#showtext — Public Fediverse posts

#Día23 | Series de Tiempo – Seasons (Temporadas) | #30DayChartChallenge | Malcolm in the Middle. Creada usando #Rstats con #ggplot2, #dplyr, #ggtext, #showtext, #patchwork, #scales y #glue.

#Día23 | Series de Tiempo – Seasons (Temporadas) | #30DayChartChallenge | Malcolm in the Middle. Creada usando #Rstats con #ggplot2, #dplyr, #ggtext, #showtext, #patchwork, #scales y #glue.

#Día23 | Series de Tiempo – Seasons (Temporadas) | #30DayChartChallenge | Malcolm in the Middle. Creada usando #Rstats con #ggplot2, #dplyr, #ggtext, #showtext, #patchwork, #scales y #glue.

#Day18 | Relationships – UNICEF – Data Day | #30DayChartChallenge | UNICEF Children's Climate and Environment Risk Index (CCRI). Built with #RStats using #ggplot2, #dplyr, #ggrepel, and #showtext.

#Día16 | Relaciones – Causalidad | #30DayChartChallenge | ¿Más personas = más ciudad?. Creada usando #Rstats con #ggplot2, # patchwork, #grid, #ggrepel, #scales, #showtext y #ggflags.

#Día15 | Relaciones – Correlación | #30DayChartChallenge | Población vs Área Urbana en Centroamérica. Creada usando #Rstats con #ggplot2, #ggrepel, #scales, #showtext y #ggflags.

#Day8 | Distributions – Circular | #30DayChartChallenge | Elevation distribution in the most circular department of Honduras. Built with #RStats using #sf, #raster, #exactextractr, #ggplot2, #ggnewscale, #ggtext, #dplyr, #terra, #showtext, #scales, #patchwork and #ggspatial.

Día 1 | Comparaciones – Part-to-Whole | #30DayChartChallenge. Distribución del área construida en Centroamérica según ESA WorldCover, donde el tamaño refleja los km² de suelo urbanizado por país. El gráfico fue creada usando R con los paquetes #ggplot2, #treemapify, #scales y #showtext.

Día 8 | Distribuciones – Histograma | #30DayChartChallenge. | Visualización hecha usando R con los paquetes #ggplot2, #dplyr, #patchwork, #sf, #ggtext, #showtext, #raster, #exactextractr, #ggscale y #scales.

Day 28 | Uncertainties – Inclusion | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #ggtext and #showtext | Source: Google Trends.

Día 9 | Distribuciones – Divergente | #30DatChartChallenge. | Visualización hecha usando R con los paquetes #ggplot2, #dplyr, #patchwork, #sf, #ggtext, #showtext, #raster, #exactextractr and #SPEI.

Day 24 | Timeseries – Data Day – WHO | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #patchwork, #ggrepel, #glue, #ggtext, #sf and #rnaturalearth. | Source: WHO.

Day 19 | Timeseries – Smooth | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #ggtext, #showtext, #patchwork, #sf and #rnaturalearth. | Source: Google Trends

Day 23 | Timeseries – Log Scale | #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #patchwork, #janitor and #scales. | Source: Our World in Data

Day 21 | Timeseries – Fossils| #30DayChartChallenge. Visualization made with R using #ggplot2, #dplyr, #showtext, #ggrepel and #janitor. | Source: Our World in Data

Day 12 | Distributions – Data Day – Data.gov | #30DayChartChallenge. Visualization made with R using #sf, #tigris, #ggthemes, #patchwork, #tidyverse, #ggtext and #showtext . | Source: data.gov - https://catalog.data.gov/dataset/biodiversity-by-county-distribution-of-animals-plants-and-natural-communities

Day 15 | Relationships – Complicated | #30DayChartChallenge. Visualization made with R using #tidyverse, #ggtext and #showtext . | Source: google trends https://trends.google.com/trends/explore?date=all&q=Avril%20Lavigne%20Complicated&hl=en

Día 11 | Distribuciones – “Stripes” | #30DayChartChallenge. La visualización fue creada usando R basado en los paquetes: #ggplot2, #dplyr, #sf, #lubridate, #ggtext, #showtext, #RcolorBrewer, #rnaturalearth y #cowplot. Fuente: CHIRPS.

Day 7 | Distributions– Outliers | #30DayChartChallenge. Visualization made with R using #ggplot2, #tidyverse, #terra, #ggtext, #showtext y #sf. Data source: Sentinel-2 MSI (2019-2024)

Day 6 | Comparisons – Florence Nightingale (theme day) | #30DayChartChallenge. Visualization made with R using #tidyverse, #ggtext and #showtext. Data source: HDX - https://data.humdata.org/dataset/cod-ps-hnd.

Day 5 | Comparisons – Ranking | #30DayChartChallenge. Visualization develop with R using #ggplot2, #dplyr, #ggtext, #showtext, #glue and #ggimage. Data source: Opta Analyst.

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

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)

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