#30daychartchallenge — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #30daychartchallenge, aggregated by home.social.
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Un resumen de mi participación en el #30DayChartChallenge 2026 :)
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Un resumen de mi participación en el #30DayChartChallenge 2026 :)
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#30DayChartChallenge Day 10 | Pop Culture. Top 20 #books of 2025 by genre & publish date, according to Readers’ favourites on Goodreads. 📚📖
Most romance novels were published in spring/summer. Nonfiction books have the longest book titles and Fantasy books lead in terms of total pages.
Tried to make it look like a book shelf, not sure I suceeded 😅
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#30DayChartChallenge Day 10 | Pop Culture. Top 20 #books of 2025 by genre & publish date, according to Readers’ favourites on Goodreads. 📚📖
Most romance novels were published in spring/summer. Nonfiction books have the longest book titles and Fantasy books lead in terms of total pages.
Tried to make it look like a book shelf, not sure I suceeded 😅
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#Day30| Uncertainties – Data Day – Global Health Data Exchange | #30DayChartChallenge | Life Expectancy at Birth — Latin America & Caribbean. Built with #RStats using #ggplot2, #patchwork, #scales, #grid, #gridExtra and #tidyr.
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#Day30| Uncertainties – Data Day – Global Health Data Exchange | #30DayChartChallenge | Life Expectancy at Birth — Latin America & Caribbean. Built with #RStats using #ggplot2, #patchwork, #scales, #grid, #gridExtra and #tidyr.
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#Day29 | Uncertainties – Monochrome | #30DayChartChallenge | . Coffee Price Forecast — Holt-Winters (HW) Built with #RStats using #forecast, #ggplot2, #dplyr, #lubridate, #scales and #tidyr.
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#Day29 | Uncertainties – Monochrome | #30DayChartChallenge | . Coffee Price Forecast — Holt-Winters (HW) Built with #RStats using #forecast, #ggplot2, #dplyr, #lubridate, #scales and #tidyr.
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#Day28 | Uncertainties – Modeling | #30DayChartChallenge | Barro Colorado Island — Tree Species Richness Estimation. Built with #RStats using #ggplot2, #patchwork, #MASS, #mgcv, #scales, #vegan, #gridExtra and #grid.
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#Day28 | Uncertainties – Modeling | #30DayChartChallenge | Barro Colorado Island — Tree Species Richness Estimation. Built with #RStats using #ggplot2, #patchwork, #MASS, #mgcv, #scales, #vegan, #gridExtra and #grid.
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Fun #dataviz for the #30DayChartChallenge Day8 Circular 👽🛸 UFO sightings around the world reported to the National UFO Reporting Center between 1926 & 2013 (total >80,000).
Reports increased since the 1990s, maybe internet made reporting easier or more happening in space? (note: that last week with fewest dots is when the year has 53 weeks which doesnt happen a lot)
Data via #TidyTuesday
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Fun #dataviz for the #30DayChartChallenge Day8 Circular 👽🛸 UFO sightings around the world reported to the National UFO Reporting Center between 1926 & 2013 (total >80,000).
Reports increased since the 1990s, maybe internet made reporting easier or more happening in space? (note: that last week with fewest dots is when the year has 53 weeks which doesnt happen a lot)
Data via #TidyTuesday
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#Día27 | Incertidumbre – Animación | #30DayChartChallenge | Tendencia de la temperatura global. Creado con #RStats usando #dplyr, #ggplot2 y #gganimate.
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#Día27 | Incertidumbre – Animación | #30DayChartChallenge | Tendencia de la temperatura global. Creado con #RStats usando #dplyr, #ggplot2 y #gganimate.
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#Día26 | Incertidumbre – Tendencias | #30DayChartChallenge | Tendencia de la temperatura global. Creado con #RStats usando #dplyr y #ggplot2
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#Día26 | Incertidumbre – Tendencias | #30DayChartChallenge | Tendencia de la temperatura global. Creado con #RStats usando #dplyr y #ggplot2
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#Day25 | Uncertainties – Space | #30DayChartChallenge | Near-Earth Asteroid Orbit Uncertainties. Built with #RStats using #ggplot2 and #ggrepel.
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#Day25 | Uncertainties – Space | #30DayChartChallenge | Near-Earth Asteroid Orbit Uncertainties. Built with #RStats using #ggplot2 and #ggrepel.
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Day 26 of the #30DayChartChallenge: Trend 📊 (a couple of days early)
A simple chart made with #RStats to show how easy it is to get nice-looking, effective charts with {ggauto}!
