3000 records from 1984 to 1987, quickly trailing off and ending in 1990. At bottom right, a nested taxonomic sunburst chart shows that all records are within the Phylum Chordata and Class Aves. The vast majority of records are within Order Procellariiformes and Family Procellariidae, with representation from other Procellariiformes Families (primarily Diomedeidae) and other Orders: Charadriiformes (Family Laridae) and Pelecaniformes (Family Sulidae).
@dslc.io welcomes you to week 15 of #TidyTuesday! We're exploring Bird Sightings at Sea!
π https://tidytues.day/2026/2026-04-14
ποΈ obis.org/dataset/29ea15ed-8f76-40...
#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds
#30DayChartChallenge Day 3: Mosaic and #TidyTuesday week 14: Repair Cafes Worldwide
Created this faceted mosaic chart using #D3js
#DataViz #DataVisualization #RepairCafes
π¦ tidytuesdayR 1.3.2 is on its way to CRAN π
Changes center around Dataset Curation functions
β Curation works on Positron
π§βπ» tt_meta() gains options for attribution/social media
β
tt_submit() checks & deals with more things
dslc-io.github.io/tidytuesdayR...
#RStats #DataBS #TidyTuesday
#30DayChartChallenge 2026 Day10: Pop
How does #Spotify classify #Billboard top100 pop songs? The bumpline chat shows classifications by the finest categories. The data is from #tidytuesday 2021 week 38 challenge.
Two-panel data visualization titled "Rough Seas Suppress Feeding β They Don't Enhance It." Panel A is a heatmap showing survey effort by wind condition (Beaufort scale, binned Calm to Gale+) and sea state (SS1βSS6). Observation density peaks at slight-to-moderate seas with light-to-moderate winds, shown in deep navy. Panel B is a dot plot with Wilson 95% confidence intervals showing seabird feeding rates by sea state. Feeding peaks at 11.9% under calm, rippled conditions (SS1) and declines steadily through rough (SS5, ~4%) and very rough seas (SS6, ~2%). A dashed reference line marks the peak feeding rate. Data from Te Papa Tongarewa, Museum of New Zealand, 1969β1990.
π #TidyTuesday β 2026 W15 | Bird Sightings at Sea
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π: stevenponce.netlify.app/data_visuali...
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#rstats | #r4ds | #dataviz | #ggplot2
The nine economies that will define the next 20 years of energy.
The nine economies that will define the next 20 years of energy.
Each panel is its own transition β compare them side by side.
Explore β energtx.com/datasets
#EmergingMarkets #EnergyTransition #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
Whose energy appetite grew β and whose shrank?
Whose energy appetite grew β and whose shrank?
A view of per-capita energy demand change, ranked by size.
Explore β energtx.com/datasets
#EnergyDemand #PerCapita #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
Who cleaned up their electricity fastest?
Who cleaned up their electricity fastest?
Green bars = climbed. Red bars = regressed. 8 years, 20 biggest movers.
Explore β energtx.com/datasets
#CleanElectricity #Decarbonization #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
On a per-person basis, Denmark laps the world.
On a per-person basis, Denmark laps the world.
Seven European leaders plotted together β the gap is wider than headlines suggest.
Explore β energtx.com/datasets
#Wind #Denmark #Europe #PerCapita #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
Solar per capita isn't about China β it's about rooftops.
Solar per capita isn't about China β it's about rooftops.
Australia and Netherlands lead on a per-person basis.
Explore β energtx.com/datasets
#Solar #PerCapita #Australia #Netherlands #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
The Gulf uses electricity like nowhere else.
The Gulf uses electricity like nowhere else.
Even among the wealthy, the GCC stands out for sheer per-person demand.
Explore β energtx.com/datasets
#GCC #Gulf #Electricity #PerCapita #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
High-use grids AND high-renewable grids β can both be true?
High-use grids AND high-renewable grids β can both be true?
Bubble = population. A handful of countries sit in the upper-right quadrant.
Explore β energtx.com/datasets
#Electricity #Renewables #Scatter #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
Who gets the most renewable electricity per head?
Who gets the most renewable electricity per head?
Norway, Iceland, and a handful of countries punch far above their weight.
Explore β energtx.com/datasets
#Renewables #PerCapita #Norway #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
Eight grids where gas is the grid.
Eight grids where gas is the grid.
Qatar, Iran, Algeria β and a few surprises at 90%+.
Explore β energtx.com/datasets
#NaturalGas #Gas #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
Seven grids that still lean hard on coal.
Seven grids that still lean hard on coal.
Mongolia, Kosovo, Bosnia β not the usual suspects.
Explore β energtx.com/datasets
#Coal #CoalPower #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
G20's 'other half' on clean primary energy.
G20's 'other half' on clean primary energy.
A heatmap over 23 years. Some countries barely moved.
Explore β energtx.com/datasets
#G20 #LowCarbon #Heatmap #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
10 countries where hydro is the grid.
10 countries where hydro is the grid.
When droughts hit, these economies don't just lose power β they lose the power system.
Explore β energtx.com/datasets
#Hydropower #WaterSecurity #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
Per-capita energy is climbing across the big emerging economies.
Per-capita energy is climbing across the big emerging economies.
Slope chart: 2000 on the left, 2023 on the right.
Explore β energtx.com/datasets
#PerCapita #EmergingMarkets #EnergyUse #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
Eight countries, one story: booming electricity demand.
Eight countries, one story: booming electricity demand.
This is where the next 5,000 TWh will come from.
Explore β energtx.com/datasets
#Electricity #ElectricityDemand #Turkey #Vietnam #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
How the biggest EU grids decarbonized.
How the biggest EU grids decarbonized.
Six lines, six paces. The UK and Germany made giant strides; Poland barely moved.
Explore β energtx.com/datasets
#EU #CarbonIntensity #Germany #Poland #UK #ClimateData #EnergyTransition #EnergyData #DataViz #RStats #ggplot2 #TidyTuesday
