Día 3| Comparaciones – Círculos | #30DayChartChallenge. La visualización fue creada usando R basado en los paquetes #sf, #terra, #tidyterra, #extarctexactr, #ggplot2, #dplyr, #scales, #ggnewscale ,#ggtext, #patchwork y #showtext. Fuente SRTM y SIGMOF ICF - https://geoportal.icf.gob.hn
2025 #30DayChartChallenge | day 03 | comparison | circular
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: https://stevenponce.netlify.app/data_visualizations/30DayChartChallenge/2025/30dcc_2025_03.html
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#rstats | #r4ds | #dataviz | #ggplot2
We're looking at Pokemon data for #TidyTuesday this week!
Stream plot showing speed and colour using {ggstream}
Image added with {ggimage}
Aiming for a minimalist, fun, and arty chart
Code: https://github.com/nrennie/tidytuesday/tree/main/2025/2025-04-01
Day 2 | Comparisons – Slope | #30DayChartChallenge. Analysis develop with R using #ggplot2, #tidyverse, #ggpmisc, , #terra, #ggtext, #showtext y #sf. Data source: Sentinel-2 MSI (2019-2024)
2025 #30DayChartChallenge | day 02 | comparison | slope
.: https://stevenponce.netlify.app/data_visualizations/30DayChartChallenge/2025/30dcc_2025_02.html
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#rstats | #r4ds | #dataviz | #ggplot2
#Day2 of the #30DayChartChallenge, theme: #Slope
Comparando pendientes: Índice Precios Vivienda (IPV) vs Índices Salario Modal (H/M, € const.) en España (2009-2021, Base 2015=100).
Visualiza la brecha creciente: el coste de la vivienda subió mucho más rápido que los salarios modales reales.
Datos: INE. Hecho con #rstats #ggplot2.
Código: https://t.ly/heDni
#Day1 of the #30DayChartChallenge, theme: #Fractions
Fracciones de Tenencia de Vivienda (Propiedad vs Alquiler/Otros) por Grupo de Edad en España (2024). Se ven claras diferencias generacionales.
Fuente: INE (Indicadores Calidad de Vida)
Hecho con #rstats #ggplot2
Código: https://t.ly/o0_y8
Día 1 | Comparaciones – Fracciones | #30DayChartChallenge. La visualización fue creada usando R basado en los paquetes #ggplot2, #dplyr, #scales, #ggtext, #patchwork, #showtext, #sf, #rnaturalearth, #rnaturalearthdata y #ggrepel. Fuente HDX - https://data.humdata.org/dataset/cod-ps-hnd
For #Day1 of #30DayChartChallenge, I tackled comparing proportions over time. Here’s what I came up with:
Code: github.com/gnoblet/30Da...
#rstats #dataviz #ggplot2 cc @30daychartchall.bsky.social
RE: https://bsky.app/profile/did:plc:7ebnmsusl3r2uuaf24igiazh/post/3llqfkva5r22g
gganimate is a powerful extension for ggplot2 that transforms static visualizations into dynamic animations. By adding a time dimension, it allows you to illustrate trends, changes, and patterns in your data more effectively.
The attached animated visualization, which I created with gganimate, showcases a ranked bar chart of the top 3 countries for each year based on inflation since 1980.
More information: https://statisticsglobe.com/online-course-data-visualization-ggplot2-r
Life has been 'lifeing'. Everything is chaotic and I'm just patiently waiting for May for a vacation. In the meantime, I am slowly working on my artpack package. I'm creating convenience functions, group_sample() and group_slice() that will allow you to quickly sample/slice entire groups out of data frames. This is something I personally do a lot for my art. Being able to drop groups of data can lead to some cool visuals sometimes: #rtistry w/ #ggplot2 in #rstats.