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Day 26 of the #30DayChartChallenge: Trend 📊 (a couple of days early)
A simple chart made with #RStats to show how easy it is to get nice-looking, effective charts with {ggauto}!
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#Día24 | Series de Tiempo – Día Temático - South China Morning Post | #30DayChartChallenge | Producción de Café en Centroamérica: Tendencias 2021-2025. Creada usando #Rstats con #ggplot2, #patchwork, #dplyr, #grid, #gridExtra, #scales, #sf, #rnaturalearth y #rnaturalearthdata.
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#Día24 | Series de Tiempo – Día Temático - South China Morning Post | #30DayChartChallenge | Producción de Café en Centroamérica: Tendencias 2021-2025. Creada usando #Rstats con #ggplot2, #patchwork, #dplyr, #grid, #gridExtra, #scales, #sf, #rnaturalearth y #rnaturalearthdata.
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#Día23 | Series de Tiempo – Seasons (Temporadas) | #30DayChartChallenge | Malcolm in the Middle. Creada usando #Rstats con #ggplot2, #dplyr, #ggtext, #showtext, #patchwork, #scales y #glue.
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#Día23 | Series de Tiempo – Seasons (Temporadas) | #30DayChartChallenge | Malcolm in the Middle. Creada usando #Rstats con #ggplot2, #dplyr, #ggtext, #showtext, #patchwork, #scales y #glue.
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#Día22 | Series de Tiempo – Nueva Herramienta | #30DayChartChallenge | Precio histórico del aceite de palma. Creada usando #Python con #io, #pandas, #numpy y #matplotlib
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#Día22 | Series de Tiempo – Nueva Herramienta | #30DayChartChallenge | Precio histórico del aceite de palma. Creada usando #Python con #io, #pandas, #numpy y #matplotlib
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Day 22 of the #30DayChartChallenge: New Tool 📊
🛠️ Tool: @datawrapper table
🏭 Data: @ourworldindata
💜 With some data wrangling in #RStats -
Day 22 of the #30DayChartChallenge: New Tool 📊
🛠️ Tool: @datawrapper table
🏭 Data: @ourworldindata
💜 With some data wrangling in #RStats -
From the boom of AI 🤖, to the strategic use of sea routes 🌊 and on to changes in municipal populations🏡, visualisations are useful for illustrating complex topics. Find out more about them and a new batch of #30DayChartChallenge visualizations in our latest blog!👇
https://www.datawrapper.de/blog/data-vis-dispatch-april-21-2026-sea-routes-ai-and-penguins -
From the boom of AI 🤖, to the strategic use of sea routes 🌊 and on to changes in municipal populations🏡, visualisations are useful for illustrating complex topics. Find out more about them and a new batch of #30DayChartChallenge visualizations in our latest blog!👇
https://www.datawrapper.de/blog/data-vis-dispatch-april-21-2026-sea-routes-ai-and-penguins -
Catching up #dataviz for #30dayChartChallenge Day5 Experimental. Which flower attracts which pollinator? 🌸🐝🦋
Played around with data from the UK Pollinator Monitoring Scheme. For bees or any pollinator plant some lavender, for butterflies go with buddleja aka butterfly bush.
Made in #Svelte + #D3. Still practicing, so progress is slow but learning lots!
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Catching up #dataviz for #30dayChartChallenge Day5 Experimental. Which flower attracts which pollinator? 🌸🐝🦋
Played around with data from the UK Pollinator Monitoring Scheme. For bees or any pollinator plant some lavender, for butterflies go with buddleja aka butterfly bush.
Made in #Svelte + #D3. Still practicing, so progress is slow but learning lots!
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💡 Changes life expectancy follow changes in total death counts -- an observation of Alexsey Raksha ✨
📝 https://doi.org/10.31219/osf.io/g9mxt
🔗 #rstats code: https://github.com/ikashnitsky/30daychart2026
🧙♂️ no ai jumpstarter this time, I worked off Jonas Schoeley's code, all here https://github.com/ikashnitsky/ex-delta
DAY 16 -- causation 💫 #30DayChartChallenge -
#Día19 | Series de Tiempo – Evolución | #30DayChartChallenge | Nuevas especies de mamíferos descritas por la ciencia · 1900–2050. Creada usando #Rstats con #ggplot2, #dplyr, #scales y #patchwork.
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DAY 15 -- correlation 😱 #30DayChartChallenge
I was struggling to come up with a funny correlation example, so decided to revisit the famous plot that claimed rappers dye young, featured in Calling Bullshit 😆
🔗 #rstats code: https://github.com/ikashnitsky/30daychart2026
🧙♂️ pplx chat: https://www.perplexity.ai/search/day-15-correlation-i-recall-th-R_fAVa8gTEuZZ4tOikdgwA#1 -
Day 17 of the #30DayChartChallenge: Remake 📊
🛠️ A remake of a remake! This is a remake of a chart I originally made with #RStats a few years ago then remade with #Python for the Plotnine contest, and remade again today - this time using LibreOffice Calc!
(Originally started the remake with Excel but it was actually easier in LibreOffice in case you needed another reason to switch to LibreOffice)
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Installations of small-scale renewable technology like solar panels, heat pumps and battery storage have risen notably in the UK over the past few years. ☀️ 🌬️
In March the UK government announced that plug-in solar panels will become legal soon. This will make the data on rollout more patchy, but probably boost uptake.
#Dataviz for the #30DayChartChallenge Day4 Slope
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DAY 14 -- trade 💰 #30DayChartChallenge
This is a very lazy shoot, the map below is completely compiled by Claude Sonnet 4.6 via Perplexity 🤯
I got curious about the cases when land was traded between countries
🔗 #rstats code: https://github.com/ikashnitsky/30daychart2026
🧙♂️ pplx chat: https://www.perplexity.ai/search/day-14-trade-another-idea-for-36pTpR.SRW.3mqSuBL_Nlg -
🎨 {linuxcolors} a small #rstats package with the identity colors of the most popular #Linux distros 🐧
💎 #ggplot2 ready with scale_{color/fill}_linux() functions🔗: https://github.com/ikashnitsky/linuxcolors 📦
DAY 13 -- ecosystems 🌍 #30DayChartChallenge
✨ #FOSS world is a unique human #ecosystem -
#30DayChartChallenge Día 29: Extraterrestrial! 👽✨ ¡Planetas con su incertidumbre a cuestas! #UncertaintiesWeek #Astronomy
Volvemos al gráfico Radio vs Insolación (log-log, color=Temp) de exoplanetas (NASA Archive). Pero hoy añadimos una capa visual para la incertidumbre: el "halo" gris ⚪️ detrás de cada punto.
El tamaño del halo es proporcional al log(error) reportado para la Insolación. ¡Halos grandes = más incertidumbre en la energía que recibe ese planeta!
Es un recordatorio de que los datos astronómicos tienen errores y no todos los puntos son igual de "seguros". Interesante ver qué planetas en la zona habitable (verde) tienen más incertidumbre. (+ Venus/Tierra/Marte 💎).
🛠 #rstats #ggplot2 #ggrepel | Data: NASA | Theme: #theme_week5_uncertainty
📂 Código/Viz: https://t.ly/ygNLW#Day29 #Extraterrestrial #dataviz #DataVisualization #Exoplanets #HabitableZone #Astrobiology #UncertaintyViz #ErrorVisualization #NASA #ggplot2 #RStats #Science
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#30DayChartChallenge Día 29: Extraterrestrial! 👽✨ ¡Planetas con su incertidumbre a cuestas! #UncertaintiesWeek #Astronomy
Volvemos al gráfico Radio vs Insolación (log-log, color=Temp) de exoplanetas (NASA Archive). Pero hoy añadimos una capa visual para la incertidumbre: el "halo" gris ⚪️ detrás de cada punto.
El tamaño del halo es proporcional al log(error) reportado para la Insolación. ¡Halos grandes = más incertidumbre en la energía que recibe ese planeta!
Es un recordatorio de que los datos astronómicos tienen errores y no todos los puntos son igual de "seguros". Interesante ver qué planetas en la zona habitable (verde) tienen más incertidumbre. (+ Venus/Tierra/Marte 💎).
🛠 #rstats #ggplot2 #ggrepel | Data: NASA | Theme: #theme_week5_uncertainty
📂 Código/Viz: https://t.ly/ygNLW#Day29 #Extraterrestrial #dataviz #DataVisualization #Exoplanets #HabitableZone #Astrobiology #UncertaintyViz #ErrorVisualization #NASA #ggplot2 #RStats #Science
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It's almost the end of the #30DayChartChallenge and for the prompt of "Extraterrestrial", I decided to make a chart designed in the style of an extraterrestrial who has never heard of good data visualisation principles! 📊
How many chart crimes can you spot? 🕵️♂️
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It's almost the end of the #30DayChartChallenge and for the prompt of "Extraterrestrial", I decided to make a chart designed in the style of an extraterrestrial who has never heard of good data visualisation principles! 📊
How many chart crimes can you spot? 🕵️♂️